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Found 87 Skills
Set up monitoring, logging, and observability for applications and infrastructure. Use when implementing health checks, metrics collection, log aggregation, or alerting systems. Handles Prometheus, Grafana, ELK Stack, Datadog, and monitoring best practices.
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.
Set up comprehensive infrastructure monitoring with Prometheus, Grafana, and alerting systems for metrics, health checks, and performance tracking.
Create professional Grafana dashboards with visualizations, templating, and alerts. Use when building monitoring dashboards, creating data visualizations, or setting up operational insights.
Comprehensive observability and monitoring skill covering Prometheus, Grafana, metrics collection, alerting, exporters, PromQL, and production monitoring patterns for distributed systems and cloud-native applications
Application monitoring and observability setup for Python/React projects. Use when configuring logging, metrics collection, health checks, alerting rules, or dashboard creation. Covers structured logging with structlog, Prometheus metrics for FastAPI, health check endpoints, alert threshold design, Grafana dashboard patterns, error tracking with Sentry, and uptime monitoring. Does NOT cover incident response procedures (use incident-response) or deployment (use deployment-pipeline).
Query Prometheus and Loki billing metrics from Grafana. Use when discussing observability costs, active series, ingestion rates, storage usage, or cardinality analysis.
OpenTelemetry with Grafana stack. Covers OTel SDK instrumentation for Go/Java/Python/Node.js/.NET, OTLP protocol and endpoint configuration, sending telemetry to Grafana Cloud via OTLP endpoint, Grafana Alloy as OTel collector, sampling strategies, Kubernetes OTel Operator, and migration from other observability tools. Use when instrumenting apps with OTel, configuring OTLP endpoints, setting up collectors, or migrating to OpenTelemetry.
Grafana Beyla eBPF auto-instrumentation for application observability without code changes. Covers supported languages/runtimes, requirements, installation, configuration (discovery, eBPF settings, OTLP traces export, Prometheus metrics export), Kubernetes deployment, and integration with Grafana Cloud. Use when setting up zero-code instrumentation, configuring eBPF probes, deploying Beyla to Kubernetes, connecting to Tempo/Prometheus, or troubleshooting instrumentation issues.
Create, modify, and organise Grafana dashboards including panels, variables, transformations, and alerting. Use when the user asks to create a Grafana dashboard, add a panel, configure a time series or stat panel, add template variables, set up dashboard linking, use transformations, configure thresholds, build a dashboard for a service, or export dashboard JSON. Triggers on phrases like "create dashboard", "add panel", "time series panel", "Grafana dashboard JSON", "template variables", "dashboard variable", "panel transformation", "threshold", "stat panel", "table panel", "Grafana annotations", or "dashboard folder".
Grafana Pyroscope continuous profiling platform. Covers instrumentation of Go/Java/Python/Ruby/Node.js/ .NET/Rust apps via SDKs or eBPF (Alloy), flame graph analysis, ProfileQL queries, server configuration and architecture, Grafana Cloud Profiles integration, and trace-profile linking (Span Profiles). Use when working with profiling data, instrumenting apps for Pyroscope, analyzing performance profiles, or deploying Pyroscope server.
Grafana Tempo distributed tracing backend. Covers TraceQL query language (span selectors, attribute scopes, pipeline operators, structural operators, metrics functions), trace ingestion via OTLP/Jaeger/Zipkin, Tempo architecture (distributor/ingester/compactor/querier/metrics-generator), full configuration reference with YAML, metrics-from-traces (span metrics, service graphs, TraceQL metrics), deployment modes (monolithic/microservices/Helm/Kubernetes), multi-tenancy, performance tuning, caching, and HTTP API. Use when working with distributed traces, writing TraceQL queries, deploying Tempo, configuring trace pipelines, or setting up Grafana-Tempo integrations (traces-to-logs, traces-to-metrics, traces-to-profiles).