Sentry connector
Set up the Sentry connector in Kaivo: authentication, configuration, the 5 BigQuery tables it syncs, and answers to common questions.
Written By Lauri Raivio
Last updated 15 days ago
Kaivo is a fully managed data platform that syncs your Sentry data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your data from Sentry instead of moving it.
What is the Sentry connector
Sync your Sentry issues, events, and releases into BigQuery with Kaivo to analyse application errors alongside the rest of your data.
Getting started with the Sentry connector
- Sign up for Kaivo and create a workspace.
- Connect your Sentry account.
- Choose which tables to sync.
- Wait for the initial sync to finish.
- Query your data in BigQuery or your favourite AI or BI tool.
Authenticating Sentry
Authenticate with your User Auth Token.
Configuring the Sentry connector
When you set up the connector, you provide:
Tables and columns synced from Sentry
Kaivo syncs 5 tables from Sentry into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
events (46 columns)
events (46 columns)
Subtable: events__tags
Subtable: events__errors
Subtable: events__context__results
Subtable: events__context__empty_list
Subtable: events__entries
Subtable: events__fingerprints
issues (30 columns)
issues (30 columns)
Subtable: issues__stats___24h
Subtable: issues__stats___24h__list
Subtable: issues__annotations
project_detail (98 columns)
project_detail (98 columns)
Subtable: project_detail__teams
Subtable: project_detail__access
Subtable: project_detail__plugins
Subtable: project_detail__plugins__assets
Subtable: project_detail__plugins__contexts
Subtable: project_detail__plugins__features
Subtable: project_detail__plugins__resource_links
Subtable: project_detail__plugins__feature_descriptions
Subtable: project_detail__features
Subtable: project_detail__platforms
Subtable: project_detail__safe_fields
Subtable: project_detail__organization__features
Subtable: project_detail__latest_release__authors
Subtable: project_detail__latest_release__projects
Subtable: project_detail__allowed_domains
Subtable: project_detail__sensitive_fields
Subtable: project_detail__builtin_symbol_sources
Subtable: project_detail__dynamic_sampling_biases
projects (42 columns)
projects (42 columns)
Subtable: projects__access
Subtable: projects__features
Subtable: projects__organization__features
releases (27 columns)
releases (27 columns)
Subtable: releases__authors
Subtable: releases__projects
Subtable: releases__projects__platforms
How the Sentry sync works
After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Sentry supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.
Frequently asked questions
How long does the initial sync take for Sentry?
It depends on how much history is in your Sentry account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.
Can I sync only some tables or columns?
Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.
What happens when Sentry's schema changes?
New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in Sentry, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.
How do I handle GDPR or data deletion requests?
Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in Sentry instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the Sentry connector in Kaivo and all of its synced data is deleted with it.
Common use cases for Sentry data
Error trends
Track issues and events over time to monitor error volume and spot regressions.
Release quality
Analyse issues by release to see whether each deploy improved or worsened stability.
Project health
Break errors down by project to find the noisiest areas of your app.
Errors and product together
Join Sentry data with product usage in BigQuery to see which errors affect real users.
Use Sentry data in your AI and BI tools
Once Sentry data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with Sentry data.
Claude
Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →
Power BI
Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →
Data Studio
Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →
Tableau
The premium analytics standard, with native BigQuery integration. Setup guide →
Google Sheets
Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →
Excel
Connect via Power Query's BigQuery connector. Setup guide →
Metabase
Open-source BI tool with strong BigQuery support. Setup guide →
See our pricing page for Sentry connector pricing and plan details.
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