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Found 17 Skills
Reduce Grafana Cloud Metrics costs by managing cardinality with Adaptive Metrics aggregation rules. Use when the user asks to reduce metrics costs, manage cardinality, create aggregation rules, apply label dropping, analyse unused metrics, understand Active Series, or optimise Prometheus storage. Triggers on phrases like "adaptive metrics", "reduce cardinality", "aggregation rules", "metrics cost", "too many series", "Active Series", "label dropping", "unused metrics", "cardinality reduction", or "metrics spend".
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.
Grafana Cloud Application Observability (APM), Frontend Observability (RUM/Faro), and AI Observability. Covers RED metrics (Rate/Error/Duration), service maps, span metrics from traces, Faro JavaScript/React SDK for browser instrumentation, session replay, AI/LLM model monitoring, and integration with traces/logs/profiles for full-stack correlation. Use when setting up APM, configuring frontend monitoring, analyzing service performance, or monitoring AI/LLM applications.
Grafana Cloud cost management — usage monitoring, cost attribution by label, usage alerts, invoice management, and optimization strategies. Covers Adaptive Metrics (cardinality reduction), Adaptive Logs (log filtering), cost attribution labels, and the FOCUS-compliant billing application. Use when analyzing Grafana Cloud spending, setting up cost alerts, attributing costs to teams, reducing metric/log cardinality, or forecasting observability budgets.
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".
Grafana Cloud AI and ML features — Grafana Assistant (natural language queries, dashboard generation, incident investigations), Dynamic Alerting (ML forecasting and outlier detection), Sift (automated root cause analysis with 8 analysis types), Knowledge Graph (entity discovery and RCA Workbench), and the LLM Plugin (OpenAI/Anthropic/Azure integration). Use when setting up AI-powered alerting, using natural language to query metrics/logs, automating incident investigation, or integrating LLMs with Grafana panels and workflows.
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.
Sending telemetry data to Grafana Cloud — metrics via Prometheus remote write or OTLP, logs via Loki push or Alloy, traces via OTLP to Tempo, profiles via Pyroscope. Covers Alloy-based pipelines, direct SDK/agent integrations, cloud integrations catalog, and credentials management. Use when connecting an application or infrastructure to Grafana Cloud, setting up data ingestion, configuring remote write, or choosing between ingestion methods.
Write, validate, and optimise PromQL queries for Prometheus and Grafana Cloud Metrics. Use when the user asks to query metrics, write a PromQL expression, calculate rates, aggregate across labels, build histogram quantiles, create recording rules, debug query performance, or understand metric cardinality. Triggers on phrases like "PromQL", "Prometheus query", "write a metric query", "calculate rate", "histogram_quantile", "recording rule", "metric cardinality", "sum by", "rate vs irate", "absent()", or "query is slow".
Grafana Alloy OpenTelemetry collector and telemetry pipeline configuration. Covers the Alloy configuration language (blocks, attributes, expressions), components for collecting metrics/logs/traces/profiles, sending data to Grafana Cloud/Prometheus/Loki/Tempo, clustering, Fleet Management remote config, and building telemetry pipelines. Use when configuring Alloy, writing Alloy config files (.alloy), building data collection pipelines, setting up scraping, or troubleshooting Alloy deployments.
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.
Prometheus and Grafana Cloud Metrics overview including PromQL query language, Metrics Drilldown, alerting, recording rules, and integration patterns. Use when working with Prometheus, writing PromQL queries, configuring alerting, or discussing metrics architecture and best practices.