What's new in Keypup

We are thrilled to announce that the Keypup MCP server can now do everything you do in the app: find your dashboards and insights, run the queries behind them, and create, edit, share and arrange them, with your own permissions. Your AI assistant can now build a complete dashboard from a single request.

Alongside this, the filter operators of the insight designer are now formula operators you can use anywhere in a query, the queries behind any insight can be retrieved through the API and the MCP server, and insights now explain clearly what went wrong when a query fails.

MCP Server: Everything You Do in the App, From Your AI Assistant

When we launched the MCP server, it could query your datasets, but it knew nothing about what your team had built in Keypup. To explain an insight, you had to describe it, and your AI assistant rebuilt a query that might not be the one the insight runs. To change a dashboard, you had to leave the conversation and open the app.

The MCP server now reaches parity with the app. Your AI assistant acts as you, with your permissions, on the records you can see, and nothing more:

• Build and Edit Insights: Your AI assistant can read an insight and change any part of it: its name, type, metrics, dimensions, filters, style and drilldowns. It can also create, copy and delete insights, and start from the app's library of ready-made insights. Every change is checked against the reporting engine before it is saved, so a broken insight never reaches your dashboard.
• Manage Dashboards: Create, rename, delete and pin dashboards, change their icon, share them, place insights on the grid and manage dashboard-wide filters.
• Manage Your Team: Update your team's settings, invite members, cancel invites, change roles and remove members, sign out sessions, and enable, disable or track projects.
• Look Up Your Setup: Search your dashboards, insights, projects, members and the rest of your team's setup, with the same visibility rules as the app. Ask "Which of my dashboards use the Commits dataset?" or "How many insights are on each of our dashboards?".
• Safe by Design: Actions that change data need the MCP server's mcp:write permission, the app's roles apply (editing a dashboard needs the editor role, managing members and projects needs the admin role), and every change is recorded in your team's audit trail.

Try asking your AI assistant "Build me a dashboard tracking pull request cycle time and review load for the backend team": it now ends with a working dashboard in your sidebar.

Check out the Using the MCP server documentation to connect your AI assistant.

New Formula Operators: The Insight Designer's Filters, Everywhere

The insight designer offers powerful filters, such as "is me", "includes any of" or "in the last N weeks". Until now, they only existed in the app: API and MCP queries had to rebuild them from lower-level operators.

The 36 filter operators of the insight designer are now formula operators, usable anywhere in a query: in filters, metrics and dimensions, from the API, the MCP server and custom formulas.

• Filter Operators as Functions: IS_ME, INCLUDE_ANY_OF, INCLUDE_ONLY, LAST_N_TIMEPERIOD, HAS_ANY_VALUE and the rest each have their own article in the functions dictionary. The AI Agent and the MCP server know how to use them.
• "Me" on the MCP Server: Queries run through the MCP server now know who is asking, so your AI assistant can answer "What are my open pull requests?" or "Which issues are assigned to me?" directly.
• ME() and USERNAMES() Return Usernames: ME and USERNAMES now return usernames instead of user IDs, so they work in formulas such as CONTAINS(assignee_usernames, ME()) ? "Mine" : "Other". If an API query compared them with user IDs, update it to compare with usernames.
• DIMENSION(): The new DIMENSION operator reuses a dimension of the same query in another dimension, a metric or a filter, by its position or its label. No more repeating a long formula when one dimension builds on another. The AI Agent and the MCP server know how to use it.

Retrieve the Queries Behind Any Insight

An insight is more than the formulas you see in the designer: dashboard-wide filters, "me" rules and formula dimensions all change the query it runs. You can now retrieve the exact queries behind an insight, ready to run, instead of rebuilding them by hand.

• Through the API: Insights now have a queries field on the Keypup API. Pass a dashboardId to apply that dashboard's filters, and asFormulas to get the metrics, dimensions and filters written as formulas.
• Through the MCP Server: Two new tools return the queries behind an insight or a whole dashboard, dashboard-wide filters included, and your AI assistant runs them as is. It can now explain what an insight shows, check its numbers, or break it down further: "Why did cycle time spike on my Delivery dashboard last week?".

Check out the Exporting insights as queries section of our API documentation to get started.

Other improvements and bug fixes

• Improvement: Dashboard-Wide Filters: Text and Text list filters can now be restricted to a list of allowed values. Viewers can only pick among those values, and picking nothing applies all of them, so the dashboard stays scoped to them. The Dashboard AI Agent knows about this setting.
• Improvement: Insights: A query error is now shown on charts, lists and KPIs, instead of an empty "no data" insight. The editor preview, the filter count, the CSV and JSON exports and the MCP server report it too.
• Improvement: Insights: Error messages now say what is wrong and where: a wrong argument type, a wrong number of arguments, an unknown function or an unknown field names the function, the argument and the types expected. Database errors that used to show as "Invalid query" are now explained in plain words.
• Improvement: MCP Server: Your AI assistant now builds reporting queries itself, which is faster and more reliable. The generate_dataset_query tool is deprecated.
• Bugfix: AI Agent: Fixed an issue where dashboard-wide filters taking no value (such as "is me" or "is empty"), and filters restricted to allowed values with none picked, were ignored in the AI Agent's dashboard summary and in the insight queries export. The AI Agent now sees the same numbers as the dashboard.
• Bugfix: Drilldowns: Fixed an issue where clicking a heatmap cell on a number or yes/no dimension opened the drilldown of the wrong record.

We are thrilled to announce that the AI Usage dataset now covers Claude Platform, OpenAI Platform and OpenAI Codex Enterprise: you can now compare how your engineers use Claude Code, the OpenAI API and Codex, side by side with GitHub Copilot.

Alongside this, GitHub Copilot metrics can now be imported once for your whole GitHub enterprise.

Claude & OpenAI: Every AI Coding Assistant in One Dataset

Most engineering teams don't use a single AI assistant. Some developers live in Claude Code, others in Codex or Copilot, and scripts call the APIs directly. Until now, only GitHub Copilot reached Keypup. To solve this, we are introducing three new AI integrations, available in beta under Settings > App management:

• Claude Platform: Imports the usage of your Claude Console organization: how many developers use Claude Code, where they use it (terminal, IDE, cloud), which models, how much code it writes, and the tokens your applications consume through the Claude API. See the Claude Platform integration article for the plans it covers.
• OpenAI Platform: Imports the requests made with your OpenAI organization's API keys, per user or API key and per model, including Codex run with an API key. See the OpenAI Platform integration article.
• OpenAI Codex Enterprise: Imports the Codex usage of your ChatGPT Enterprise or Edu workspace: which members use Codex, on which client (web, command line, IDE), the credits and lines of code, and the pull requests reviewed by Codex code review. See the OpenAI Codex Enterprise integration article.
• Connect with an Admin Key: Each integration connects with an admin key that you paste in Keypup, and our Help Center walks you through creating it. The first import retrieves up to one year of history (about 90 days for Codex Enterprise, as much as OpenAI keeps).
• Your Code Stays Yours: Keypup only retrieves the daily usage counts the providers publish. We never fetch your code or your prompts.

Every provider lands in the same AI Usage dataset, so a single insight can compare them. Try asking the AI Agent "How does our Claude Code usage compare with Copilot over the last month?".

Cursor is coming next. Check out the AI integrations collection to get started.

GitHub Copilot for Enterprises

If your Copilot subscription is managed by a GitHub enterprise, importing it organization by organization meant one project per organization, and a developer who belongs to several organizations appeared in each of them with the same activity. You can now import Copilot metrics at enterprise level.

• One Project for the Whole Enterprise: Your enterprise now appears in your list of GitHub accounts, with a Copilot Metrics project named after it. Enable it, and a single import covers every organization of the enterprise.
• Each Developer Counted Once: The enterprise-wide daily total counts a developer once, whatever the number of organizations they belong to. A new Enterprise aggregation level and an Enterprise day totals only quick rule let you report on it, and the AI Usage dashboard templates, the AI Agent and the MCP server know how to use it.

You need to be an enterprise owner, a billing manager of the enterprise, or hold the View Enterprise Copilot Metrics permission. If your enterprise does not appear, reconnect GitHub from the Apps page: GitHub connections made before this release did not grant the permission to list enterprises. Check out the updated GitHub Copilot integration article.

Other improvements and bug fixes

• Improvement: Design & UI: The connection pages of our self-hosted integrations (GitLab, Jira and Bitbucket) have been restyled.
• Bugfix: Dashboards: Fixed an issue where deleting a dashboard with "Also delete insight(s) that only belong to this dashboard" checked left those insights behind.
• Bugfix: GitLab: Fixed an issue where a temporary GitLab server error during a token refresh could disconnect your GitLab integration, instead of retrying later.

We are thrilled to announce the AI Usage dataset, starting with GitHub Copilot metrics: you can now measure how your engineers adopt AI coding assistants, right next to the pull requests they ship.

Alongside this, connecting your AI assistant to the Keypup MCP server now takes a single click, and the AI Agent is out of beta.

AI Usage Dataset: Measure AI Adoption Across Your Team

Your engineers use AI coding assistants every day, but how much, on which tools, and with what result? Until now, that answer lived in each vendor's admin console, disconnected from your delivery data. To solve this, we are introducing the AI Usage dataset!

• Daily Usage Metrics: Interactions, suggestion acceptance, credits consumed and code contribution, broken down by user, model, surface (IDE completion, chat, agent mode, CLI, code review), client and language.
• GitHub Copilot, with One Year of History: The GitHub integration now retrieves Copilot usage metrics. Enable the Copilot Metrics project that appears in your list of GitHub projects, and Keypup imports up to one year of history on the first import.
• The AI Adoption & Usage Dashboard: A new dashboard template tracks active developers, adoption by model and surface, suggestion acceptance rate, credit consumption, code contribution, a developer leaderboard and pull request outcomes.
• Everywhere You Report: The dataset is available in insights, the API and the MCP server, and both the AI Agent and the MCP server know how to query it. Try asking your AI assistant "Which models do our engineers use most, and has our acceptance rate improved this quarter?"

GitHub Copilot is only the start. The AI Usage dataset is built to hold every AI coding assistant side by side, so you can compare them on the same insights. Claude Platform (including Claude Code) is coming next, followed by Cursor and OpenAI (the API Platform and Codex). Stay tuned! 🤖

Every field is documented in the AI Usage dataset collection. To get started, check out our GitHub Copilot integration article for the prerequisites.

MCP Server: Connect in One Click with OAuth

Connecting an AI assistant to the MCP server used to mean generating an API token and pasting it into a configuration file. The MCP server now supports OAuth: your AI client opens Keypup, you approve the connection, and you're done.

• Simpler and More Secure: OAuth tokens expire and are never handled by hand, so there is no long-lived token to store or leak. API tokens remain available if you prefer them.
• Automatic Client Registration: Clients that support Client ID Metadata Documents, such as VS Code and Claude, register themselves automatically. We have also pre-registered several popular clients and will keep adding more.
• MCP Setup Page: A new MCP Setup page, available from the sidebar, gives the setup instructions for each AI client, including ChatGPT, with screenshots.
• Clear Scopes: The new mcp:read and mcp:write scopes enable every MCP capability, now and in the future, and are the default when you connect over OAuth. Every scope now has an info bubble explaining what it grants, and new scopes let you manage Pin Groups through the API.

The MCP server has also learned a few things: it can read your team's AI Instructions, and the list of teams now includes their connected apps, so your AI assistant starts every conversation with the right context. Check out the updated Using the MCP server documentation.

Other improvements and bug fixes

• Improvement: AI Agent: The AI Agent is out of beta, and now runs on Gemini 3.8 Flash by default.
• Improvement: AI Agent: Custom fields are no longer all sent to the AI upfront. The AI Agent now looks them up when your question needs one, which makes answers faster and fixes a permanent error for teams with a very large number of custom fields.
• Improvement: Performance: Insights that filter on custom fields are faster, when using the "equal" and "contains" operators.
• Improvement: Jira: Changes to Fix Versions, such as a new release date, are now reflected on the associated issues in near real time. Previously they could get out of sync, because Jira does not send an issue update when a Fix Version changes.
• Improvement: Pin Groups: The open or closed state of each pin group on the sidebar is now remembered across page reloads.
• Improvement: MCP Server: When a team has no active plan, the MCP server now responds with an explanation and a link to the billing page, instead of a generic error.
• Bugfix: Bitbucket: Bitbucket restricted access to review data without notice. Bitbucket no longer lets us retrieve the number of approvals required on a pull request. A ticket has been opened with them to reinstate this feature.
• Bugfix: Business Duration Operators: Fixed a calculation that added one day to BUSINESS_DAYS durations when the start date's time of day was later than the end date's.
• Bugfix: AI Agent: The AI Agent can now add OR and AND filter groups on every type of insight, not only card feeds.
• Bugfix: Custom Formulas: An invalid custom formula now returns a detailed error explaining what is wrong, instead of a generic error.
• Bugfix: Custom Fields: Fixed the names of Jira custom fields built from lists of values, such as Fix Version release dates.
• Bugfix: Pin Groups: Fixed the "others" group staying collapsed after switching teams, which made the list of dashboards look empty.
• Bugfix: Dashboards: Choosing "edit" on a dashboard from the collection view now opens it in edit mode, and saving no longer sends you back to the collection.
• Bugfix: Login: Fixed an issue where you could land on the onboarding page instead of your dashboards after logging in, and signup and login links now keep their parameters.
• Bugfix: MCP Server: Fixed a response format issue that prevented some AI clients from listing teams.

We are incredibly excited to announce the release of the Keypup MCP (Model Context Protocol) Server!

This release marks a major step forward, allowing you to connect Keypup's powerful engineering analytics directly to your favorite AI assistants (like Claude Desktop, Cursor, Kiro, and any other MCP-compatible client).

The Keypup MCP Server

Instead of writing code or manually building queries, you can now ask questions about your engineering activity in plain language, and your AI assistant will orchestrate everything on your behalf.

The MCP server exposes a focused set of tools that allow your AI to:

• Discover your workspace (list teams/companies you belong to).
• Explore datasets (browse fields across PRs, issues, commits, comments, etc.).
• Discover formula operators for building precise metrics and filters.
• Generate and run reporting queries directly from your natural language requests!

You can ask open-ended questions like "How many pull requests did we merge each month over the last 6 months?" or "Who are our most active reviewers this month?" and the AI will automatically fetch the schema, build the query, execute it, and explain the results to you.

The MCP server is currently in beta and focused on building and running reporting queries. See MCP use cases

In the near future, we will expose the full capabilities of our GraphQL API, as well as the insight-building capabilities currently provided by our platform's AI Agent!

Want to get it set up? Check out the Using the MCP server documentation.

Granular API Scopes

To support the MCP Server and enhance general security on the API, we have concluded our chapter on API Scopes.

When generating API tokens, you can now choose specific permission levels (scopes) to follow the principle of least privilege.

For example, you can create a read-only token exclusively for your MCP client. Check out the updated Using the API documentation for full details.

