Skill UI

A comprehensive collection of diagnostic scripts designed for troubleshooting Sentry integration failures. This bundle collects SDK versions, runtime configuration details (e.g., DSN, environment), and performs network connectivity checks to the Sentry ingest endpoint. Use it when events are not appearing in Sentry, or when systematically diagnosing complex setup issues across Node.js and Python environments.

Master advanced error capture and context enrichment using Sentry SDKs for both TypeScript and Python. This skill teaches how to reliably capture exceptions, track non-exception events (messages), and enrich reports with structured data like user context, tags, breadcrumbs, and custom fingerprints. It is essential for dramatically improving the ability to diagnose complex production issues quickly.

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 guide provides a comprehensive, environment-aware setup for Sentry in local development workflows. It details how to correctly route development events to separate DSNs, enable verbose debugging, and maximize data capture rates (e.g., setting sample rates to 1.0). Users learn to use `startSpan` for performance profiling and ensure that sensitive credentials are safely managed outside of source control.

Provides a comprehensive guide and code examples for configuring Sentry across development, staging, and production environments. It ensures data isolation by using separate DSNs, allows tuning of sample rates (e.g., 10% for production, 100% for dev), and implements environment-specific logic for PII scrubbing and event filtering, optimizing visibility while maintaining data security.

This skill guides you through advanced integration patterns to connect Sentry with your full observability stack. Learn how to correlate error events from structured loggers (like Winston/Pino) using Event IDs, track business metrics (counters, gauges) within Sentry, and link performance data across multiple tools (Grafana, Datadog). Achieve end-to-end visibility, ensuring every error is tied back to its root cause and business context.

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.

This framework enforces organizational governance and policy guardrails for Sentry usage. It standardizes configuration across services, mandatorily scrubbing PII, enforcing naming conventions, and managing trace rate caps based on service criticality. It integrates into CI/CD to prevent compliance drift and ensure adherence to standards like GDPR and HIPAA.

A comprehensive guide to managing Sentry's event volume, quotas, and rate limits. Learn how to prevent 429 Too Many Requests errors and control costs by implementing client-side sampling (sampleRate/tracesSampleRate), using beforeSend filters to drop noisy errors, and understanding various quota types (Errors, Transactions, Replays). Essential for high-volume, cost-sensitive applications.

This comprehensive guide details how to harden Sentry's security posture and ensure compliance with regulations like GDPR. It covers best practices for managing sensitive data, implementing PII scrubbing, and configuring `beforeSend` hooks to automatically redact sensitive information such as passwords, API keys, tokens, IP addresses, and emails from client-side and server-side events.