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Found 112 Skills
Use when working with CUE kind definitions, schemas, or versioning in grafana-app-sdk projects (app platform apps). This skill should be used when the user asks to "define a kind", "add a CUE kind", "write a kind schema", "create a CUE schema", "model a resource", "add a new resource type", "edit kinds/", "what is a kind in grafana-app-sdk", "add a version to a kind", or asks about CUE kind structure, versioning, schema fields, validation constraints, or the codegen configuration section. Provides guidance on authoring CUE kind definitions for grafana-app-sdk projects.
Grafana Cloud infrastructure monitoring — Kubernetes monitoring, cloud provider integrations (AWS, Azure, GCP), host and container monitoring, infrastructure dashboards, and collector setup. Use when setting up Kubernetes monitoring, connecting cloud provider metrics, configuring node exporter or cAdvisor, setting up infrastructure dashboards, or using the k8s-monitoring Helm chart.
Use when the user asks to "write a reconciler", "implement a reconciler", "add business logic", "handle resource changes", "process resource events", "implement the reconcile loop", "add async processing", "write a controller", "handle create/update/delete events", "use TypedReconciler", "use a Watcher", or asks how to respond to resource state changes in a grafana-app-sdk app. Provides guidance on implementing reconciler and watcher business logic for grafana-app-sdk apps.
Grafana-to-Perses dashboard migration: export Grafana dashboards, convert with percli migrate, validate converted output, fix incompatibilities, deploy to Perses. Handles bulk migration with parallel processing. Use for "migrate grafana", "grafana to perses", "perses migrate", "convert grafana". Do NOT use for creating new dashboards from scratch (use perses-dashboard-create).
Expert evaluator for Grafana Loki label strategy. Audits, designs, and improves label schemas using cardinality scoring, access-pattern alignment, static vs. dynamic label rules, and consistency checks. Use when the user asks to evaluate, audit, design, or improve a Loki label strategy — or asks why their Loki queries are slow.
Observability visualization with Grafana and LGTM stack. Dashboard design, panel configuration, alerting, variables/templating, and data sources. USE WHEN: Creating Grafana dashboards, configuring panels and visualizations, writing LogQL/TraceQL queries, setting up Grafana data sources, configuring dashboard variables and templates, building Grafana alerts. DO NOT USE: For writing PromQL queries (use /prometheus), for alerting rule strategy (use /prometheus), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: grafana, dashboard, panel, visualization, logql, traceql, loki, tempo, mimir, data source, annotation, variable, template, row, stat, graph, table, heatmap, gauge, bar chart, pie chart, time series, logs panel, traces panel, LGTM stack.
Set up, configure, and troubleshoot Grafana Cloud integrations for AWS, Azure, and other cloud providers. Use when the user asks to connect AWS CloudWatch, set up Azure Monitor, configure Confluent Cloud observability, install a Grafana integration, set up hosted exporters, use AWS Firehose for CloudWatch logs, or troubleshoot a cloud integration. Triggers on phrases like "AWS CloudWatch", "Azure Monitor", "Confluent integration", "cloud integration", "hosted exporter", "AWS Firehose", "install integration", "cloud metrics", or "cloud logs".
Use when the user asks to "write a validator", "add validation", "implement admission control", "write a mutating webhook", "add a mutation handler", "validate incoming resources", "implement admission logic", "add admission webhooks", "write ingress validation", or asks how to validate or mutate resources before they are persisted in a grafana-app-sdk app. Provides guidance on implementing validation and mutation admission handlers for grafana-app-sdk apps.
Expert-level Grafana dashboards, visualization, data sources, alerting, and production operations
Design, refactor, and validate Grafana dashboards for OpenShift/Kubernetes platform operations. Use when users ask to improve platform health dashboards, prioritize critical tenant-impacting signals, filter noise (for example ArgoCD), add Crossplane/Keycloak health panels, validate PromQL programmatically, or apply GrafanaDashboard CR changes live then promote to GitOps.
Grafana Cloud Database Observability — query-level performance insights for MySQL and PostgreSQL. Covers setup with Grafana Alloy, query samples, visual explain plans, RED metrics, pg_stat_statements and Performance Schema integration, and correlation with application traces. Use when monitoring database performance, diagnosing slow queries, setting up database observability for MySQL or PostgreSQL (self-managed, RDS, Aurora, Azure, Cloud SQL), or correlating DB metrics with APM data.
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).