Other improvements and bug fixes

• Improvement: Insight Edition Performance: We’ve deployed a massive performance improvement to the insight edition screen. Teams utilizing a high number of custom fields will notice that field dropdowns are now highly scalable, completely eliminating previous page-freezing issues.
• Improvement: KPIs: Custom dimensions are now fully supported for filtering and drilldowns on KPIs (previously, this was only possible on regular charts/tables).
• Improvement: Dashboard AI: Changes made by the AI Agent to Markdown widgets are now reflected immediately on the dashboard without requiring a page reload.
• Improvement: Dashboard Analyze Button: If you already have an active AI discussion open, clicking the "Analyze" button on a dashboard will now append the analysis request to your ongoing chat rather than doing nothing.
• Bugfix: Dashboard-Wide Filters: You can now copy the text values from locked dashboard-wide filters (previously, text selection was blocked).
• Bugfix: Linked Dashboards: Fixed an issue where the system would unnecessarily offer you the ability to delete orphan insights when deleting a Linked Dashboard (the checkbox didn't do anything in this context anyway).
• Bugfix: KPI with Trend/Chart: When editing a KPI, the background color that highlights which rows are being factored into your trend line now correctly takes precedence over the striped table row colors, making it much easier to see your data selection.
• Bugfix: Dashboard Edition: Fixed a UI glitch where the top bar would overflow to the right when saving a dashboard with a very long description.
• Bugfix: Dashboard Edition: Fixed a visual bug where new decorators (like horizontal/vertical bars) would briefly disappear while the dashboard was saving, which was particularly noticeable on larger layouts.

We are incredibly excited to introduce a game-changer for scaling your reporting: Linked Dashboards!

Alongside this, we're bringing major enhancements to the AI Agent and rolling out several UI improvements and fixes to streamline your experience.

Linked Dashboards: Scale Your Reporting Effortlessly

When duplicating a dashboard, you now have the option to create a Linked copy instead of a full, independent copy. This highly requested feature fundamentally changes how you can manage metrics across multiple teams and projects.

A Linked Dashboard acts as a delegate that stays in perfect sync with its "source" dashboard. Any changes you make to the source dashboard's layout, insight configurations, or decorators (like text boxes) are automatically and instantly reflected across all of its linked copies.

What makes this so powerful is that you can still customize the outset of the linked copy: the name, icon, sharing permissions, and - most importantly - dashboard-wide filters.

Typical use cases include:

• Team-specific views: Build one master dashboard layout, then create a linked copy for each team with their specific project or assignee filter presets applied.
• Consistent reporting: Guarantee that all stakeholders are looking at the exact same metrics and layout, while still allowing them to customize their individual filter parameters.

When viewing a linked copy, a handy indicator in the top bar will show you the name of the source dashboard so you always know where the structure is managed. Want to dive deeper? Check out our updated dashboard duplication documentation.

AI Agent: Deeper Analysis & Viewer Access

The AI Agent continues to get smarter and more accessible to everyone on your team.

• Dedicated "Analyze" Button: We've added an "Analyze" button right next to the "Ask AI" button. Under the hood, we've considerably fleshed out the instructions for dashboard analysis, allowing the AI to generate much better-structured, data-driven commentary on your metrics.
• Accessible to Dashboard Viewers: The AI Agent is no longer restricted to just dashboard editors! Dashboard viewers can now open the AI Agent in a read-only mode to analyze the dashboard's results or change dashboard-wide filter values safely.
• Linked Dashboard Support: The AI Agent is also fully available on linked dashboards, intelligently adapting to offer a reduced set of editing capabilities that respect the locked layout of the linked structure.

Other improvements and bug fixes

• Improvement: Guest Role: Guest users are once again allowed to change dashboard-wide filter values. (Note: Dashboard maintainers can still lock or hide specific filters if they need strict control over what guests can change).
• Improvement: Team Management: Keypup Support accesses are now explicitly highlighted on the team list screen, clearly showing the support role and when the access is scheduled to expire.
• Improvement: Design & UI: We've polished several areas of the interface. This includes an improved general loading screen, a cleaner automated loading state when adding templates, fixed insight sorting in the dashboard-wide filter modal, corrected dark colors on Sidebar dashboard icons, a more vibrant color scheme for the drilldown preview table, and fixed button styles in the Duplicate modal.
• Bugfix: Insight Doc Editor: Fixed an issue where the height of the documentation editor would appear entirely squashed when empty.
• Bugfix: Widget Configuration Assistant: Fixed the behavior of the "Back" button, which previously failed to navigate back reliably in certain cases.

We are incredibly excited to roll out a massive update focused entirely on your user experience. We've completely redesigned the look and feel of Keypup to make your data more readable, and we've introduced a highly requested feature to help you organize your growing list of dashboards.

A Beautiful, Modern UI Redesign

As your analytics needs grow, you spend more time deep inside your dashboards. We realized the Keypup experience needed to match the sophistication of the data it presents. We went back to the drawing board and polished the visual layer!

Say goodbye to flat white cards and hello to a sleek, modern, glassmorphic design. We’ve introduced a crisp new typography system, ambient animated backgrounds, and translucent glass cards with subtle backdrop blurs that give your metrics room to breathe.

• Clearer Hierarchy: The top header has been decluttered, pushing your eyes straight to the data. The sidebar has been refined with grouped sections for easier scanning.
• Smoother Interactions: The interface now responds with elegant micro-animations. Cards lift gently on hover, buttons shimmer, and focus states glow softly.
• Your Data is Untouched: Crucially, this redesign is purely about the "chrome" around your insights. Every user-controlled customization - chart colors, metric labels, threshold ranges - works exactly as before.

This visual overhaul provides better contrast and readability, turning Keypup from a utility dashboard into a premium analytics command center. Long sessions deep in the numbers just got a lot more comfortable!

Pin Groups on the Sidebar

If your team manages dozens of dashboards across different concerns - delivery tracking, code quality, sprint planning, individual views - a flat list of pinned items can quickly become overwhelming. To solve this, we are introducing Pin Groups!

You can now organize your pinned dashboards into custom, collapsible sections directly on the sidebar.

• Fully Customizable: Create labeled groups (like "DORA Metrics" or "Sprint Health") and assign them custom icons and accent colors. You can visually distinguish categories at a glance, even when the sidebar is collapsed down to icon-only mode.
• Drag-and-Drop Organization: Moving a dashboard is as easy as dragging it from the list and dropping it into your target group. The UI updates instantly.
• Keep it Tidy: Groups are collapsible, meaning you can tuck away the dashboards you aren't actively using to keep your navigation clean and focused.

This is a massive release! Following the recent launch of our insight-level AI Agent, we are thrilled to introduce the Dashboard AI Agent. You can now build, modify, and fine-tune entire dashboards using natural language.

The Dashboard AI Agent

The Dashboard AI is a conversational assistant built directly into the dashboard experience. You simply open it, describe what you want in plain English, and it makes the changes for you—no manual clicking through menus required.

At the dashboard level, the AI Agent acts as your personal data architect. It can rename your dashboard, change its icon, and add, remove, or reposition insights on the grid. It can even insert markdown blocks and separators to structure your layout, manage dashboard-wide filters, and map them to specific fields across all your insights. If you need inspiration, the AI can search Keypup's template library or your personal collection to find and insert pre-built insights.

Of course, it retains all the deep insight-level capabilities: switching visualization types, configuring complex metrics with custom formulas, setting up drilldowns, and styling everything from axis labels to KPI thresholds. All changes are staged in real-time, allowing you to review the dashboard updates before saving them.

Starting fresh? An empty dashboard now features a central prompt box so you can immediately tell the AI what you want to build.

Smart Fine-Tuning

Every team works differently, and standard dashboard templates don't always capture your unique workflows out of the box. To solve this, we've introduced AI Fine-Tuning. When you ask the AI to fine-tune a dashboard, it keeps the core structure (the same insights) but intelligently adapts the metrics, filters, and dashboard-wide variables to match your team's specific habits and custom fields.

We've integrated this directly into the creation of dashboard templates. You can now choose between the classical experience, where you answer questions or the AI experience, which automatically gather contexts about your team and habits.

New Formula Operators: Business Timelines & Version Sorting

We've added three highly requested operators to make your custom formulas even more powerful:

• TIMELINE_BUSINESS_DAYS and TIMELINE_BUSINESS_HOURS: These operators are a game-changer for workflow reporting. They combine the power of our timeline tracking with business hour logic, allowing you to calculate exactly how many working hours or days an issue stayed in a specific status (e.g., "In Review" or "Blocked").
• VERSION: This new operator tells the formula engine that a string represents a software version (e.g., 1.100.5). This ensures proper version sorting, where 1.100 correctly evaluates as greater than 1.99 (which standard alphabetical sorting would get wrong).

Other improvements and bug fixes

• Improvement: AI Defaults: The AI Agent will now default to sorting time-based fields in descending order, as this is the most natural behavior for building time series charts.
• Improvement: Dashboard Deletion: Drastically sped up the deletion time when deleting a dashboard and all of its associated insights.
• Bugfix: Report Insights: The AI Agent can now successfully configure drilldowns when the report utilizes metrics.
• Bugfix: Cycle Time KPI: Fixed an issue to allow the AI Agent to modify the trend/sparkline section of KPI widgets.
• Bugfix: Drilldown on table: Fixed an occasional issue where metrics on a report insight could not be drilled down.

This is a massive update! We are taking a fundamental leap forward in how you interact with your engineering data by introducing the AI Agent, a fully autonomous, data-aware successor to our previous AI Agent.

Plus, our API is officially out of beta and available to everyone!

Meet the AI Agent: A Smarter Way to Build Insights

The AI Agent was great for conversational configuration, but it had a limitation: it wasn't aware of your actual project data and relied on one-shot generations. The new AI Agent changes everything.

It is a tool-equipped, autonomous agent that doesn't just suggest configurations - it actively does the work for you, step-by-step.

Powered by advanced reasoning (function calling), the AI Agent works iteratively. If you ask it to "show only bug-related pull requests," it will first query your actual database to see what label values exist, and then set the correct filter.

No more guessing field names or filter values!

Analyzes Data and Acts with Full Transparency

The AI Agent is equipped with over 40 specialized tools, giving it complete control over visualization types, complex filters, drilldowns, custom formulas, and even chart styling (like setting threshold-based colors for KPIs).

Even better, the Agent can read and analyze your actual insight results. You can simply ask it, "What trends do you see?" and it will read the data points on your chart and provide meaningful, data-driven commentary.

Every action the Agent takes is completely transparent - you can expand the new "Agent Actions" section to see exactly what steps it took, ensuring nothing happens in a black box.

AI Steering is now AI Instructions

To better reflect its purpose, we have renamed "AI Steering" to AI Instructions. Accessible via Team Management, this is where you can teach the AI Agent your team's specific habits, workflows, and label conventions.

Because the new Agent is data-aware, it utilizes these instructions far more effectively to make intelligent decisions on your behalf. Check out our new dedicated article on AI Instructions to learn more.

Other improvements and bug fixes

• Improvement: The Keypup API is out of beta! It is now generally available to all users, allowing you to seamlessly integrate Keypup's engineering metrics programmatically into your own workflows. The API documentation has been updated accordingly.
• Improvement: Increased the global Custom Fields limit from 1,000 to 2,000 across all applications, giving power users even more room for complex reporting.
• Improvement: Custom fields are now updated in near-realtime when you connect new apps or projects. No more manual page reloads required to clear the cache.
• Improvement: Added a convenient cogwheel icon to the Dashboard Filter "quick edit" popover, allowing you to edit the filter's configuration directly without having to put the entire dashboard into edit mode.
• Improvement: Continued UI performance optimizations. We've significantly reduced the number of background queries and implemented data pre-loading to make the interface feel much snappier.
• Improvement: Refined the AI Agent chat UI so that auto-scrolling is automatically disabled when a user intentionally scrolls up to read previous messages.
• Improvement: Enhanced stability and disconnection detection for our Jira integration
• Improvement: Added support for legacy Epic Links in the Jira connector (primarily for Jira Data Center instances), alongside the currently recommended Parent Link.
• Improvement: Added Azure DevOps (ADO) as an official login and signup option on our authentication pages.
• Improvement: Insight filters using comma-separated lists (e.g., "equals any of") now support comma-escaping. This is handled transparently when using the value picker, allowing you to easily select values that naturally contain commas (like john, D).
• Improvement: Added the ability to bulk-apply a field across all unspecified links in the Dashboard-wide Filters modal, drastically speeding up your dashboard filter configuration.
• Improvement: An initial value is no longer required to save a Dashboard-wide filter. The operator now defaults to "has any value" across all cases (including presets or type changes).
• Improvement: Cleaned up the drilldown modal by restricting the displayed "coordinates" of the selected data point to only show the values actually used for filtering (e.g., just the ID or Key). This prevents massive, ugly blocks of text from appearing when clicking on complex aggregate reports.
• Bugfix: Fixed an issue where regular dashboard filters placed after a hidden filter would incorrectly show as "edited" and display save/cancel buttons.
• Bugfix: Resolved a UI flickering issue that occurred when editing the content of dashboard-wide filters.
• Bugfix: Enabled the Value Picker for Sprint Names in filters, which had been previously omitted.

We are thrilled to announce the release of our integration with Azure DevOps Boards! Alongside this major addition, we have deployed significant performance updates to both the user interface and our AI engine.

Azure DevOps Work Items

You can now track Azure DevOps Work Items directly within Keypup. This brings your project management data under the same roof as your development data, allowing for powerful cross-functional reporting.

• Track Sprints & Issues: visualize work items, track sprint progress, and manage backlogs seamlessly.
• Link with Pull Requests: correlate your development efforts with your project management items to see the full picture of delivery.
• Custom Fields Support: Just like our other integrations, we support ADO custom fields, ensuring your unique workflows are fully captured in your reports.
• Group and Filter PRs based on Issue Custom Fields: This allows you to report on engineering data based on business-oriented classifications and explore your ADO data like never before.

Charting Performance & Progressive Loading

We have overhauled how insights are loaded and displayed to ensure the platform remains snappy, even when crunching large datasets.

• Progressive Loading: Charts now load data in pages rather than all at once. A new thin progress bar above the insight gives you real-time feedback on the data fetching process.
• Configurable Data Limits: You can now configure the number of data points displayed on a chart (default is 10k). This allows you to increase the depth of reporting or decrease it for speed.
• Stability Guardrails: To prevent browser freezes on extremely complex visualizations, we have introduced hard limits for multi-series charts (100 series) and heatmaps (10k cells). If a query exceeds these limits, a clear message is displayed, prompting you to refine the dataset or adjust the limit.
• UI Snappiness: The insight editor has been optimized to handle reports with a high number of columns and custom fields without becoming sluggish.

AI Engine Upgrade: Faster and Smarter

We have upgraded the underlying engine of our AI Agent to Gemini 3 Flash. This round of improvements also prepares the next generation of AI agent for Keypup. Stay tuned! 🤖

• Drastic Speed Increase: Query times have dropped significantly (e.g., from over 2 minutes to under 15 seconds in some cases).
• Improved Infrastructure: We have migrated to a more robust infrastructure and optimized the amount of context sent to the model. This eliminates throttling issues and ensures the AI is more responsive and accurate.
• Better Error Handling: Error messages are now much friendlier and helpful.

Other improvements and bug fixes

• Improvement: Custom formulas: The ARRAY_FIND operator now supports Regular Expressions (regex) instead of just strings, offering more flexibility in finding data.
• Improvement: The detection of "disconnected" apps and projects has been considerably improved to reduce the number of false positives.
• Improvement: Reconnecting app now resumes since the last successful import instead of re-importing all disconnected projects from scratch. This considerably speeds up the reconnection process when an authorization token has expired.
• Fix: Connector Bitbucket: Fixed the connection flow for Bitbucket Hosted users who have special characters in their usernames. We also added several fallbacks to handle API oddities when retrieving PRs and commits.
• Fix: Drilldown: Fixed an issue where clicking on a data point with a null value on the X or Y axis (typically in heatmaps) would incorrectly drill down into a different data point.

