Skill UI

A comprehensive guide to configuring Sentry error tracking and performance monitoring across modern application architectures. Learn how to implement coherent, end-to-end distributed tracing for monoliths, microservices, serverless functions (Lambda/Cloud Functions), event-driven systems, SPAs, and mobile applications, ensuring all application hops are monitored from a single source.

Automates Sentry monitoring workflows through Composio’s Rube MCP by orchestrating issue investigation, project issue management, alert rule configuration, release tracking, and organizational monitoring.

This guide provides comprehensive steps to diagnose and fix the most frequent Sentry SDK integration issues. It covers critical topics such as DSN validation, missing event capture, source map failures, rate limiting, and proper flushing patterns in Node.js, Python, and serverless environments. Use this when your error monitoring system is not working as expected.

Integrate Sentry into your CI/CD pipeline to achieve end-to-end release tracking. This skill guides you through using the Sentry CLI and SDK to record deployments, associate commits, upload source maps, and monitor crucial release health metrics. Key functions include detecting regressions, calculating crash-free session rates, and tracking user adoption curves for every deployed version.

This skill provides a comprehensive walkthrough for setting up and testing Sentry error monitoring using both Node.js and Python SDKs. It demonstrates how to capture various event types, including simple messages and full exceptions, and crucially, how to enrich these events with user context, searchable tags, and detailed breadcrumbs. This is essential for verifying robust error logging and monitoring in a production environment.

This guide identifies and provides remedies for common anti-patterns when configuring and using the Sentry SDK in production environments. It covers critical pitfalls like hardcoded DSNs, incorrect sample rate settings, and failure to flush events, ensuring data integrity, preventing cost overruns, and maintaining comprehensive monitoring coverage across various platforms.

This advanced guide provides strategies for scaling Sentry in high-traffic, enterprise-level applications handling millions of events daily. It details implementing adaptive sampling based on endpoint criticality, using adaptive error deduplication to manage quotas, and optimizing the SDK for minimal runtime overhead, ensuring robust visibility even under extreme load.

This comprehensive guide provides a phased strategy for migrating error tracking services from legacy tools like Rollbar, Bugsnag, or New Relic to Sentry. It covers crucial steps including concept mapping between diverse providers, implementing safe parallel reporting (dual-write), validating data parity via API comparison, and performing the final cutover to ensure continuous monitoring and zero downtime.

This skill guides the setup of distributed tracing and performance monitoring using Sentry. It covers configuring the SDK (e.g., setting tracesSampleRate) to capture latency, identify performance bottlenecks, and trace requests across the entire application stack. It demonstrates how to create manual spans for business logic and utilizes profiling for deeper performance insights, ensuring comprehensive application observability.

A comprehensive guide to optimizing Sentry's performance monitoring pipeline. Learn how to minimize SDK overhead and event costs while maximizing signal quality. Techniques covered include replacing static sampling rates with dynamic `tracesSampler`, configuring profiling rates, preventing cardinality explosion through proper transaction naming, and implementing custom measurements for deeper business logic visibility. Essential for high-traffic, production applications.

A comprehensive checklist for ensuring Sentry is properly configured before any production deployment. This guide covers best practices for managing environment variables (DSN), implementing release tracking, optimizing error and trace sample rates, uploading source maps, and filtering noise. Essential for go-live readiness and auditing existing monitoring setups.

A comprehensive guide covering the principles of production-grade server management. Topics include process control (PM2, systemd), advanced monitoring strategies (Grafana, metrics), structured logging, scaling decisions (horizontal/vertical), and security best practices. It teaches systematic thinking for ensuring high availability, reliability, and scalability in complex systems.