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Found 95 Skills
Observability and monitoring for data pipelines using OpenTelemetry (traces) and Prometheus (metrics). Covers instrumentation, dashboards, and alerting.
Scaffold a production-ready Go HTTP service with OpenTelemetry observability, TLS, lifecycle management, Dockerfile, GitHub Actions CI/CD, and golangci-lint. Use when creating or regenerating a full Go service skeleton (project layout, config package, server package, CI workflows, and container build files).
Integrates Flowlines observability SDK into Python LLM applications. Use when adding Flowlines telemetry, instrumenting LLM providers, or setting up OpenTelemetry-based LLM monitoring.
Set up Kafka-based event-driven microservices with Platformatic Watt. Use when users ask about: - "kafka", "event-driven", "messaging" - "kafka hooks", "kafka webhooks" - "kafka producer", "kafka consumer" - "dead letter queue", "DLQ" - "request response pattern" with Kafka - "migrate from kafkajs", "kafkajs migration", "replace kafkajs" Covers @platformatic/kafka, @platformatic/kafka-hooks, consumer lag monitoring, and OpenTelemetry instrumentation.
Parses OpenTelemetry-formatted logs to reconstruct execution traces, extract errors with call chains, and provide AI-powered root cause analysis. Use when investigating errors, checking logs, debugging issues, viewing traces, or analyzing execution flow. Triggers on "check the logs", "analyze errors", "what's failing", "debug this issue", "show me the traces", or "investigate the error".
OpenTelemetry, structured logging, distributed tracing, alerting, and dashboards
Use this skill when implementing logging, metrics, distributed tracing, alerting, or defining SLOs. Triggers on structured logging, Prometheus, Grafana, OpenTelemetry, Datadog, distributed tracing, error tracking, dashboards, alert fatigue, SLIs, SLOs, error budgets, and any task requiring system observability or monitoring setup.
Use when the user needs API design, microservices architecture, event-driven systems, database integration, caching strategies, or backend observability. Triggers: REST/GraphQL API implementation, service architecture design, message queue setup, rate limiting, health checks, OpenTelemetry integration.
This skill should be used when adding error tracking and performance monitoring with Sentry and OpenTelemetry tracing to Next.js applications. Apply when setting up error monitoring, configuring tracing for Server Actions and routes, implementing logging wrappers, adding performance instrumentation, or establishing observability for debugging production issues.
Builds, configures, debugs, and optimizes AWS observability using CloudWatch (Logs Insights, Metrics, Alarms, Dashboards, EMF), X-Ray, CloudTrail, and ADOT. Covers Log Insights query syntax (fields, filter, stats, parse, pattern, join, subqueries), alarm configuration (metric, composite, anomaly detection, missing data treatment), dashboard design, custom metrics (PutMetricData, EMF, metric filters), X-Ray tracing (ADOT, sampling rules, annotations vs metadata), ADOT collector config, and CloudTrail auditing. Use when the user mentions CloudWatch, Log Insights, alarms, INSUFFICIENT_DATA, dashboards, custom metrics, EMF, X-Ray, traces, sampling, CloudTrail, who deleted, ADOT, OpenTelemetry, observability, monitoring, synthetics, canaries, or troubleshooting alarm behavior. Do NOT use for application logging setup, container log drivers, or security threat detection.
Production-grade backend service development across Node.js (Express/Fastify/NestJS/Hono), Bun, Python (FastAPI), Go, and Rust (Axum), with PostgreSQL and common ORMs (Prisma/Drizzle/SQLAlchemy/GORM/SeaORM). Use for REST/GraphQL/tRPC APIs, auth (OIDC/OAuth), caching, background jobs, observability (OpenTelemetry), testing, deployment readiness, and zero-trust defaults.
Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance monitoring. Handles end-to-end optimization, real user monitoring, and scalability patterns. Use PROACTIVELY for performance optimization, observability, or scalability challenges.