This release brings a major leap forward for our AI Agent, giving you more control and context than ever before. We've also significantly expanded our data model for Parent Issues and unlocked powerful workflow reporting for GitHub Projects.

AI Instructions and Dashboard Context

The AI Agent is now smarter and more adaptable to your specific needs.

We've introduced AI Instructions, a new settings section on the team screen that allows you to configure context at the team level. You are now in control of the data passed to the AI, specifying preferred groupings, labels, teams, and calculation preferences to ensure the answers you get are perfectly tailored to your team's workflow.

Additionally, the AI now possesses Dashboard Context. It can "see" the list of insights on the dashboard you are currently working on. This means you can now ask it to iterate on existing work with natural prompts like, "Do something similar to insight 'Team Velocity' but change the calculation to be based on Story Points."

Under the hood, we've also massively improved the reliability of AI answers. Check out the new version and let us know what you think! 🤖

Parent Issue Data Model Expansion

We have significantly expanded the data model to expose richer information about Parent Issues across both Issues and Pull Requests.

• Custom Fields: Parent Issue custom fields are now fully exposed. You can now filter Jira issues based on their parent Epic's custom fields, unlocking new depths of reporting.
• Core Attributes: We now expose core attributes like project, workflow_status, past_workflow_statuses, and workflow_timeline for parent issues on both the Issues/PRs and Activity Events datasets.
• Parent Issue for Pull Requests: Pull Requests now expose the first resolved issue as Parent Issue. This gives more granular control on PR reporting based on related issue attributes. This approach relies on a new ranking logic for resolved issues, which uses the order of appearance of issue keywords in auto-closing fields (branch name, title, body, commits).

GitHub Projects: Workflow Reporting

We are now capturing transition events for GitHub Projects! This is a game-changer for teams using GitHub Projects, as it unlocks full workflow reporting capabilities.

You can now utilize the Issue Cycle Time dashboard to track and analyze the movement of your cards across columns, giving you deeper insights than most issue trackers.

Other improvements and bug fixes

• Improvement: Formula Operators: Added COUNT_IF_CUMULATIVE and COUNT_IF_TOTAL operators, simplifying calculations that previously required conditional SUMs.
• Improvement: Formula Operators: All TIMELINE_* operators are now case-insensitive regarding status names.
• Improvement: Insights: Insight are no longer limited to 1000 data points and now fetch data pages progressively. This prevents data truncation on dense visualizations like heatmaps.
• Improvement: Insights: Added a style option to explicitly display data point values on charts, which is perfect for static reporting and screenshots.
• Improvement: Dashboard Filters: Added support for "hidden" or "locked" dashboard-wide filters, allowing for "global variable" style configurations.
• Improvement: Dashboard Filters: Changed the default operator to "has any value," allowing filters to be saved immediately after mapping fields, without value selection.
• Improvement: Dashboard Templates: Added support for Azure DevOps (ADO) in the PR Cycle Time dashboard and GitHub Projects in the Issue Cycle Time dashboard.
• Improvement: Drilldown: The recommended drilldown configuration now automatically includes all chart dimensions and extracts formulas from inside metric aggregators to create calculated drilldown columns.
• Improvement: Drilldown: FLATTEN dimensions are now properly detected and handled with a "contains" filter instead of an "equal" filter.
• Improvement: Data Model: Exposed Project Source on Activity Events, a requirement for the new GitHub Projects transition events.
• Fix: GitHub: Fixed an issue where commits would not resync upon receiving a PR push update via webhook.
• Fix: Jira: Do not flag projects as disconnected when Atlassian returns an "access forbidden" error due to a migration on their servers.
• Fix: Insights: URLs in report cells are no longer truncated, ensuring links remain clickable.

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We are thrilled to announce our latest integration with Microsoft's Azure DevOps! You can now connect your Azure DevOps organizations to Keypup, whether you're using the Cloud version or the self-hosted Server version (2022.1 and later). This new integration brings a wealth of data from your Azure DevOps projects into Keypup, allowing you to gain deeper insights into your development workflows and make data-driven decisions.

What's new?

Our Azure DevOps integration allows you to import and analyze a wide range of data from your repositories, including:

• Pull Requests: Track the entire lifecycle of your pull requests.
• Comments and Reviews: Understand the conversation and feedback happening around your code.
• Commits: Get insights from the commits associated with your pull requests.
• Activity Events: Monitor events like pull request creation, closure, and assignments.
• Build Statuses: Keep an eye on the CI/CD pipeline by tracking the build status of your pull requests.

Key Benefits for Your Team

By connecting Azure DevOps to Keypup, you can unlock a number of benefits:

• Comprehensive Metrics: Calculate key industry metrics, including DORA metrics, to measure and improve your team's performance.
• ‍In-depth Analysis: Drill down into specific aspects of your development process. For example, you can easily find all pull requests that are currently awaiting a peer review or identify pull requests that were merged with a failed build.
• ‍Real-time Insights: Stay up-to-date with real-time data synchronization from Azure DevOps via webhooks.
• ‍Code-level Insights: Understand the impact of your team's work by analyzing commit messages and calculating metrics like the refactoring ratio (lines of code deleted vs. added).

• ‍Improved Reporting: By linking pull requests to issues, Keypup can automatically enrich your data, helping you to better track due dates and the resolution state of your work items.

Getting started is easy. Simply connect your Azure DevOps organization to your Keypup account and start getting meaningful insights in minutes. We're excited to see what you will uncover!

We’re thrilled to share that Keypup is now officially SOC 2 Type II compliant!

(SOC 2 compliance = the gold standard for data security)

This rigorous certification focuses on security, availability, processing integrity, confidentiality, and privacy—ensuring that your most critical data is protected.

Why this matters:

Achieving this milestone reflects our commitment to safeguarding our customers' and partners' information. This certification is a testament to our dedication to security, reliability, and collaboration.

Details about all our Security Control Points can be found in our Trust Center.

We are proud to contribute to a safer digital World! ☀️​

We're excited to roll out a set of powerful new formula operators that unlock more sophisticated data analysis, alongside significant enhancements to your AI Agent! Get ready for more precise metrics and a smarter conversational experience.

Unlock Business Time Calculations and Powerful String Manipulation with New Operators!

You asked, and we listened! A major highlight of this release is the introduction of the highly anticipated BUSINESS_DAYS and BUSINESS_HOURS operators. These functions finally allow you to accurately measure time elapsed between two dates specifically during your defined working hours and days, providing a crucial capability for calculating true cycle times, lead times, and other metrics that respect your team's actual work schedule.

But that's not all! We've also added operators that bring powerful string and array manipulation capabilities to your custom formulas:

• ARRAY_RANGE (or myarray[start_index..end_index]): Easily select a specific range of elements from any array. Useful for focusing on, for example, the last two assignees or the first three labels.
• REGEX_EXTRACT: Extract substrings from a text field based on a POSIX regular expression. Perfect for pulling out specific IDs, version numbers, or other patterns from strings.
• REGEX_REPLACE: Perform sophisticated find-and-replace operations using regular expressions. Great for reformatting text fields or cleaning up data based on patterns.

These new operators empower you to tailor your metrics with greater precision and flexibility than ever before. Full documentation is available for each new operator!

AI Agent Gets Smarter with Custom Field Awareness

Our AI Agent continues its journey to become your most powerful reporting tool! In this new version, we've made significant strides:

• Custom Field Integration: The AI Agent is now aware of company-app-specific custom fields from Jira and GitHub! When you ask the AI to build an insight, it understands your custom attributes, allowing for more relevant and precise reporting tailored to your specific setup.
• Improved Reliability: We've squashed a few bugs preventing the AI-generated widgets from being saved occasionally, making the whole experience more stable.
• Enhanced KPI Understanding: Thanks to a related bugfix, the AI now has a slightly improved understanding of KPIs with trend/sparkline visualizations.

These updates make the AI Agent a more reliable and powerful partner in exploring your data and generating insights based on the specifics of your engineering workflow.

Other improvements and bug fixes

• Improvement: Widget Edition: Cancelling widget edits now correctly redirects back to the dashboard and scrolls to the widget's position, preventing loss of scroll state.
• Bugfix: KPIs with trend/sparkline: Prevented the removal of the dimension in the trend/sparkline configuration, as it's essential for visualizing evolution.
• Bugfix: Formula Custom Fields: The list of custom fields in the formula help assistant (F1) now correctly updates when switching between teams.

We're incredibly excited to introduce the Keypup AI Agent, a revolutionary new way to unlock deep engineering insights and get the data you need, faster than ever before. Say goodbye to building complex dashboards from scratch and hello to simply asking questions in your own words!

Introducing the AI Agent

The AI Agent is designed to make software development analytics radically simple and accessible. It leverages the full power of Keypup's advanced data engine and your connected applications (like Git and Jira, including custom fields!) to instantly generate the insights you need.

• Ask in Plain Language: No more technical query building or complex formulas required. Just type your question in plain English (or any language!), and the AI Agent understands your context and intent.
• Get Instant, Tailored Insights: The AI Agent provides fully-formed analytics, building charts and reports with the correct data, dimensions, and calculations, often in just a single click.
• Turn Curiosity into Clarity: Whether you want to understand team workload, compare metrics based on specific criteria (like PR size), or get historical reports, the AI Agent helps you quickly validate hypotheses and gain a clear picture of your team's performance.
• Make Insights Self-Explanatory: The AI Agent can even explain existing insights, detailing the calculation, the business objective, and how to interpret the results, empowering everyone on your team.

The AI Agent is the world's first platform to combine advanced data power with the radical simplicity of a conversation. Stop building dashboards, and start asking questions to get instant, precise software development analytics tailored to your needs.

Ready to experience the future of engineering insights? Learn more about the AI Agent here

Other improvements and bug fixes

• Improvement: Jira Integration - The "Team" field (and any "team type" field) is now available as a custom field on Keypup
• Improvement: Issues & PRs dataset - the Workflow Status field is now exposed on the Parent Issue.

We’re proud to announce that Keypup has officially achieved ISO/IEC 27001 certification!

This marks a significant milestone for our team and highlights our steadfast commitment to information security. It reinforces our dedication to delivering a safe and secure experience for candidates and recruiters worldwide.

Achieving ISO 27001 certification means we meet stringent international standards for establishing, implementing, and continuously improving an information security management system (ISMS). This accomplishment demonstrates the strength of our data protection and security practices, ensuring we meet and exceed the expectations of our enterprise customers.

Details about all our Security Control Points can be found in our Trust Center.

Here’s to raising the bar for security and trust across the industry! 🚀

‍

This update brings powerful new capabilities to Keypup, headlined by our integration with GitHub Projects and a suite of versatile reporting fields. Seamlessly track your GitHub Projects data and gain unprecedented control over your reporting!

GitHub Projects Integration: Gain Project-Level Visibility for your Repositories

Now you can properly track issues and pull requests managed through GitHub Projects, gaining a comprehensive view of your project's progress directly within Keypup. Our integration goes beyond simple issue tracking, allowing you to:

• Track Multiple Projects: An issue or Pull Request can belong to multiple GitHub Projects, and Keypup captures this, allowing you to analyze progress across different project management layers.
• Leverage Project-Specific Fields: Each GitHub Project's status, iteration (mapped as Sprint in Keypup), and custom fields are imported, enriching your reporting with project-level context.
• Avoid Data Duplication with Filtering: To prevent confusion arising from duplicated issues across different GitHub Projects, leverage Project-level or App-level filtering to ensure your reporting focuses on the right project.
• Access Key Project Data: The integration captures key attributes like Status (mapped to Workflow Status), Iteration (mapped to Sprint attributes), Project Name, and Project Source, enabling richer reporting and analysis.
• Filter by Sprint Attributes: Leverage Sprint attributes (Sprint Name, Sprint End Date, Sprint Start Date, etc.) to filter issues and pull requests based on project iterations.
• Complement Existing Integrations: Our GitHub Projects integration supplements your existing GitHub integration, providing project-level insights on top of repository data.

To know more about it, read our dedicated article about GitHub Projects.

New Reporting Fields: Source Workflow Status & Cross-entity fields

Take your reporting to the next level with our newly added reporting fields. Filter across resolved issues & PRs, generate historical "at date" charts on activity events and calculate more granular metrics like Review Cycle Times!

• All Datasets > Project Account: exposes the name of the parent organization/workspace.
• Activity Events > Source Workflow Status: capture the source status on transition events. See our new insight Historical in status at date for an example of usage.
• Issues/PRs > Project Source: used to capture the underlying repositories with GitHub Projects.
• Issues/PRs > Resolved Issue Projects: provide the ability to filter PRs based on resolved issue projects.
• Issues/PRs > Resolving PR Projects: provide the ability to filter issues based on resolving PR projects.
• Reviews > Requested at: capture the moment the review was requested for each review.

Other improvements and bug fixes

• Improvement: Drilldown/Filters - allow custom dimensions (using formulas) to be used in filters and drilldown. The drilldown auto-configurator now takes into account custom dimensions.
• Improvement: Drilldown/Filters - the field dropdown will now display suggested fields at the top of the dropdown based on the reporting dimensions used in the insight.
• Improvement: GitHub Integration - Capture manually linked issues (through the GitHub UI) on top of issues referred to in PRs/commits via auto-closing keywords.
• Improvement: New template Historical in status at date - This new insight is similar to the “Historical open at date”, showing the number of issues that were in a specific status (or list of statuses) at a given date + moved in/out trends.
• Improvement: Dashboard Value Stream Management / Insights with custom dimensions - The drilldown has been updated on several insights to only display the records related to the clicked dimension.
• Bugfix: Drilldown - It is now possible to drilldown on null values
• Bugfix: Jira Integration - Add logic to detect and remove duplicate activity events. Jira sometimes generates duplicate changelog transition events for issues.
• Bugfix: Jira Integration - Add logic to resync child issues when a parent issue is updated. Jira silently updates child issues when a parent is updated (e.g. Sprint attribute)
• Bugfix: Dashboard Delivery / Deployment Frequency KPI - fixed the calculation to be dynamic based on the selected reporting period.

‍

We're thrilled to unveil the brand-new Team Benchmark dashboard, a significant addition to our analytics suite designed to offer unprecedented insight into your team's development dynamics!

This dashboard's primary objective is to provide a clear, comparative view of individual developer contributions alongside aggregated team-wide statistics. By juxtaposing individual metrics against team benchmarks, it moves beyond isolated data points, offering rich context to better understand performance, workload distribution, and collaborative patterns.

The Team Benchmark dashboard empowers you to identify key trends, pinpoint potential workflow bottlenecks, and foster more productive, data-informed discussions. Dive into detailed breakdowns of Pull Request (PR) cycle times — from coding and idle periods through to review and merge phases — to see where time is truly spent, both for individuals and the team as a whole.

You can also explore metrics around the volume of work, such as Lines of Code (LoC) in PRs (compared against team averages and percentiles), and understand the review load generated and handled within the team.

Ultimately, this powerful tool is designed to help you and your team highlight areas for process optimization, ensure fairer comparisons, and collaboratively enhance overall efficiency and throughput.

