Log Monitoring Software Resources

Sentry supports all three of those layers with official, first-party SDKs. No separate tools or vendors needed. Web frontend: SDKs for JavaScript, React, Angular, Vue, Svelte, and more. You get error monitoring, performance tracing, and session replays, among many other things. Backend services: First-party SDKs for Python, Node.js, Java, Go, Ruby, .NET, PHP (including Laravel), and others. Each includes error monitoring, performance tracing, and profiling. Mobile: SDKs for native iOS (Swift/Obj-C), native Android (Kotlin/Java), React Native, Flutter, and Kotlin Multiplatform. Mobile SDKs also include session replay. The part that matters for a mixed stack: Sentry's distributed tracing connects requests across all of these services automatically. A trace that starts in your mobile app or browser flows through your backend services, so you see the full picture in one place. With current SDK versions, this works without any custom wiring. It also supports desktop apps and gaming engines. You don't need separate setups for each part of your stack. On the organization side, you'd create a Sentry project per service or platform (one for your React frontend, one for your Python API, one for your iOS app). They all live under one org with shared dashboards that span across projects. One place for everything. Full list of supported platforms: https://docs.sentry.io/platforms/

Sentry covers the core APM use cases: distributed tracing across services, transaction-level performance monitoring with P50/P75/P95/P99 breakdowns, and alerts when things regress. If you're already using it for errors, the biggest win is that errors and slow transactions share the same trace, so you're not jumping between tools to figure out what happened. It also tracks slow database queries and surfaces N+1 issues automatically, monitors web vitals like LCP, CLS, and INP tied back to specific code, and does continuous profiling so you can see function-level performance data, not just spans. Sentry focuses on the application layer, so everything it surfaces is directly tied to your code. For most teams already using Sentry for errors, turning on performance is a straightforward call. You get meaningful APM coverage without adding another vendor, and the shared context between errors and traces is genuinely useful.

Seer is Sentry's AI debugging agent, not a chatbot. It uses the data Sentry already collects (stack traces, logs, traces, profiles) to figure out why something broke, identify the root cause in your code, and suggest a fix or open a pull request. You control how far it goes: just root cause analysis, a solution plan, or a full PR. It also reviews your pull requests in GitHub before you merge, flagging potential bugs based on your error patterns. Seer works across all the languages and frameworks Sentry supports, and you can configure how much autonomy it gets per project. Check out Seer's full capabilities here: https://docs.sentry.io/product/ai-in-sentry/seer/