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.

This guide provides a comprehensive, multi-language walkthrough for installing and initializing the Sentry SDK in various environments (Node.js, Python, Browser). It covers essential concepts like DSN setup, using secure environment variables, configuring release versions, and implementing basic error and performance tracking for robust observability in production and CI/CD pipelines.

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.

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 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.

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 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.

This guide provides enterprise-grade architectural patterns for integrating Sentry into multi-service, microservices environments. It covers centralized configuration modules, standardized project topologies (e.g., one project per service), distributed tracing setup, and robust error handling middleware for Node.js, Express, and Python/FastAPI. Ideal for organizations planning large-scale Sentry rollouts or managing complex service ecosystems.

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.

Automates Sequelize model creation for backend development, offering step-by-step guidance, best practices, and production-ready code/config validation when working with Node.js, Python, Go, databases, caching, messaging, and microservices.

Guides engineers through setting up Server Sent Events connections as part of API integration work, providing best practices, sample configurations, and validated code for third-party webhooks, SDKs, and OAuth flows.