Discover now how these comparative insights can drive continuous improvement and a deeper understanding of your software delivery lifecycle.

We're thrilled to announce a major update focused on simplifying your reporting workflows with the introduction of dedicated fields for Sprints and Parent Issues. Say goodbye to cumbersome custom fields and hello to advanced (yet streamlined) insights! 🧘

Jira Sprints: Deeper visibility on SCRUM iterations

With this release, you no longer need to juggle with array-based custom fields to get sprint information. We've mapped Jira sprints directly into our data model, adding six new, dedicated fields. These new fields make past, current, and future sprint reporting drastically easier and pave the way for enhanced sprint-based dashboards 🏃

These fields expose the attributes of the most relevant sprint associated with each issue:

• Past Sprint Names: The list of sprint names the issue has gone through before the currently associated sprint.
• Sprint Closed At: The closure date of the sprint associated with the issue.
• Sprint End At: The end date of the sprint associated with the issue.
• Sprint Name: The name of the sprint associated with the issue.
• Sprint Start At: The start date of the sprint associated with the issue.
• Sprint State: The state (closed, active, future) of the sprint associated with the issue.

Here are some typical scenarios where these new fields will be useful. If you want to see:

• A retrospective view of issues from closed sprints, use the filter "Sprint State = CLOSED"
• Issues in a currently active sprint, use the filter "Sprint State = ACTIVE"
• Issues that are scheduled in a future sprint, use the filter "Sprint State = FUTURE"
• Issues that were previously in sprint XXX but have been carried over to another sprint, use the filter "Past Sprint Names contains XXX"
• A distribution of the number of issues allocated to current and future sprints, use a pie chart with "Sprint State" as dimension.

Parent Issue Attributes: Epic-level reporting

We're also excited to introduce Parent Issue attributes, which allow you to easily filter issues based on their parent issue (e.g., Epics). Jira and GitHub both support parent issues, such as Epics in Jira or parent issues in GitHub. This feature provides valuable context and enables more granular reporting, allowing you to understand how individual issues contribute to larger initiatives.

A typical reporting scenario is to calculate the percentage of progression of Epics based on how many issues are associated with them and how many have been closed so far. With this new release, it is only a matter of grouping issues by parent attributes and using a formula of type COUNT_IF(state = "CLOSED")/COUNT to get a percentage of progression. That's it! 🔥

Other improvements and bug fixes

• Improvement: Support Microsoft Entra (previously known as Active Directory) as a login option
• Improvement: Parent custom fields (Jira custom fields) are now exposed on Activity Events & Comments.
• Improvement: Parent story points are now exposed on Activity Events & Comments.
• Improvement: Parent key is now exposed on Activity Events, Comments and Commits.
• Improvement: Custom Formula: Improved the editing experience of Custom Formulas with better bracket highlighting/matching as well as better field highlighting/selection.
• Improvement: New ARRAY_FILTER operator for Custom Formulas, allowing one to filter a list of values based on a regex.
• Improvement: Support the explicit use of null values in Custom Formulas. NULL values get ignored in aggregation metrics. Being able to explicitly use null values in formulas is useful when you want to do conditional aggregations. E.g., an average of "big PRs" such as AVG(lines_changed > 1000 ? lines_changed : null).
• Improvement: Array arithmetics for Custom Formulas - elements can now be added to an array using the + sign. E.g. label_names + ['bug'] or label_names + 'bug'
• Improvement: Array arithmetics for Custom Formulas - elements can now be removed from an array using the - sign. E.g. label_names - ['bug'] or label_names - 'bug'
• Improvement: Dashboards can now be set as viewable or editable by the whole team (team-wide sharing).
• Improvement: On top of exposing properly mapped sprint attributes, the Jira "sprints" custom field is now also sorted consistently by sprint completion date, with the current/future sprint always last (Jira does not return a specific order on its API).
• Improvement: Field picker dropdowns now support filtering via multiple keywords (instead of filtering based on the whole sentence).
• Improvement: A new insight named "Reopen Rate" has been added to the library. It displays the ratio of issues reopened versus issues created.
• Improvement: Two new insights named "Burndown chart" (based on count or story points) have been added to the library.
• Improvement: A new insight named "Open at date" has been added to the library. It displays the number of open items (Issues and PRs) at any given point in time alongside the cumulative count of created/reopened and closed/merged events."
• Improvement: Performance improvements have been released to the "Issues & Pull Requests" and "Reviews" datasets, boosting reporting speed by up to x100.
• Bugfix: Fixed an issue with some array operators considering null values as empty arrays, creating an offset for some advanced count formulas.
• Bugfix: Fixed an issue where the drilldown was incorrectly working on multi-dimensional charts in some rare scenarios.

Understanding and improving developer productivity just got clearer! Moving beyond simplistic metrics like lines of code, we've embraced the multi-dimensional SPACE framework. Now, you can leverage a dedicated analytics dashboard designed to translate this powerful framework into tangible, actionable insights directly from your development workflows.

This dashboard operationalizes the five key dimensions of SPACE:

• Track Satisfaction & Well-being: Gain objective insights into workload patterns and potential burnout risks by analyzing commit times and task distribution, enabling proactive support for team health.
• Measure True Performance: Focus on outcomes, not just output. Monitor system stability and quality through metrics like Change Failure Rate and Mean Time To Recovery, derived directly from your PRs and incident data.
• Visualize Activity: Get a clear view of team throughput. Track completed PRs, issues closed, story points delivered, and deployment frequency to understand development velocity and focus areas.
• Analyze Communication & Collaboration: Optimize teamwork by dissecting review cycle times (Idle, Review, Merge), identifying high-discussion items, and measuring comment density to pinpoint communication bottlenecks and efficiencies.
• Optimize Efficiency & Flow: See how work moves through your pipeline. Measure end-to-end Lead Times for issues and PRs, track deployment cadence, and analyze active implementation time to identify and remove friction points.

By grounding the SPACE framework in concrete data visualizations and metrics, this dashboard empowers teams and leaders to move beyond theory. It provides the necessary visibility to diagnose specific challenges, track the impact of process improvements, and foster a more productive, sustainable, and data-informed engineering environment.

Get started today with Keypup's SPACE analytics dashboard and transform your Development Productivity.

We're excited to announce the availability of our Bitbucket Data Center integration and a significant performance boost for Activity Event, Commits & Comment datasets. Read on for all the details! 🤓

Bitbucket Data Center Integration

You asked, we delivered! Bitbucket Data Center (DC) is now available as a fully supported application within Keypup.

This means you can now seamlessly track your Bitbucket DC repositories directly within Keypup, gaining the same valuable insights and metrics as you do with our existing Bitbucket Cloud integration. This allows teams using on-premise Bitbucket instances to leverage Keypup's powerful reporting capabilities and track their engineering performance.

The Bitbucket DC integration plays nicely with our Jira DC/Cloud integrations, automatically detecting relationships between Bitbucket Pull Requests and Jira Issues, allowing Tech Leaders to create combined reports!

Details on the Bitbucket DC integration and which data we fetch can be found in our dedicated help center article.

Activity Event, Commits & Comment Datasets: Performance Boost

We've been hard at work optimizing our data processing engine, and we're thrilled to announce a massive performance improvement for our Activity Event, Commits, and Comment datasets.

You can now expect reporting speeds to increase by x10 to x100, depending on the complexity of your query! This speed boost is a result of implementing more efficient querying strategies, allowing you to generate reports and gain insights faster than ever before 🚀

We're not stopping there! We will deploy this performance optimization to the Issues & Pull Requests and Pull Request Reviews datasets over the next few weeks. Stay tuned for even faster reporting across the board.

Other improvements and bug fixes

• Improvement: Configured Bitbucket Cloud to use static IPs, mirroring Jira, GitLab, and GitHub. This enables users to leverage IP whitelists on Bitbucket Cloud and use Keypup securely.
• Improvement: Integrated GitHub issue types from their public preview API, providing early access to this new feature and enhanced reporting capabilities.
• Improvement: Jira custom fields can now be directly selected from the "dimension" dropdown, eliminating the need to switch to a custom formula.
• Improvement: Visually upgraded the team invite flow to align with the regular onboarding flow, providing a consistent and modern user experience.
• Improvement: Added an option to display the value of each slice on pie charts. This option can be toggled alongside the "show percentage" option to display both values simultaneously.
• Improvement: The table in the Report widget now expands to occupy the full available width, automatically expanding the last column if there's space.
• Bugfix: Added logic to filter out system-generated usernames (e.g., User e3r4w2) returned by Bitbucket's API under pressure, preventing incorrect username updates and reporting errors.
• Bugfix: Improved the stability of custom formulas, especially when switching between the "formula modal" and "inline formula" editors.
• Bugfix: Fixed an issue with presets in dashboard-wide filters where a field (mapping) would be automatically reselected on modal open, even if it had been previously cleared.
• Bugfix: Fixed an issue in the insight filter modal where the cursor would constantly be pushed to the end of input fields, improving the editing experience.
• Bugfix: Added a loading indicator to the "Remove User" action in team management to improve feedback and prevent the impression of unresponsiveness.

‍

We're starting 2025 with the release of one of the most requested features: the API 🤓🎉

API in private beta

Our newly released API allows you to use Keypup programmatically. The API is composed of two endpoints:

• The Platform API: This endpoint is the general-purpose API used to manage dashboards, insights, projects, and users. It can be used to retrieve the list of team members, send team invites, edit dashboards, create insight configurations, etc.
• The Reporting API: This endpoint is the actual reporting engine used by insights to query the datasets. You can make listing or "group by" queries, such as counting the number of Pull Requests per month labeled as "bug", for the last 12 months.

The API can be used to incorporate engineering metrics into your existing workflows and systems, such as:

• Creating a Slack bot, to send a standup report every morning
• Configuring alerts, in your favorite monitoring system (Datadog, New Relic, and the like)
• Leveraging engineering metrics in your global DevOps flow, such as increasing the number of required reviewers when quality drops

The API is a self-documented GraphQL API, which you can easily try out using our API Explorer (see screenshot). The API powers our frontend, this means that you can simply look at the network requests while navigating the Keypup interface to get examples of GraphQL queries 💪

The API is currently in private beta. Access is provided on a per-user basis during the beta. Do not hesitate to contact our team via chat to get your access enabled.

If you want to learn more about our API, simply check out our dedicated article on the help center.

Other improvements and bug fixes

A few additional items worth mentioning 🥰

• Improvement: Dashboards added through the standalone "add Dashboard" flow are now automatically pinned
• Improvement: Array operators now consider null values as empty arrays to make the formulas on custom fields consistent across records from different applications
• Improvement: The number of displayed custom fields has been increased from 500 to 1000
• Improvement: The MIN and MAX operators now support string values on top of numbers
• Improvement: The platform's accessibility (WCAG 2.0) has been considerably improved. Work remains but this is a significant step forward.
• Improvement: Stick to integer ticks on the Y axis when values only contain integers. Decimal ticks may only appear if values contain decimals.
• Improvement: The TIMELINE_DURATION operator supports a boolean fourth argument to set the return value as "null if none". This is useful to ignore zeros in averages when issues have skipped the measured step in a flow.
• Bugfix: The selected drilldown data point is now reset when the insight configuration changes, in edition mode.
• Bugfix: Custom field cache (in custom formulas and filter box) is properly reset when apps are connected/disconnected
• Bugfix: Drilldown could not be activated on new "Report" insights (only after save + edit). This has been fixed.
• Performance: Jira issue descriptions are now limited to 10k characters. This limitation will be rolled out to all applications.
• Performance: The memory usage of the user interface has been reduced by around 60%, especially over long usages (memory leaks).

‍

‍

This release brings a new dataset to the Keypup family! The Activity Events dataset allows engineering managers to create activity feeds as well as historical "open at date" insights 📈 As part of this update we also improved the UX around column handling in our insight editor.

New Activity Events dataset in beta

The Activity Events dataset tracks historical events occurring on Issue and Pull requests. This dataset is currently available in beta and we are collecting feedback to further improve the data model.

The following events are currently captured:

• CREATED: the issue/PR was created
• CLOSED: the issue/PR was closed
• REOPENED: the issue/PR was opened was being closed
• MERGED: the PR was merged
• REVIEWER_ASSIGNED: a reviewer was assigned (requested reviewers) to the PR. Keypup generates one event per assigned reviewer in case of bulk assignments.
• REVIEWER_UNASSIGNED: a reviewer was unassigned (requested reviewers) from the PR. Keypup generates one event per unassigned reviewer in case of bulk unassignments.
• USER_ASSIGNED: a user was assigned (assignees) to the issue/PR. Keypup generates one event per assigned user in case of bulk assignments.
• USER_UNASSIGNED: a user was unassigned (assignees) from the issue/PR. Keypup generates one event per unassigned user in case of bulk unassignments.
• WORK_LOGGED: a user logged some time on the issue/PR.
• WORKFLOW_STATUS_UPDATED: the issue transitioned to a new workflow status.

For each event, we also capture useful content fields:

• Parent: The parent issue or pull request is captured through the "Parent > *" fields. This allows you to filter events based on parent attributes such as the issue type, state, or labels.
• Duration: This field is populated on WORK_LOGGED events. It allows users to create time spent reports per week and/or per assignee.
• Target User: This field is populated on assigned/unassigned events and captures who was the person being assigned or unassigned.
• Workflow Status: This field is populated on WORKFLOW_STATUS_ UPDATED events and captures the destination status

The types of Activity Events will vary slightly based on the apps you connect to Keypup. Here is the list of supported events for each application:

• Github: CREATED, CLOSED, REOPENED, MERGED, REVIEWER_ASSIGNED, REVIEWER_UNASSIGNED, USER_ASSIGNED, USER_UNASSIGNED
• GitLab: CREATED, CLOSED, REOPENED, MERGED, REVIEWER_ASSIGNED, REVIEWER_UNASSIGNED, USER_ASSIGNED, USER_UNASSIGNED, WORK_LOGGED
• Bitbucket: CREATED, CLOSED, MERGED, REVIEWER_ASSIGNED, REVIEWER_UNASSIGNED
• Jira: CREATED, CLOSED, REOPENED, USER_ASSIGNED, USER_UNASSIGNED, WORK_LOGGED, WORKFLOW_STATUS_UPDATED
• ClickUp: CREATED, CLOSED. ClickUp does not expose an events API. Keypup generates these two events based on the issue timestamps (date_created & date_closed)
• Trello: CREATED, CLOSED, REOPENED, USER_ASSIGNED, USER_UNASSIGNED, WORKFLOW_STATUS_UPDATED

All the documentation for the Activity Events dataset can be found here.

So what can you do with Activity Events? Here is a list of insights and reports you can build on Keypup:

• An activity feed showing the most recent actions that were taken for all issues and pull requests, or a subset of them
• An open-at-date report, showing the historical running count of open issues, by summing (cumulative sum) the number of open/reopened events minus closed/merged events
• An "in status" at-date report for Jira/Trello, showing the historical running count of issues that were in a specific status (e.g. In Progress) by summing (cumulative sum) the number of transitions minus the number of transitions to the next status.
• A consolidated report of how much time has been spent on issues, per issue type or label
• An assignment report showing how often engineers get assigned to PRs for review

Have other use cases in mind? Need a hand setting up insights using the new Activity Events dataset? Just ping our team on the chat! 🤓

Easier handling of columns in the insight editor

Many of you were frustrated that columns could not be inserted in the middle of a report 🤯 This forced people to add a column at the end and then move it all the way up.

