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Found 356 Skills
Guides microservice design and delivery—bounded contexts, service boundaries, REST/gRPC/event APIs, sync vs async tradeoffs, resilience (timeouts, retries, circuit breakers, bulkheads), per-service data ownership, saga and outbox patterns, twelve-factor containers, observability (logs, metrics, trace propagation), API versioning at gateways/meshes, and contract testing. Use for microservices developer, service boundary, bounded context, gRPC between services, circuit breaker, saga pattern, outbox pattern, twelve-factor, contract testing microservices, service decomposition, or event-driven microservice—not K8s platform ops (platform-engineer, site-reliability-engineer), enterprise iPaaS (enterprise-integration-api-developer), monolith-first apps (senior-software-engineer), or classified pipelines (classified-software-devsecops-engineer).
Guidelines for structured logging, distributed tracing, and debugging patterns across languages. Covers logging best practices, observability, security considerations, and performance analysis.
Expert skill for Datadog Observability & Security Platform
Expert site reliability engineer specializing in SLOs, error budgets, observability, chaos engineering, and toil reduction for production systems at scale.
Supabase Edge Function observability style: tiny provider-neutral OTel-shaped shim, OTLP export config, traces/logs/metrics, and LLM cost metrics.
Build production-ready multi-agent AI systems with security, observability, and scalability using LangGraph and FastAPI
Use when you need to implement or improve Java metrics observability with Micrometer — including meter design, naming/tag conventions, cardinality control, timers/counters/gauges/distribution summaries, percentiles/histograms, Actuator/Prometheus integration, and metrics validation through tests. This should trigger for requests such as Improve metrics; Apply Micrometer; Add metrics observability; Refactor Micrometer instrumentation. Part of cursor-rules-java project
Plan, create, and configure production-ready Azure Kubernetes Service (AKS) clusters. Covers Day-0 checklist, SKU selection (Automatic vs Standard), networking options (private API server, Azure CNI Overlay, egress configuration), security, and operations (autoscaling, upgrade strategy, cost analysis). WHEN: create AKS environment, provision AKS environment, enable AKS observability, design AKS networking, choose AKS SKU, secure AKS.
Instrument web applications to send telemetry data to Azure Application Insights for observability and monitoring. USE FOR: instrument app with app insights, add appinsights instrumentation, configure application insights, set up telemetry monitoring, enable app insights auto-instrumentation, add observability to azure web app, instrument webapp to send data to app insights, configure telemetry for app service. DO NOT USE FOR: non-Azure monitoring (use CloudWatch for AWS, Datadog for third-party), log analysis (use azure-kusto), cost monitoring (use azure-cost-optimization), security monitoring (use azure-security).
Azure Observability Services including Azure Monitor, Application Insights, Log Analytics, Alerts, and Workbooks. Provides metrics, APM, distributed tracing, KQL queries, and interactive reports.
This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or API code patterns (use google-agents-cli-adk-code).
Golang everyday observability — the always-on signals in production. Covers structured logging with slog, Prometheus metrics, OpenTelemetry distributed tracing, continuous profiling with pprof/Pyroscope, server-side RUM event tracking, alerting, and Grafana dashboards. Apply when instrumenting Go services for production monitoring, setting up metrics or alerting, adding OpenTelemetry tracing, correlating logs with traces, migrating legacy loggers (zap/logrus/zerolog) to slog, adding observability to new features, or implementing GDPR/CCPA-compliant tracking with Customer Data Platforms (CDP). Not for temporary deep-dive performance investigation (→ See golang-benchmark and golang-performance skills).