--- title: "AI for Sentry — Query Sentry Data in Plain English" description: "Ask Sentry what broke – not how to write the query." canonical: "https://www.aifordatabase.com/integrations/sentry/" --- # AI for Sentry. ![Sentry](https://www.aifordatabase.com/brand-logos/sentry.svg) Sentry · Analytics Platform Ask Sentry what broke – not how to write the query. [Connect Sentry](https://app.aifordatabase.com/signup)[Connection options](https://www.aifordatabase.com/integrations/sentry/#connection) Read-only · Flexible connection options Read-only query ``` > Which unresolved production issues affected the most users in the last 7 days? ``` ✓ Read-only · APISetup time varies by connection Turn Sentry's issues, events, projects, and releases into direct answers. Ask which errors regressed after a deploy, what's burning the most users, or where the team keeps paying the same reliability tax. AI for Database queries the Sentry API in read-only mode and returns the evidence – without making you wrestle with filters, exports, or another dashboard. Sentry stays the system of record. AI for Database gives you a faster way to interrogate it. ## What data you can query ### Issues Grouped errors with titles, severity, occurrence counts, and user impact `id``title``status``level``count``user_count``first_seen``last_seen``priority` ### Events Individual error occurrences with stack traces, breadcrumbs, and user context `event_id``message``culprit``timestamp``platform``environment``release` ### Projects All projects in your org with platform, status, and metadata `slug``name``status``platform``date_created``first_event_date` ### Releases Deployment history with version, commits, and associated projects `version``date_created``date_released``project_count``commit_count` ## Problems this solves ### The issue list is not a priority list Sentry can show hundreds of active issues. It can't decide which ten deserve engineering time before the next planning meeting. ### Release regressions hide inside familiar noise A deploy lands, event volume climbs, and the new failure gets mixed in with errors everyone has already learned to ignore. ### Simple questions turn into filter archaeology Comparing projects, releases, environments, and time windows should take seconds. Too often it means reconstructing the right search syntax and clicking through multiple views. ### Reliability context gets lost between incidents The team fixes the obvious fire, but recurring exceptions, noisy services, and long-running regressions quietly become part of the production baseline. ## How AI for Database helps ### Triage by impact, not inbox order Rank unresolved issues by event volume, affected users, recency, project, or release so the team starts with failures that matter. \> Which unresolved production issues affected the most users in the last 7 days? ### Interrogate every release Compare error activity before and after a release and surface issues that first appeared after deployment. \> What new or reappearing issues showed up after the latest release of the API project? ### Cross-project questions in plain English Query multiple Sentry projects without rebuilding the same filters or exporting data into a spreadsheet. \> Which three projects produced the most error events this month, and what were the top issues in each? ### Turn incident review into evidence Pull the issue and event history needed for postmortems, weekly reliability reviews, and leadership updates. \> Show me the top 5 issues by user count that are still open, with their first and last seen timestamps ### Expose recurring engineering debt Find old unresolved issues, repeated regressions, and projects that generate a disproportionate share of production errors. \> Which issues have increased by more than 50% in event volume since the previous release? ## Example queries \> Which unresolved production issues affected the most users in the last 7 days? Filters open issues by environment, sorts by user\_count descending, compares with previous 7-day window \> What new issues showed up after the latest release of the API project? Compares issue first\_seen timestamps against the latest release date for the API project \> Which issues have increased by more than 50% in event volume since the previous release? Aggregates event counts per issue before and after the previous release, calculates percentage change \> Show me unresolved issues older than 30 days that still generated events this week Filters issues by status=open and first\_seen > 30 days ago, checks for recent event activity, ranks by affected users \> Which three projects produced the most error events this month? Aggregates event counts per project for the current month, orders descending, returns top 3 with contributing issues ## Dashboard templates ### Release Regression Watch Track new and reappearing issues around every deploy * New issues by release (bar) * Event-volume change from previous release (table) * Affected users per release (line) * Projects with sharpest post-deploy increase (highlight) ### Reliability Debt Board Surface what's been ignored too long * Top unresolved issues by age and impact (table) * Recurring issues across releases (list) * Error volume by project (bar) * High-frequency failures still unassigned (KPI) ## Automated workflows ### Morning production triage Unresolved issues that grew fastest in the last 24 hours, ranked by user impact Weekdays at 8:30 AM ### Post-deploy check Newly introduced or reappearing issues after the latest release, with event and user impact After every deploy ### Weekly engineering review Which projects produced the most errors, which issues repeated, and what remained unresolved Weekly on Friday at 4 PM ### Incident follow-up When an issue started, how volume changed, which releases overlapped, and whether similar failures appeared elsewhere On-demand after incidents ## Key metrics Unresolved issue countError events over timeUsers affected by issueNew issues by releaseRegressed or reappearing issuesEvent-volume change after deploymentMean and median issue ageError volume by projectRepeat issues across releasesHighest-impact unresolved issues ## Connection options ### Direct API Connect via Sentry's REST API with a read-only auth token. No warehouse, no ETL, no infrastructure – just your API token and org slug. Pros * \+ Setup in under 2 minutes * \+ Real-time data * \+ No additional infrastructure * \+ Read-only – zero risk to your Sentry account Cons * \- Rate limited (~1000 requests/min – more than enough for queries) * \- No historical backfill beyond Sentry's own retention Setup 01 Create an API token — In Sentry, go to Settings → Auth Tokens → Create New Token. Select 'Project: Read' and 'Org: Read' scopes 02 Grab your org slug — Open your Sentry dashboard. The slug is in the URL: sentry.io/{org-slug}/ 03 Connect in AI for Database — Add a new connection, select Sentry, paste your token and org slug ## How to get your Sentry API token 01 Log in to sentry.io and navigate to Settings → Auth Tokens 02 Click 'Create New Token' and name it (e.g., 'AI for Database') 03 Under scopes, check 'Project: Read' and 'Org: Read' – that's all you need 04 Click 'Create Token' and copy it immediately (it starts with 'snr\_') 05 Grab your org slug from your Sentry URL (the part after sentry.io/) **Tip:** This token is read-only. It can't create, modify, or delete anything in your Sentry account. [View official Sentry documentation →](https://docs.sentry.io/api/auth/) ## FAQ ### Does this replace Sentry? No. Sentry stays the system of record for error and event data. AI for Database gives you a faster, conversational way to query that data and combine results across issues, projects, releases, and time windows. ### Can it change issue status, assign owners, or modify alerts? No. The integration is read-only. It queries data through the Sentry REST API and does not resolve issues, change project settings, or edit alert rules. ### What Sentry data can I ask about? Issues, events, projects, and releases. Available detail depends on the API permissions and data in your Sentry account. ### Will it tell me the root cause of an error? It can surface patterns and evidence – when an issue appeared, which release preceded it, how event volume changed. It doesn't inspect your code or guarantee a root-cause diagnosis. [← All integrations](https://www.aifordatabase.com/integrations/) ## Your Sentry speaks English now. [Start free](https://app.aifordatabase.com/signup)[View pricing](https://www.aifordatabase.com/pricing/) Free plan available · No credit card required Source: https://www.aifordatabase.com/integrations/sentry/