Well, the pain is over! This release includes two UX improvements related to column handling:

• The table columns in the "Configure table" section now properly use the label defined on the column, instead of using the column number. This makes the overall navigation easier, especially on large reports.
• The column menu now allows you to right-insert a dimension or a metric (depending on the type of insight).

It's a small change but it helps considerably when editing reports 😇

Other improvements and bug fixes

A few additional items worth mentioning 🥰

• Improvement: The state (OPEN/CLOSE) of Jira issues is now purely based on the status category of their workflow status ("done" status category or not). We no longer rely on the resolution field since this field is not longer standard in Jira flows (e.g. Jira Product Discovery does not support this field) and its use has become unreliable (e.g. some issues may have a resolution status without being closed status-wise).
• Improvement: Support IS_NULL and IS_NOT_NULL filtering on number fields.
• Bugfix: The edition modal of dashboard-wide filters now displays insights in alphabetical order instead of using the "add date" of each insight.
• Bugfix: Fixed the alphabetical listing of some fields in the datasets
• Bugfix: The search bar in the dashboard share modal now uses case-insensitive search for users
• Bugfix: Gracefully handle the login flow when an old session token is present in the URL (e.g. when bookmarked)

Our latest release brings new functionalities to some of our existing features, allowing users to unlock even more reporting use cases 🚀 Most of these features were requested by Keypup users, we thank you all for helping us build the best engineering analytics tool 🙏💙

Added multi-metric variants for stacked charts

Our 2-dimensions stacked charts already allow users to create reports using two dimensions (e.g. creation date and author) and one metric (e.g. lines changed, count of PRs), where the second dimension is used to generate the stacked slices.

But what if you want to create a chart with one dimension (e.g. creation date) and multiple custom metrics (e.g. sum of lines added and sum of lines deleted)? Well this is now possible thanks to the multi-metric variants! Our standard stacked charts now allow you to specify multiple metrics, which will stack with each other.

Here is the complete list of stacked charts available on Keypup. The multi-metric ones are standard and the (existing) 2-dimensions version have been renamed to be more explicit:

• Stacked Area Charts
• Stacked Area Charts (2-dimensions)
• Stacked Bar Charts
• Stacked Bars Charts (2-dimensions)
• Stacked Column Charts
• Stacked Column Charts (2-dimensions)

Have more use cases for stacked charts? Don't hesitate to contact us via chat!

Improved auto-filling support on date operators

Our auto-filling feature fills the blanks between data points on time series. This is useful to highlight zero-areas or plateaus (cumulative reporting) when data are missing for a given day, week, or month, instead of connecting the dots and giving a false impression of continuity between existing data points. Our auto-filling feature automatically activates when you select a date dimension with a standard formatter such as "Year > Month", "Year > Week" etc.

This week's release extends the auto-filling logic to also apply to custom formulas when using the following operators:

• DAY (1..31)
• DAY_OF_WEEK (1..7)
• DAY_OF_YEAR (1..365)
• HOUR (1..24)
• MONTH (1..12)
• QUARTER (1..4)
• WEEK (1..52)

Note that the auto-filling logic will only activate if the date operator is used as a top-level operator (e.g. MONTH(...)) and not as a calculation element (e.g. CONCAT("Foo", MONTH(...)) ).

On top of this, we also enabled the auto-filling behavior on heatmaps. This allows you to create visual maps to help understand cyclic patterns, such as a contribution map:

‍

Better detection of Jira closure dates

Our integration was previously solely relying on the use of the Resolution field in Jira to detect the closure state and date of issues. This field is usually populated as part of Jira Workflows when issues reach a "Done" status (this is the default in standard Jira Workflows).

Over the last two years we've observed that the usage of the Resolution field has been declining, becoming less and less standard in Jira projects. Jira Product Discovery, the newest product of the Jira family, even dropped support for the Resolution field.

In order to keep delivering consistent reporting on closed Jira issues, we have updated our Jira integration to detect issue closure if any of the following conditions match:

• A Resolution is set on the issue, in which case the resolution date will be used as the closure date
• The issue is in a Status that has a Status Category set to Done, in which case the closure date will be set to the last Status Category Changed Date. This means that if you post-mortem transition an issue from a done status (e.g. Won't do) to another done status (e.g. Released), the closure date will be set to the first closure event (e.g. Won't do).

Other improvements and bug fixes

A few additional items worth mentioning 🥰

• Improvement: Two new custom formula operators, SHA1 and SHA256, were added. These operators can be used to anonymize reports.
• Improvement: Stop retrieving ecosystem.atlassian.net projects when connecting Jira. These projects start appearing after liaising with Atlassian's support. They do not relate to any business-related project.
• Improvement: Jira project-specific custom fields will not be grouped under their respective project ID. The field name used by these fields in custom formulas will also include the Jira project ID. This is done to help differentiate custom fields with identical names from different projects.
• Improvement: Add negative variants for user filters, allowing you to exclude specific users based on their connected identities. The list is: Is not me, Is not user, does not include me, does not include user.
• Improvement: The maximum number of allowed dimensions and metrics on insights has been increased, from 20 to 30 and 10 to 20 respectively. Many insights will restrict this hard limit further based on type (e.g. a heatmap has two dimensions and one metric, no more no less).
• Improvement: Wait for custom formulas to be valid before triggering a reload of the insight. This improves the custom formula editing experience and avoids many unnecessary reloads.
• Bugfix: Fix the sorting of the axis values (or slice names) for the secondary dimension when using charts with two dimensions. The sorting of the could previously appear out of order.
• Bugfix: The array element accessor (e.g. assignees[1] ) was not returning the correct type with date or boolean arrays. This could prevent users from applying type-specific operators on some array elements (e.g. Jira custom field sprint date array).
• Bugfix: The CSV export functionality of insights was not taking into account the auto-filling behavior of insights.

‍

This week's release delivers a new dashboard that leverages the Time in Column feature released some time ago. It also includes a couple of improvements related to time series and our beloved configuration assistant 💪

New dashboard: Issue Cycle Time for Jira & Trello

A few months ago we released a series of fields and operators allowing people to report the time spent by Jira & Trello issues into a given status ("Time in Column" feature). These features unlocked very advanced reporting capabilities via custom formulas. However, we were still missing a fully-featured and preconfigured dashboard using the Time in Column field and operators.

The wait is over! To complete our existing Pull Request Cycle Time dashboard, which focuses on core development, we just released an Issue Cycle Time dashboard that analyzes the time spent by issues in their various delivery stages.

The dashboard groups your Jira statuses into four key phases, to facilitate reporting:

• Pickup Time is the total duration spent in the initial status before the development starts (e.g. “To Do”)
• Implementation Time is the total duration spent in the development status (e.g. “In Progress”)
• Quality Assurance (QA) Time is the time it takes to verify that the implementation matches the business objectives (e.g. "In Testing", "In QA")
• Release Time is the time it takes to move the issue to production (E.g. "Ready to Release", "Pending Release Approval").

Our Configuration Assistant allows you to specify the list of Jira/Trello statuses to include in each phase:

Easy enough! Now you can get a detailed view of how long issues spend in each column of your Scrum or Kanban board 😎

Time series: Quarterly grouping in charts

On top of the yearly, monthly, weekly, and daily groupings, we have added the ability to group time series per quarter.

Need to check how you performed this quarter compared to the previous quarter? Now you can 😁

‍

As part of this new feature, we also added two operators to the library of custom formula functions:

• YEAR_QUARTER(datetime), which formats a timestamp field in YYYY-Qx format (e.g. “2023-Q2”)

• QUARTER(datetime), which returns the quarter number for a given date (or the duration of a quarter in seconds when no arguments are provided)

Configuration Assistant simplified thanks to value pickers

Value pickers were already available for insight filters and dashboard-wide filters. But they were still missing in our Configuration Assistant.

Well, good news everyone, they're now available there as well! Picking statuses, labels, and commit keywords while configuring a dashboard or an insight is now dead easy! Just pick the value that is the most relevant to the question.

Check out the gif above to see an example of a value picker in action ⛏️

New presets available for dashboard-wide filters

On top of the existing Reporting Period and Projects presets, you can now quickly create dashboard-wide filters using the App and the Owners fields.

The Owners field was introduced as part of the previous release. Its objective is to facilitate filtering across issues and pull requests, and help identify who is responsible for a given item:

• For issues: the Owners field is equal to the assignees field
• For pull requests: the Owners field is equal to the author field (list with a single element)

Some improvements and bug fixes

A few additional items worth mentioning 😉

• Improvement: Associations between PRs and Jira issues now support using the issue key in branch names (case insensitive) and commit messages (without an auto-closing keyword)
• Improvement: Expand the catalog of errors supported in a human-friendly way when connecting GitLab/Jira hosted instance
• Improvement: The search bar in the insight library now only filters insights based on their title and tags, and no longer uses their description. The use of the description for filtering was returning too many results due to the popularity of certain keywords.
• Bugfix: The due date for issues attached to sprints now uses the last sprint due date instead of the last active sprint due date. The latter was leading to due dates disappearing once a sprint was completed.
• Bugfix: The CONCAT operator now supports decimal arguments (was returning an error before)
• Bugfix: the unit helpers such as YEAR, MONTH, WEEK, etc. now return a proper integer instead of a stringified integer. This could cause issues when trying to apply a math operation on the return value of these operators.
• Bugfix: Fixed an issue where a Jira user changing name then being rolled back would not be reflected on the Keypup side

This week's release highlight is a long-awaited feature: the ability to automatically fill missing data points as zeros on time series. This round of updates also brings some new fields to help filter on resolving PRs and resolved issues and some quality-of-life improvements on our login system.

Auto-filling on Time Series

Your time series charts may look slightly different since you last viewed them. That's because we now fill the blanks with zeros on time series, instead of "just" connecting the dots between values with underlying data. This produces sharper charts and better highlights periods of inactivity.

Let's take the example of a count of pull requests per month and assume the following data:

• July: 17 PRs
• August: 0 PRs
• September: 12 PRs

Previously, our time series would have connected July to September (2 existing data points), leaving an impression that there was some in-between count for August.

With the auto-filling feature, this time series will now display three data points, with the middle one being set to zero, therefore highlighting the lack of activity for August.

The auto-filling feature only fills the blanks between existing data points, not around them. So if you set your insight filters to retrieve data from the last 6 months but only have actual data for the last 4 months, the auto-filling feature will only fill in the blanks within those last 4 months.

If you still want to connect the dots between existing data points only, you can disable this auto-filling feature by editing your insights and going to the Customize Style tab:

New Fields on Datasets

The following new fields have been released to help you make your filtering even more powerful (click the fields to access their documentation).

Comments

• Parent > Metatags
• Parent > Sub-Type

Commits

• Parent PR > Metatags

Issues & Pull Requests

• Owners
• Past Assignees
• Past Workflow Statuses
• Resolved Issues > Metatags
• Resolved Issues > Sub-Types

Reviews

• Parent PR > Metatags

Email Matching when Logging In with New Identities

When logging in to Keypup with a new identity (e.g. Google), we will now attempt to match this identity with an existing user by looking up identities with verified emails (e.g. GitHub) instead of creating a new Keypup account.

We were previously only matching identities that had been explicitly linked to your account upon logging. This new approach is a bit more flexible, especially when you do not remember which service you used to log in to Keypup.

‍

This week we are bringing you some quality-of-life improvements, specifically focusing on insight building and dashboard-wide filtering.

Improved Insight Builder UI

You will notice that the UI received some tweaks here and there:

• The Select Visualization section on the sidebar has been removed to streamline the edit flow. Switching visualization is now done via the top left dropdown.
• This Switch Visualization Dropdown has received a lifting and now allows you to switch between regular charts and KPIs. This last one was long overdue but were busy on big bang features (see our previous announcement on Historical Events and Time in Column)
• In the Select Dataset section, fields are now grouped by topic and can be clicked to access their respective documentation (this will open the doc in-app, you can open it in a new tab via ctrl/cmd + click). Many of you have requested more direct access to field documentation to easily explore our extensive dataset, so here it is! Enjoy 🤗
• On the Configure Table section, we have reworked the headers to be more streamlined and provide easier access to custom formulas, which is one of the most powerful features of Keypup, allowing you to build fit-for-purpose metrics via custom calculations.
• Still on the Configure Table section, we've made the size of the Add Dimension/Metric button (+) more visible. Also, adding a dimension/metric now highlights it. This is particularly useful when handling reports with lots of columns. Enjoy adding more dimensions and metrics to insights!

Dashboard-wide Filter Presets

A couple of weeks ago we released Quick Presets for insight filters. Such a great idea that many of you asked us why it was not available for the dashboard-wide filters. Simply because we were cooking it! 🍳

We've added two presets to the dashboard-wide filters:

• Reporting Period: This preset allows you to quickly filter your entire dashboard on a given period. The preset selects the most relevant time field for each insight, based on their filter configuration. Yes, it's magical 🪄
• Projects: This preset allows you to refine your dashboard based on a list of projects or repositories. Not rocket science but very useful.

This is only the beginning! More presets will be added over time. One preset will come to light soon (next few weeks) allowing you to quickly filter an entire dashboard on item ownership (author for PRs and assignees for issues). This is a standard dashboard-wide filter for some of our dashboard templates and we're making it standard.

This week we are giving you the tools to better Cycle Time on your development flow. Not only are we releasing a new version of the Cycle Time dashboard but we also greatly improved the way we track events on issues and pull requests. The result is more accurate ways to measure the time spent in each stage of development to detect bottlenecks early or simply to measure yourself against elite performers such as Netflix or Amazon.

New Cycle Time Dashboard

We are delighted to unveil our reworked Cycle Time Dashboard! It is packed with new and enhanced insights to provide teams with the best calculation for each stage of your development process.

Discover the 4 stages of your development process (with the new Idle Time insight) to locate and resolve your bottlenecks and improve delivery.

Historical Events support for GitLab and Trello

The assigned_at, last_assigned_at, review_requested_at, and review_last_requested_at events fields are now based on the changelog of issues and PRs and populated retrospectively (they used to be observed and only valid from the moment projects were connected to Keypup).

These fields are now available for full historical reporting on GitLab and Trello. (GitHub, Jira, and Bitbucket were already supporting historical events since the Keypup 2.2 release).

That enables use cases such as:

• Calculating the time between an issue was assigned to someone and the beginning of development (by transitioning to a specific status, or when the resolving PR was opened)
• Calculating the time between a PR review was requested and it was submitted.

Time in Column available for Trello

With the support of historical events for Trello, we've added the capability to measure the time spent in columns on Trello! This update follows the 2.2 update which included Time in Column for Jira.

The Time in Column feature allows you to:

• Measure time spent in each workflow status: Tailor your analytics to reflect your team's unique workflow, whether it's tracking time spent in review, development, QA, or any custom stage.
• Gain efficiency insight: Understand where time is being invested, identify bottlenecks, and streamline your processes for maximum efficiency.
• Enhance project management: With detailed insights into every stage of the development cycle, manage your projects more effectively and make informed decisions that drive success.

Improved support of merge request reviews for GitLab

Our best API gymnasts have worked on our GitLab integration to improve the detection of creation timestamps for peer reviews and add support for "changes requested" reviews.

