Sentry

Sentry helps developers monitor errors, crashes, and performance issues in real time with rich context to fix problems faster. Sentry can provide Error Monitoring, Structured Logs, Tracing, Session Replay, AI debugging, and much more.

Where Sentry ranks

Current edition · updated Oct 20, 2026

About Sentry

Sentry helps developers monitor errors, crashes, and performance issues in real time with rich context to fix problems faster. Sentry can provide Error Monitoring, Structured Logs, Tracing, Session Replay, AI debugging, and much more.

Industries served

Products

What customers say

  • Error Monitoring

    Duolingo adopted Sentry for error monitoring across more than 200 microservices, using querying, dashboards, tags, and ownership rules to investigate issues and reduce alert noise. Sentry reports migration in two weeks…

    Case study
  • Sentry

    Atlassian migrated from a deprecated self-hosted Sentry instance to Sentry SaaS to reduce infrastructure maintenance. Sentry reports that the move saved the Observability team the equivalent of up to two engineers' time…

    Case study
  • Error Monitoring

    Factory uses Sentry to monitor errors across eight frontend and backend projects and supply production context to its autonomous Droids. Sentry reports that an incident-response agent used an error payload to remediate a…

    Case study

Security and compliance

As reported by Sentry. Ask for audit reports before you buy.

Subprocessors21st, Abstra, Affogato, Agency Cyber Inc., Alloy, Amboras, Inc., Anara, Assembly, AutoNotes, Avery, AWeber Systems, Inc., Blaxel, Bond, Boundo, Capy, Char, Ciro, Clarm, Clay, Combinely, Conveo, Cosine, Cotool, Inc., Crusoe, Deepnote, Denki, Descript, Diffusion Studio, DiligenceSquared, Double, the AI Coding Copilot, Duckie, Dynamo AI, Edexia, Educato, EmailJS, Extend, Fastmail, Fiddler AI, Frigade, Grain, Greenboard, Hadrius, Harbor OpCo, Inc., Heron Data, Hyperproof, Inc., Hyperspell, Imperfect, Inkeep, Keet, Kinter, Kite Video, Inc., Langdock, Lapis Labs Inc., LegalOS Inc., LemonLime, Level AI, Lightspeed Commerce Inc., LILT, Lucent, Lucis, Machined, MadeThis, Magnetic, Manaflow, Metorial, MindFi, Motives, MyArchitectAI, Octolane AI, Outlit, Palmier, Inc., PatternFast, Plivo, ProhostAI, Protex AI, Quotain, quso.ai, Rainforest QA, Reclaim.ai, Reducto, Replit, Rovi Health, Inc., Seals AI, Sila, Solidroad, Solve Intelligence, Spott, Stratify, TesterArmy, Tinfoil, Tracecat, Tusk, TypeAI Inc., Userbrain, Veryfi, Vespper, Vybe, World Labs, XBOW, Brief, High Agency, Inc., Meeting.ai, MORAI Inc., Tarteel, CoreDMC, Skema, 3LC, ESAI, Factory AI, Acrux Education, Tsenta, Eve Legal, Secureframe, boxes.dev, OpenHack, Inc., Sona8, Graphide, Inc., Mirrors, Voyager, Sentient OS, ClickUp, The Prompting Company, Inc., Volaren, Telamont

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Latest updates from Sentry

New featurePartnership

Seer Root Cause Analysis Adds Support for GitLab

Sentry's Root Cause Analysis (Seer) tool now supports GitLab. Users can leverage GitLab code files for analysis and have Seer automatically open Merge Requests containing proposed fixes.

IntegrationGitLab
New feature

Launch of Personalized Issue Sorting

Sentry introduced a 'Recommended' default sorting option for its issue stream. This feature utilizes personalization to surface issues that specifically require immediate developer attention.

New feature

Redesigned Conversations Detail View

Sentry has redesigned the Conversations detail page for its AI features. The update allows users to track every message, tool call, and model response within a conversation, providing better visibility into the interaction flow.

New feature

Dart and Flutter SDK Adds gRPC Integration

The Dart and Flutter SDK now features a new sentry_grpc package. This integration enables tracing, breadcrumbs, and distributed tracing headers for outgoing gRPC calls, as well as the ability to capture failed calls as errors.

New feature

Beta Launch of Low-Value Span Detection

Sentry released a beta feature to automatically detect high-volume, low-signal spans. This update aims to reduce noise in performance data, lower span storage costs, and improve the utility of distributed traces.