This means our GitLab integration is now on par with GitHub and Bitbucket and allows you to track cycle time more accurately and perform historical reporting on reviews.

Contact us via chat if you would like to learn about more use cases, or if you would like to request help from a product expert.

We're excited to introduce Keypup 2.2, our latest version designed to supercharge your software development and project management processes. This update includes groundbreaking features and enhancements that cater specifically to the needs of product managers and CPOs, ensuring unmatched visibility, efficiency, and strategic depth in your software development lifecycle.

Keypup 2.2 New Features

Jira Time spent in Column

Unlock the power to measure time spent in each phase of your project lifecycle with unprecedented precision. Whether your team refers to stages as "In-Development," "In-Progress" or "In-QA," Keypup adapts to your terminology. This unique feature allows you to:

• Measure time spent in each workflow status: Tailor your analytics to reflect your team's unique workflow, whether it's tracking time spent in review, development, QA, or any custom stage.
• Gain insight into efficiency: Understand where time is being invested, identify bottlenecks, and streamline your processes for maximum efficiency.
• Enhance project management: With detailed insights into every stage of the development cycle, manage your projects more effectively and make informed decisions that drive success.

Historical Events for Github, Jira Cloud and Jira Data Center

The assigned_at, last_assigned_at, review_requested_at, and review_last_requested_at events fields are now based on the changelog of issues and PRs and populated retrospectively (they used to be observed and only valid from the moment projects were connected to Keypup).

These fields are now available for full historical reporting on GitHub, Jira Cloud and Jira Data Center:

• Overview: Allows you to perform historical reporting on assignment dates. Need to know if you have improved your PR Review Pickup Time or Issue Pickup Time over the years? This is now possible!
• Benefits: Gain a deeper understanding of project flow and timelines, enabling better forecasting and resource allocation for future projects.

Quick preset rules for intuitive metrics configuration

Get suggested filter presets to start configuring any metric with pre-configured conditions. The smart quick filters automatically adapt to the dataset you have chosen, by proposing dedicated and relevant presets. This useful feature allows you to rapidly configure metrics to match your exact needs, without having to create cumbersome filters on your own.

Activity Recap Dashboard

The Activity Recap Dashboard is a comprehensive tool providing an extensive overview of your project's lifecycle through 20 key insights, including Opened Pull Requests, Commits Made, PR Authors, and much more. Each metric is meticulously integrated to offer unparalleled project oversight.

The Activity Recap Dashboard will allow you to empower your team with data-driven decision-making capabilities, enhance collaboration and quality, ensure agility and responsiveness, and gain complete visibility across the development lifecycle.

Enhancements

Jira Data Center Integration

We've expanded our integration capabilities to include Jira Data Center, alongside our existing support for GitHub, GitLab Cloud and Hosted, Bitbucket, Trello, ClickUp, and Jira Cloud. This integration is currently in beta and aims to provide a seamless connection for comprehensive analytics and reporting capabilities.

Download Your Charts & Reports Data

Responding to user feedback, we've introduced the ability to download charts and reports data as CSV files. This enhancement allows for further data analysis and sharing, ensuring that you have full control and flexibility over your reporting needs.

Looking Ahead

As we continue to evolve Keypup, we're excited to announce that we will soon incorporate the build dataset as well as the historical events for other solutions. These updates will provide deeper insights into the post-development analytics (deployment phase), further enhancing our platform's capabilities and aligning with the needs of product managers and CPOs.

Keypup 2.2 is not just an update; it's a leap forward in empowering software development teams and their leaders to achieve their goals with precision and confidence. Embrace the future of project management with Keypup 2.2.

We're excited to announce a significant update that broadens the scope of Keypup's connectivity and integration capabilities. In our continued effort to provide comprehensive analytics and collaboration tools for software development teams, we've now added support for Jira Data Center. This new feature is currently in Beta and extends our existing integrations with GitHub, GitLab (Cloud and Hosted), Bitbucket, Trello, ClickUp, and Jira Cloud.

Expand Your Connectivity

Alongside our robust list of integrations, users can now connect Jira Data Center to Keypup, offering enhanced flexibility for teams operating in a Jira Data Center environment.

Beta Release Highlights

• Comprehensive integration: Seamlessly integrate your Jira Data Center with Keypup to unlock advanced analytics and reporting capabilities across multiple Jira sites.
• Streamlined setup: An easy-to-follow OAuth configuration process enables a secure connection between your Jira Data Center and Keypup, empowering you with enriched data analysis and project oversight.

How to Connect

• Whitelist IP addresses: (Optional) For Jira servers behind firewalls, whitelist Keypup's IP addresses for uninterrupted API communication.
• Application link creation: Configure an incoming link in your Jira server's Applications panel to establish the OAuth flow between Keypup and Jira Data Center.
• Seamless connection: Use the generated Client ID and Client secret to complete the connection on Keypup, ensuring your projects are ready for import with full analytics capabilities.

Enhanced Project Management

With unified analytics get a holistic view of your development activities, leveraging insights from your code collaboration tools integrated with Jira.

Security and Compliance

• Secure OAuth flow: Ensure a protected connection between Keypup and your Jira Data Center with OAuth, maintaining the integrity and security of your data.
• SSL certificate validation: Keypup supports publicly recognized SSL certificates for secure API calls, recommending against the use of self-signed certificates for optimal security and compliance.

We are thrilled to offer this new integration to our users, reinforcing our commitment to providing a versatile and powerful platform for software development analytics and project management. This update opens new avenues for teams to streamline their reporting processes, enhance project visibility, and foster a more data-driven engineering culture.

Explore this latest feature and elevate your Jira reporting capabilities with Keypup's advanced analytics today!

We're thrilled to announce a highly anticipated feature that our users have been waiting for – the ability to download your charts & reports data directly from Keypup. This new functionality enhances your ability to interact, analyze and share your data outside of our platform, giving you more flexibility and control over your reporting and data visualization efforts.

📊 Feature Highlights

• CSV export: You can now export the data behind any chart or report  with charts into a CSV file, allowing for further analysis or reporting in your preferred tools.
• Comprehensive data access: This feature supports the export of up to 1000 records, ensuring you have access to extensive data for in-depth analysis.
• Seamless usage: The download functionality has been integrated directly into the dashboards. To download your data, simply click the "…" menu on any insight and select the export option.
• Universal availability: This feature is enabled for all charts and reports  across the platform, offering a consistent and user-friendly experience for all your data export needs. This feature is also available for all plans, including the 14 days free trial.

🚀 How to Use This Feature

1. Navigate to your dashboard: Open the dashboard where your desired chart or KPI is located.
2. Access the menu: Click on the "…" menu icon on the top right corner of the chart or KPI insight you wish to export.
3. Select export option: Choose the 'Export data' option from the menu to initiate the download of your data.

💡 Make the Most of Your Data

This new feature opens up numerous possibilities for data analysis and reporting. Whether you're looking to perform a custom analysis, integrate data into other reports, or simply keep a record offline, the ability to download your charts data ensures that your insights are always at your fingertips, ready for whenever you need them.

We understand the importance of being able to work with your data on your terms, and with this update, we're excited to offer you even more flexibility in how you access and analyze your insights.

Explore this new feature today and take your data analysis to the next level!

The Dataset Exploration Dashboard

• Discover data transparency: Dive into our new Dataset Exploration Dashboard for a comprehensive overview of your software engineering data, directly sourced from connected Git repositories and project management projects.
• Key features: Explore datasets like Issues, Pull Requests, Commits from Pull Requests, Reviews, and Comments for in-depth analysis.

The Developer Summary Dashboard

• Boost engineering productivity: Monitor crucial software developer metrics and improve productivity with our Developer Summary Dashboard.
• Metrics included: Commit Frequency, Deployment Frequency, Average PR Size, Coding Time, and more for a detailed engineering overview.

2023 Engineering Retrospective Dashboard

• Empower development with insights: Gain a bird's-eye view of your team's performance over the year, making it an essential tool for CTOs and tech leaders.
• Comprehensive analysis: Includes PR Pulse, Commit Chronicle, Issue Tracking, and more.

🛠️ Feature Enhancements

• Enabled KPI charts: Now display 2-12 records, providing greater flexibility.
• New operators: Including TO_FLOAT, TO_INT, TO_STR, and IF_MATCH for more robust data handling.
• Custom fields: Use custom fields in queries, significantly enhancing reporting capabilities.

Navigating the labyrinth of data fields has never been easier. With our groundbreaking dynamic Pickers feature, we're handing the power directly to you, our users. Complex filtering, which used to take minutes, will now be accomplished in seconds.

🔍 Key Highlights: Streamlined Filtering Across Multiple Datasets

Dive deeper and harness the full potential of your data with absolute ease. With the new dynamic Pickers feature, effortlessly select values from a comprehensive list across a range of datasets, directly retrieved from your own data:

• Issues & PRs Dataset:

AUTHOR, ASSIGNEES, BASE REF BRANCH, BASE REF REPOSITORY, HEAD REF BRANCH, HEAD REF REPOSITORY, LABELS, MERGED BY, PAST REVIEWERS, REQUESTED REVIEWERS, RECOMMENDED ACTORS, SUB TYPE, SUGGESTED MERGERS, WORKFLOW STATUS.

• Commits from PR Dataset:

AUTHOR, PROJECT, PR > AUTHOR, PR > BASE REF BRANCH, PR > BASE REF REPOSITORY, PR > HEAD REF BRANCH, PR > HEAD REF REPOSITORY, PR > LABELS

• Comments from Issues/PR/Reviews Dataset:

AUTHOR, PROJECT, PARENT > AUTHOR, PARENT > BASE REF BRANCH, PARENT > BASE REF REPOSITORY, PARENT > HEAD REF BRANCH, PARENT > HEAD REF REPOSITORY, PARENT > LABELS, REVIEW > AUTHOR.

• Reviews from PRs Dataset:

AUTHOR, PROJECT, PR > AUTHOR, PR > BASE REF BRANCH, PR > BASE REF REPOSITORY, PR > HEAD REF BRANCH, PR > HEAD REF REPOSITORY, PR > LABELS

Efficiency at Its Peak

No more manual entry or guessing values. With Pickers for Filters, every value you might need is immediately available.

Complex Filtering Simplified

Welcome a new era where intricate data input is a thing of the past. With pick-list values at your disposal, data navigation becomes a breeze.

Elevate Your Data Filtering Experience

With the new Pickers for Filters, we're setting a new standard in data interaction and analysis. Immerse yourself in your datasets with renewed confidence and efficiency. We eagerly await the incredible insights you'll derive using this feature!

Visualization Enhancements

📈 Cycle-Time Chart

Visualize your entire development lifecycle from ideation to production.

Easily identify potential bottlenecks and areas for optimization.

🚀 KPI with Cycle-Time

Monitor key performance indicators tied directly to your cycle-time.

Make informed decisions backed by concrete data metrics.

⚙️ Gauge Chart

Gauge your development velocity and productivity in an intuitive, visual format.

📏 Log Scale Customization

Enhanced customization options for charts with the addition of log scales.

Available for lines & area charts, column & bar charts, and the gauge chart.

Google SSO

Introducing a frictionless way to get started with Keypup:

🔗 Sign-Up with Google

Quick and easy onboarding via your Google account.

Existing users can now link their Google account for an even smoother experience.

🎬 Seamless Dashboard Onboarding

Each dashboard now comes with a handy video guide defining each insight and its goal.

Locate this guide in the right panel of the Configuration Assistant for a seamless user experience.

Query Engine Upgrades

Our backend has received significant updates to provide users with more capabilities:

✨ Enhanced Filter Operators & New Operators & Aggregators

• "Contains any of" filter operator has been improved for both user and userlist fields, enhancing dashboard filtering experience.
• FLATTEN: Useful for breaking down array fields.
• LOG & LN: Enhanced mathematical functions for refined data analytics.
• EXP: Execute complex calculations with Euler’s number.
• LENGTH: Extended to support string parameters.
• RIGHT/LEFT: Extract specific portions from a string effortlessly.
• PERCENTILE & PERCENTILE_CONT: Derive both discrete and continuous values for any given percentile in a numeric field.

Boost Your Software Development Analytics with Keypup's Latest Features!

Explore the new capabilities, streamline your processes, and achieve unparalleled efficiency with your team.

Get ready to sync with the heartbeat of your development workflow! With the all-new Cycle Time Dashboard, you're not just monitoring; you're understanding every beat that drives your software engineering team forward.

Here are the newly released Insights 🚀

🔍 Coding Time Metric

• Gauge the pace of your development's core.
• Track both active coding periods and waiting intervals pre-reviews.
• Pinpoint early-stage bottlenecks for faster code delivery.

💬 Review Time Metric

• Delve deep into the duration of your full review cycle.
• Ensure robust collaboration and feedback processes for enhanced code quality.

🔧 Merge Time Metric

• Observe how long it takes to merge finalized work into production.
• Streamline transitions from task completion to code deployment.

🌍 Cycle Time Overview

• A panoramic snapshot of your development pipeline's health.
• Spot critical areas needing refinement and bolster your strategy.

📊 Cycle Time Breakdown

• Get granular by dissecting specific pull requests.
• Identify and rectify anomalies to maintain a consistently agile flow.

Bonus: Like all other Keypup metrics and dashboards, you can customize all templates to meet your organization definitions and processes.

The Cycle Time Dashboard is your roadmap to pinpoint and optimize  every step of your development journey. Dive in today and bring  your team's efficiency to new heights.

🌟 We’ve rolled out some exciting updates, designed to elevate your experience and provide deeper, more meaningful insights! Here’s a rundown of what’s new, complete with examples to get your creative gears turning!

🌈 Enhanced Visualization: Set Visual Thresholds on Your Charts

• Details: Whether it’s an Area, Line, Column chart, or a KPI with a sparkline, visual thresholds are now at your command.
• Example Use: If you're visualizing bug counts over time with a Line Chart, set a visual threshold to spotlight weeks where bug counts surpass the limit you've set, offering immediate insights into periods needing extra attention.

🔄 Extended Issues & PRs Dataset: First & Last Comment At

• Details: Dive deeper into your review dynamics with our new first_comment_at and last_comment_at data points! Especially useful for GitLab users, these timestamps offer insights into the initiation and conclusion of reviews, compensating for GitLab’s lack of a “review” concept.
• Example Use: Using GitLab? Detect when a review started on a merge request using first_comment_at. Use these new data points to detect the length of the review phase, in a broader way / discern the longevity and pace of dialogues on distinct threads, identifying bottlenecks or protracted deliberations impacting project timelines.

🕵️ Extended Reviews from PRs Dataset: Submitted At

• Details: For those utilizing GitHub, the exact submission times of reviews are now available, providing another layer to your analytical overview.
• Example Use: GitHub users can now refine review workflows by detecting the duration of reviews (submitted_at - created_at). This may be used to evaluate the average time spent in reviews as well as evaluate the depth of reviews by comparing the review time to the amount of code changed.

🤝 Bulk Invites: Invite Several Users at Once

• Details: Assembling your squad is more straightforward than ever! Invite your entire team in one go and hit the ground running from day one.
• Example Use: Initiating a new project with multiple department members? The bulk invite feature streamlines this process, cutting down administrative effort and ensuring immediate access for everyone.

We are thrilled to announce the release of Keypup 2.1! This version brings a range of powerful new features designed to facilitate your data-driven engineering journey. From simplified reporting and enhanced data visualization to smarter drilldown and collaborative capabilities, Keypup 2.1 empowers you to optimize your software development processes and make informed decisions in no time. Let's explore the exciting enhancements in this release.

Dashboard-wide filtering

• Combine multiple identical insight filters into a single dashboard filter
• Simplify and streamline engineering reporting efforts
• Gain a holistic view of your data at the dashboard level
• Save time, reduce complexity, and minimize errors in reporting

See our blog article about dashboard-wide filtering.

Data Hygiene Dashboard

• Gain insights into keyword, label usage, team’s proficiency, and more
• Spot trends and identify areas for improvement
• Facilitate more accurate reporting
• Optimize reporting practices and enhance data hygiene

See our dedicated page on the Data Hygiene dashboard for more details.

Enhanced data visualization

• Introduce new chart types: line charts, stacked area charts, stacked column charts, and stacked bar charts
• Present data in visually compelling and informative ways
• Track project progress, analyze performance metrics, and monitor engineering KPIs
• Make data-driven decisions confidently with enhanced clarity and insights

Smarter drilldown

• Enhanced data exploration with intelligent drilldown feature
• Recommended relevant fields based on dataset and insight configurations
• Simplified data navigation and saved time
• Uncover valuable insights efficiently for informed decision-making

Introducing the Guest role

• Invite guests to your team and share specific dashboards
• Guests have read-only access for data security
• Enable seamless collaboration with external stakeholders
• Promote transparency and effective communication

Expanded dataset for granular reporting

• Support additional fields for more detailed reporting
• Leverage story points, workflow status (board swimlane), issue type, time spent, time estimate, and parent issue
• Gain deeper insights into software development processes
• Drive informed decision-making with enhanced data granularity

Keypup 2.1 is an exciting release that simplifies your data-driven engineering journey. With dashboard-wide filtering, a Data Hygiene Dashboard, enhanced data visualization, smarter drilldown, the Guest role, and expanded dataset capabilities, you can streamline reporting, optimize collaboration, and gain valuable insights.

We are thrilled to announce the release of 10 new timestamps, making SDLC process analytics extremely precise. These timestamps will allow users to calculate more granularly how much time is spent in each step of the development process, from ideation to production. The new timestamps include:

• First commit at - this field provides the datetime at which the first commit was made on a PR. It is populated based on the creation timestamp of the first commit in the PR or issue.
• Last commit at - this field provides the datetime at which the last commit was made on a PR. It is populated based on the creation timestamp of the last commit in the PR or issue.
• Review requested at - this field tracks the datetime at which the PR review was first requested. It is showcased by observing the datetime at which the requested reviewer's array attribute was first modified. (Note: this timestamp doesn’t apply on data collected prior to connecting to Keypup)
• Review last requested at - this field tracks the datetime at which a PR review was last requested. It is showcased by observing the datetime at which the requested reviewers array attribute was last modified. (Note: this timestamp doesn’t apply on data collected prior to connecting to Keypup)
• First review submitted at - this field provides the datetime at which the first review was submitted on a PR. It is populated based on the submission timestamp of the first PR review.
• Last review submitted at - this field provides the datetime at which the last review was submitted on a PR. It is populated based on the submission timestamp of the last PR review.
• Review rejected at - this field provides the datetime at which a PR was first rejected after a review. It is populated based on the submission timestamp of the first PR review with “request changes” status.
• Review last rejected at - this field provides the datetime at which a PR review was last rejected after a review. It is populated based on the submission timestamp of the last PR review with “request changes” status.
• Review approved at - this field provides the datetime at which a PR first met its minimum approval quota from approving reviews. It is populated based on the submission timestamp of the review that allows the PR to meet its minimum number of approving reviews while no “request changes” review is still active.
• Review last approved at - this field is calculated using the same logic as the “Review approved at” field. The populated date will be different from it only if the PR is rejected and approved again.

These new timestamps will allow users to gain a deeper understanding of the development process by identifying areas where progress is slow or inefficient and where improvement can be made.

Keypup's new timestamps will provide software development teams with the data they need to improve their workflows and increase productivity.

Try out these new timestamps today and accelerate your delivery!

Optimize and streamline engineering value stream like never before! We are thrilled to announce the release of our latest feature – the Value Stream Management Dashboard.

This new dashboard allows you to identify inefficiencies and reduce waste, while increasing efficiency across your software development teams and key projects. It includes valuable insights into the engineering value stream, such as Project Effort Distribution, Value Stream Workload Categorization, Planned vs. Unplanned Work Ratio, Value Stream Engineering Proficiency, Engineering Workload Distribution, and Engineering Work Pattern Analysis. These metrics enable teams to make data-driven decisions and optimize their workflows based on their unique goals and processes.

Keypup's Value Stream Management Dashboard enables teams to better balance workloads across critical projects, identify skill gaps, and enable a culture of continuous learning among the team, making it an essential tool for any software development team looking to optimize their value stream. Use it today and accelerate your engineering time to value!

We are thrilled to announce the release of our latest feature that takes software development analytics to the next level. Our platform now offers not only popular engineering metrics and customizability, but a way to drill directly into metrics to discover root causes. With the click of a button, users can access detailed reports that provide valuable insights into their organization's performance.

Our new drill-down feature allows users to dive into the details of any metric. Users can get a report out of the box that provides information such as projects, teams, users, or branches, giving them a comprehensive view of their organization's performance. Moreover, users can customize the drill-down feature entirely to highlight what they care about most, based on their unique organizational structure.

This groundbreaking feature goes beyond what other software development analytics platforms offer. By providing not just the "what" but also the "why " our platform empowers users to identify bottlenecks and take targeted actions to improve their organization's performance and scale efficiencies.

Try out our new feature today and see the difference it can make for your organization!

Get ready to take control of your software development lifecycle (SDLC) compliance process like never before! We are thrilled to announce the release of our latest dashboard feature - the Audit and Compliance Dashboard.

With this release, you can now assess the overall compliance of your team's SDLC with industry standards such as SOC2, ISO27001 or ITIL  in real-time. Simply connect your Git(s) and get started today!

But that's not all, the audit and compliance dashboard is designed to help you address some of the most pressing questions when it comes to auditing your SDLC process. You can now easily track whether all pull requests (PRs) are verified with a green build and peer-reviewed before merging and which PRs and/or projects fail to comply.

The dashboard provides you with insightful metrics such as the Green Build Ratio, the PR Compliance Feed, the PRs Review Ratio and the Project Compliance Score, all of which help you leverage and adapt software audit metrics.

Say goodbye to manual compliance tracking and hello to effortless SDLC auditing with Keypup's Audit and Compliance Dashboard. Use it today and take control of your SDLC compliance process like a pro!

Get ready to revolutionize the way you build engineering metrics with Keypup's platform! With the brand-new Configuration Assistant feature, customizing your dashboards and metrics has never been easier. Say goodbye to the manual setup, and say hello to user-friendly questions that get you up and running in seconds!

Additionally, the Duplicate Dashboards and Metrics feature has just been released to production. Say goodbye to the hassle of manual formulas and filters copy-pasting. You can now copy any metric or dashboard with ease, and work with it to keep the original template configuration.

So what are you waiting for? Upgrade your Keypup experience today and enjoy seamless, hassle-free real-time engineering KPIs and metrics configuration!

Do you have some ideas of features, enhancements or templates we should include? Ping us via the in-app chat or email us at contact@keypup.io.

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We’ve made some enhancements to Keypup’s development intelligence platform to allow you and your team to better collaborate on shared dashboards and insights. These enhancements include:

Keypup’s Sharing Capabilities

You can now share your dashboards with your team members in Keypup. This sharing capability comes with the dashboard user permission roles “Editor” and  “Viewer”. Editors will be able to collaborate on dashboards with you and apply changes, while viewers will be able to access dashboards in a “read-only” mode.

Keypup’s Collections

You can now browse through all your dashboard and insight templates from the Collections menu located at the bottom of the left navigation panel. From the “Collections” menu, you’ll be able to access your pinned dashboards (those directly accessible from the left navigation panel), the dashboards you’ve created, the dashboards shared with you and Keypup’s template library. Each dashboard can easily be pinned/unpinned, edited, shared, or deleted using the top left appropriate icon. You can also access, browse and delete any insight from your insights collection tab.

Do you have some ideas for features, enhancements, or templates? Ping us via the in-app chat or email us at contact@keypup.io.

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Using contextual information, Keypup's Recommended action field provides a suggested course of action for each open issue and pull request. It helps software engineering managers locate open pull requests and issues throughout the SDLC process and provides logical suggestions to help merge faster. Here is a pre-built template to help you leverage Keypup’s smart fields:

Recommended actions

This template provides a count of pull requests and issues organized by recommended action in the past 12 months. You can modify the dates or add filters to calculate it among specific projects and/or teams. Follow this link to try this template.

Below is the link to the full article on How to  Streamline SDLC with Keypup Recommended Action Field.

Do you have some ideas for dashboard or insight templates to create? Ping us via the in-app chat or email us at contact@keypup.io.

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We’ve made some enhancements to Keypup’s DORA metrics dashboard by introducing Change Failure Rate (CFR) insight templates.

CFR provides the percentage of deployment causing a failure in production. Elite performers have a CFR below 15%. There are several ways to calculate it. Here are the two templates launched to help you get started:

Commit Based Change Failure Rate

This template provides the ratio of fixed commits over all commits associated with merged pull requests in the past 12 months. You can modify the dates or add filters to calculate it among specific projects and/or teams. Follow this link to try this template.

Pull Requests Based Change Failure Rate

This template provides the ratio of bug-labeled pull requests over all merged pull requests in the past 12 months. You can also modify the dates or add filters to calculate it among specific projects and/or teams. As naming conventions vary from team to team, you can adapt the query to match your own. For example, you can edit the insight and replace “bug” with “defect”. Follow this link to try this template.

Do you have some ideas for dashboard or insight templates to create? Ping us via the in-app chat or email us at contact@keypup.io.

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We’ve made some enhancements to Keypup’s Development Intelligence solution to facilitate your journey with us and improve your experience.

These enhancements include:‍

Keypup’s new product documentation is now live!

The new product documentation has been integrated through elev.io. It is accessible through this link or directly from the app using the “Help” button. Users can search for the information they need or click on the red hotspot to get contextual information on-the-go.

Users have access to 150+ articles of all lengths, providing them with all the information they need to quickly become advanced users.

Release of the Textbox widget

In addition to the reports, charts, KPIs, cards and boards, users now have the ability to add Textbox widgets to their dashboards. This new widget type allows users to seamlessly communicate on dashboards to drive themselves or other users through their data story and provide perspective. They can use Textbox widgets to add content, context, to-do lists or engineering OKRs for examples. The data stories are limitless with this new addition.

Filters enhancements

The new time operators are now in production. They provide a range of “human-friendly” operators to filter on dates such as “last two months” or “within current month” or “next month” on top of regular after/before operators for specific dates.

Have some ideas of cool features or datasets to capture? Ping us via the in-app chat or email us at contact@keypup.io.

We’ve made some enhancements to Keypup’s Development Intelligence solution to facilitate your journey with us and improve your experience.

These enhancements include:

Insight Widget Designer’s enhancements

The “Configure source” step has been renamed “Select dataset” and moved to the top of the insight builder. The content of the pane was also reworked to make it more transparent that the purpose of this step is to select a dataset, not to configure fields or take any other action. The dataset fields are hidden by default - they can be displayed by clicking a link.

We no longer expand the formula input when focused to avoid distraction.

It is now possible to switch from a “large card” widget to a “board” widget and vice versa. A toaster notifies you about the actions that were taken, such as removing all columns when switching from board to “large card”.

To improve filtering, we removed duplicate custom fields for JIRA and GitHub. We also better organized custom fields inside the dropdown, with one section per app.

Displayed data increased

When working with tables, charts and KPIs, we increased the number of displayed data points from 100 to 500. This means that when grouping per week, you can now see up to 500 weeks of history (~ 9 years). When grouping per day you can now see up to 500 days (~ 1.5 years).

Dashboard Interface

We renamed the “Add Content” button to “Add insight”. The labels and icons of the shortcut dropdown have been reworked to be more self-descriptive.

Design improvements

Design > Loaders: All loading indicators are now consistent and use the same design.

Design > Empty insights: The legend is now hidden when an insight has no data and the placeholder content is displayed.

Have some ideas of cool features or datasets to capture? Ping us via the in-app chat or email us at contact@keypup.io.

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We’ve made some enhancements to the Keypup solution to help you make the most of our development intelligence platform.

These enhancements include:

The implementation of a Widget Template Library

You can now click on the “Add content” button (previously “Add Chart”) to display a modal with a list of blank and prebuilt templates including Delivery, Development Quality, DORA, Planning & Distribution. This approach will facilitate insight widget access and creation.

A Design update for filters

A UI overhaul has been launched to simplify the design of filters. As part of this update we added the ability to re-order rules (AND / OR).

Board card widget

You can now open the Pull Requests or Issues from the source app (GitHub, JIRA etc…) in a new tab instead of opening the detailed preview modal by doing a ctrl+click or cmd+click on a card.

Have some ideas of cool features or datasets to capture? Ping us via the in-app chat or email us at contact@keypup.io.

We’ve made some enhancements to the Keypup solution to help you make the most of our development intelligence platform.

These enhancements include:

The release of additional datasets including

1. Commits from Pull Requests
2. Reviews from Pull Requests

These two datasets include pre-made JOINs to be able to associate Commits and Reviews information with their Pull Requests.

The enhancement of Comments dataset

The initial “Comments” dataset has been enhanced with a pre-made JOIN to associate Comments to Pull Requests, Issues and Pull Requests review.

The improvement of custom formula capabilities

The formula engine capabilities have been enhanced with 30+ operators & functions (e.g. COUNT_IF, MIN/MAX, GREATEST/LEAST, ARRAY_FIND, NOW…).

The ability to sign-up from a template

Start your data-driven engineering journey with a template from the Keypup library for a more personalized experience.

The launch of a toast notification system

Toasts have been implemented to notify users of punctual or persistent events that occur on their Keypup workspace to inform and improve the experience.

The enrichment of filtering capabilities

It is now possible to filter comments, commits, pull requests and reviews using the pull request source or destination branch/repository. Filtering on the destination branch (e.g. branch = master) is particularly useful to differentiate pull requests coming from developers (features, bugs) vs maintenance pull requests (e.g. release pull requests).

Have some ideas of cool features or datasets to capture? Ping us via the in-app chat or email us at contact@keypup.io.

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Keypup 2.0 allows you to track the areas of your development activities that are most important to you and your stakeholders, you can utilize the Keypup 2.0 platform to build bespoke reports, insights, and dashboards. It includes fully customizable templates to help you make the most of the development intelligence solution. Keypup 2.0 can be used for a variety of tasks, including:

• Get DORA Metrics, Sprint Overviews, Quality Insights, and more proven templates to help you improve your complete development outcomes.
• track and optimize your own operations with pre-built dashboards and insights.
• Adapt the templates to your specific goals and internal processes.
• Create your own dashboards, reports, and insights.

Look through our template library to pick the most appropriate one for your company.

The Activity Funnel is designed to show you the daily changes in your development pipe, exhibit the activity level of each stage and and highlight items that deserve attention.

• Based on your Team Board: changing the columns of your board will update the funnel view.
• Shows the activity of each stage: you can quickly identify PRs and issues losing momentum or becoming stale.
• Ability to drill down: click on each stage to see the relevant items and act on the ones deserving some love.

The Activity Funnel is still in beta. Have some ideas of cool features? Ping us via chat.

The integration with GitHub has been extended to enable the following:

• Pull request and issue associations to GitHub Projects are now imported by Keypup (Project Cards)
• A GitHub custom field called “Project Cards” has been added to query filters
• You can use this field to restrict your reports, board columns and prioritization rules to GitHub Project items.
• This is particularly useful if you need to merge multiple GitHub Project boards in one Team Board on Keypup and ignore the rest (= ignore all untriaged issues not associated with a GitHub Project)

This update enables the following:

• It is now possible to change the priority of a single item from your board or inbox
• This is useful to temporary raise the priority of items that need a kick
• This can also be used to reorder items on the team board, based on relative priorities
• The feature above comes on top of custom prioritization rules and Keypup’s natural ability to infer priorities as an 'override'.

The integrations to GitHub and GitLab have been updated to support the following:

• Number of required approvals now fetched from GitHub and GitLab for pull request reviews. If no required approvals are setup, Keypup still enforces a minimum of one.
• New recommended action “Assign missing reviewers”. If one of your pull requests is in review but missing reviewers to reach the minimum number of required approvals, you’ll know about it 😉
• Added “required approvals” and “required approvals remaining” to query filters. If you need to create reports, board columns or prioritization rules based on approval statuses, these new fields are the way to go!

With Keypup Retrospectives, developers are finally able to provide feedback remotely, at their own pace, without interrupting their work.

• Retrospectives are easy to prepare, easy to run. You can schedule retrospectives at regular intervals, that you set to match your development cycles. Set the start date, the frequency of occurrence and the feedback window.
• When it's retro time, each developer will automatically receive an email or chat notification asking them to fill their retrospective and our platform will follow up automatically until completion.
• When a retrospective closes, an email is sent to the whole team with the results. You can access to the full report in Keypup. The report is shareable within the team and saved for easy exploitation. Each aspect of the project is analyzed factually to improve future deliveries.

We built this new feature for all the remote teams that struggle to prepare retrospectives and collect usable data. This feature will save teams hours of meetings and allow retro to actually be actionable, as every team member has a say and provides contextual feedback.

The retrospective feature is currently in beta. Want to provide feedback or ask for improvements? Don't hesitate to contact us.

We recently brought various performance improvements to the platform to deliver faster data synchronization and data display. We also implemented a series of general improvements and bug fixes across the platform.

• Speed up third-party data ingestion and data enrichment processing time
• As part of this performance work, we also brought many improvements to Cloudtasker, our open source library for GCP Cloud Tasks . These improvements will soon be released as part of v0.12.0.
• Improve JIRA and Trello data fetching strategies, with better support for throttling and pagination.
• Improve UI loading strategy, using on-demand content loading. See our writeup on this approach on our blog.
• Improve default inbox prioritization rules, especially for items recently worked on

There are some cases where a company has multiple JIRA sites, either for different clients or different projects.

This new feature is for any agency, company or freelancer working on multiple client JIRA sites. We've made some enhancements for you to track projects across multiple JIRA instances. You can keep adding as many JIRA sites as you need then select which projects you wish to import on the projects page.

No matter the naming conventions and workflow specificities in your JIRA sites, you can harmonize your overall workflow statuses in Keypup.

Consolidate all JIRA instances on Keypup to have one nice organized view. You will now be able to remotely comment on issues belonging to the JIRA sites you connected.

Multiple JIRA instances + one Keypup account = One Global Workflow instead of multiple JIRA workflows completely separated from each others.

This release provides better visibility of which issues are ready to be closed.

When an issue remains open after its related pull requests have been merged, we now move the issue back to the priority inbox of its assignees with the action close.

This new behaviour allows you to take action on the issue, that is either re-assign it to people which must still do work on it (e.g. end to end testing) or simply close it. No dangling issue due to someone forgetting to close it!

Along with this new feature we now display issues which are currently being implemented by pull requests in the Coming Up tab with the action Wait for PR. This allows you to see at a glance which issues are currently being worked on, but without spamming your actual inbox. As with pull requests, you can see the unified feed of discussions on these issues.

The Data Explorer already allows you to query any development items from your projects without API and create reports.

We updated the Data Explorer with shareable reports.

Share your reports with your team or individual members.

What's great about this feature is the ability to share your reports directly with your teammates, so that you track the same things at the same time - and you can work in sync with your team and collaborate faster.

In the Query editor, just select the visibility of your report before you save it. You can also pin this report for all team members' priority inboxes and choose the order of appearance in their priority tab.

The team board is a visual way to follow the progress of issues and pull requests across all your usual tools, individually or as a team. Unlike Trello or JIRA, there is no need to move cards - the board is automatically updated based on the status of items.

Each column in the board is configured to retrieve issues and pull requests matching specific criteria. By default columns are configured in the following way:

• Todo: Any open issue with at least one assignee
• In development: Any open pull request which is not currently in review or for which changes have been requested
• In review: Any open pull request for which a review has been requested or any pull request which has been approved but currently having build issues or conflicting with the base branch.
• Mergeable: Any open pull request which has been approved, has a green build and does not conflict with the base branch.
• Done: Any issue or pull request which has been closed or merged within the last 3 days.

Columns can be fully customized to match your own development steps and workflows. So you do not need to stick with the default ones.

By default the Team board shows you the progress of items across all team members. You can filter the board for a specific Team Member by using the View as filter.

The Team Board can easily be customized to better fit your development workflows. If you are using Scrum, Kanban or a mix of both, the Agile board can accomodate all tracking methodologies at the same time. All projects, no matter which methodology, in the one consolidated board.

This is not just another Agile board. It is not complicated. It is not for the project manager. It is a simple, yet powerful agile board designed specifically for developers by developers.

Watch the demo video

The auto-linking feature allows issues to be related to pull requests and have Keypup group these items automatically in your Priority Inbox for a better visibility.

You don't need to do anything extra as it integrates natively with existing auto-linking features of GitHub or GitLab or Bitbucket.

The auto-linking feature automatically creates a unified conversation feed across all items. This makes it way easier to ensure that you haven't missed any update on a related item. Note that you can still access each individual item-related discussion separately as well.

The auto-linking works with any number of issues and you get a nice summary by clicking on the inbox item.

Our Bitbucket integration allows you to import pull requests into Keypup and better track development activities across all projects in one place - especially if you connect JIRA as well.

Get instant clarity on your pull request statuses. Finally a clear tracking view individually and across the board.

Pull Requests and JIRA issues nicely aggregated and prioritized

Tag JIRA or Trello issues in your pull request commits or title and Keypup will automatically aggregate those. Pull requests will automatically be prioritized based on due dates of attached issues.

All your pull requests in one view

Struggling to follow pull requests across all your Bitbucket projects? Keypup centralizes them all in the Review & Merge board to give you an easy way to follow what's going on.

Developer board or JIRA board? Both!

Using JIRA or Trello to track your Bitbucket development? Is that JIRA board not developer-centric enough? Get your own automated development board with Keypup.

Create your own reports

Need a better overview of Bitbucket activity? Create your own report on current or past pull requests to get a better understanding of development activities.

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Keypup now provides auto-discovery of JIRA custom fields because we know that most developers will customize their Jira to suit their needs.

Upon connecting your JIRA instance, Keypup automatically fetches and makes available filtering all JIRA fields with supported data types - this way, your own custom Jira is now ready in Keypup.

JIRA custom fields can be complex and we do our best to provide filtering that makes sense. Base JIRA fields are often composed of arrays, nested objects etc.. The Data Explorer automatically generates field and sub-field filters for these more complex fields as well.

Our ClickUp integration allows you to import project management data into Keypup and easily link issues to pull requests to get better visibility on what is getting resolved and when pull requests are due, among others.

What is the ClickUp integration for?

Link ClickUp cards to pull requests

Keypup now allows you to link ClickUp cards to pull request, giving you the best of both worlds: project management data synced with  repository data !
Simply use the URL of a ClickUp card in your pull request title or description.

Quick replies on cards

Quickly reply on cards from the Priority inbox, either directly on the card or via the activity feed when a card is nested under a pull request. Call that a time saver! (plus again, keeping data/comments consistent across all other apps).

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The data explorer allows you to easily query pull request and issue data and save these queries as reports. Reports can also be pinned as tabs on your Priority Inbox for easy access.

No API calls. All queries and reports in the one place. Yep - that simple. And really performing - the reports you will get can be customized at will and have many conditions. Oh, and they're dynamic, so once created, you can just follow up on them to see your progress.

You can find all your JIRA custom fields to perform queries. They will be automatically added to the standard fields.

Reports are shareable - so not only can you share them directly with your PM, but also with any of your teammates, so that you track the same things at the same time - and you can collaborate faster.

Major improvements have been made on the auto-linking feature along with our December 2020 feature release, the Team Board.

Pull request and issues linking is quite an essential concept in Keypup because it allows for two things:

• Pull requests and related issues are automatically grouped in your Priority Inbox or the Team Board. This considerably reduces the number of items to deal with on a daily basis and makes for a clean, easy and direct reading of everything a Pull Request addresses (including all nested issues). More convenient than having to conduct speleological searches in your repo, no?
• Pull request due dates are automatically inferred based on the due dates of related issues. This means Keypup can properly prioritize pull requests to the right person when moved to review or merge status.

There are multiple ways to link issues to pull requests.

You can link issues and pull requests from the Priority Inbox (checkout our docs below)

Or you can link issues using closing keywords directly from GitHub and GitLab via:

• Pull request title
• Pull request description
• Commit message

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Our GitHub integration allows you to import pull requests and issues to better track development activities across all projects in one place.
Get instant clarity on your pull request statuses.

Pull requests & issues prioritized and automatically aggregated

Development items are automatically prioritized based on due dates and recommended actions in your Priority inbox.
Track your items easily by linking your issues and pull requests. You can make comments that will be disseminated in GitHub.

Merge pull requests in one click

Keypup evaluates the readiness of a pull request and give you recommend actions. When Pull Requests are mergeable, have a green build and have been approved, Keypup will send a notification to project maintainers.
Pull Requests can then be merged directly from in just a click from the Review and Merge board.

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Keypup now allows you to connect hosted GitLab instances, giving you the best of both worlds: the Gitlab hosted instance you are used to and like combined with the full power of the Keypup engine to help you be more efficient and gain visibility and agility.

In order to complete the connection process you'll need to create an OAuth application in GitLab. Nothing too complicated as you know

It's a great feature because you can enhance your workflow and gain precious time with these remote actions from the dashboard:

• Link merge requests and issues: merge requests and issues can be linked to each other directly from the Priority inbox using the 🔗 icon. In order to link items we update the description of the parent merge request and add a "closes: https://issue-url.domain" auto-linking keyword at the bottom of it.

• Merge pull requests: approved merge requests with a green build on the Keypup platform - if any - and a mergeable status can be merged directly from the Keypup Review & Merge board.

• Quick reply on items: it is possible to comment on a merge request or an issue from the Priority inbox. For issues replies can be done either directly on the issue or via the issue activity feed when an issue is nested under a merge request.

Our JIRA integration allows you to import project management data into Keypup and easily link issues to pull requests to get better visibility on what is getting resolved and when pull requests are due. Our integration also includes JIRA's custom fields, for maximum tracking efficiency.

Turn JIRA into a simple, effective development tracking tool.

Keypup now allows you to link JIRA issues to pull request, giving you the best of both worlds: project management data synced with repository data !
Simply use the URL or a key of a JIRA issue in your pull request title or description
Quickly reply on issues from the Priority inbox, either directly on the issue or via the issue activity feed when an issue is nested under a pull request.

"Hello, my name is Keybot. I am pleased to meet you. You are a developer and I am your new best friend - I will help you daily by simply communicating with you by email or on Slack to help you navigate your priorities."

Keybot is your new development assistant. Get any insights on all your development and issue trackers tools.

What does Keybot do?

You can find Keybot in your email inbox or on Slack. He helps sort out all your Pull Requests, merge reviews and more.

• ⏰ Daily digests with your top priorities
• ✅ Green PR Merge recommendations
• 🔍 Provides answers on your development queries - for instance the state of pull requests

Because Monday needs an extra push, Keybot sends a complete summary of your development project progress, a short digest of your most urgent priorities, and the reason why I know it's urgent - either because of the due date of an item, or because of its criticality.

Remote actions give you the ability to action items directly from Keypup. So that in one click you can trigger actions in all your connected tools at once.

Merge pull requests in GitHub or GitLab as well as comment on items in apps directly (GitHub, GitLab, JIRA or Clickup), all of that from the one place at once.

Quick reply on items

This quick reply feature is compatible with PRs which are auto-linked to issues. Commenting on the unified feed will comment on the PR itself, while commenting on an item-specific feed will create a comment in the remote system this issue belongs to (e.g. JIRA).

Merge pull requests straight from the Review & Merge Board

The Review & Merge Board, provides the capacity of merging your pull requests in one click. Items flagged as "Merge" in your review & merge board can now be merged directly from Keypup! No need to navigate to GitHub or GitLab to do so!

Our Slack integration sets Keybot up - your soon-to-be best friend, and more pragmatically Keypup's communication bot -  into your workspace to communicate with you when important events occur.

It is also possible to ask questions to Keybot to quickly get an overview of the status of pull requests, issues and development tasks. For example asking "Which PRs are ready to be merged" will prompt Keybot to return the list of pull requests which are mergeable, have a green build, and have been approved.

Morning digest

Keypup users on Slack receive a morning digest every day at 9:05 am with the top priorities of their Priority inbox. And because we know Mondays need an extra push, Keybot will start the week with a comprehensive digest of your activities from last week and your outstanding priorities for this week. Handy, right?

Merge recommendations

When pull requests are mergeable, have a green build, and have been approved, Keybot will send a notification to project maintainers and propose to merge them. One click, and merged they are!

Asking questions to Keybot

You can ask questions to Keybot to get an update on pull requests and issues.

Here are a few examples of questions you may ask:

• How many PRs can be merged?
• Which PRs can be merged?
• How many issues are open?
• How many PRs have been merged last week?
• Which PRs are ready to be reviewed?
• ...and more!

The purpose of the priority inbox on Keypup is to gather items that you - as a developer - must action rapidly. The priority inbox leverages data from all apps you connected in order to evaluate the priority of items and the actions to take for each of them.

The priority inbox currently provides two actions.

Link pull requests to issues

Issues can be related to pull requests using keywords in titles, descriptions, and commits. Keypup will automatically combine items and activity feeds.

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Comment on pull requests or issues

A Quick reply field is also available for on items and related items (related items appear when a pull request is grouped with related issues).

Watch the feature video

Our Trello integration allows you to import project management data directly into Keypup and easily link cards to pull requests to get better visibility on what is getting resolved and when pull requests are due.

Link Trello cards to pull requests

Keypup now allows you to link Trello cards to pull requests, giving you the best of both worlds: project management data synced with repository data!
Simply use the URL of a Trello card in your pull request title or description.

Quick replies on cards

Quickly reply on cards from the Priority inbox, either directly on the card or via the activity feed when a card is nested under a pull request. Call that a time saver! (plus again, keeping data/comments consistent across all other apps).

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