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Found 18 Skills
Implement centralized logging with ELK Stack, Loki, or Splunk for log collection, parsing, storage, and analysis across infrastructure.
Generate LogQL queries, log stream selectors, metric queries, and alerting rules for Grafana Loki.
Guide for implementing Grafana Loki - a horizontally scalable, highly available log aggregation system. Use when configuring Loki deployments, setting up storage backends (S3, Azure Blob, GCS), writing LogQL queries, configuring retention and compaction, deploying via Helm, integrating with OpenTelemetry, or troubleshooting Loki issues on Kubernetes.
Query Prometheus and Loki billing metrics from Grafana. Use when discussing observability costs, active series, ingestion rates, storage usage, or cardinality analysis.
Grafana Loki log aggregation and LogQL query language. Covers LogQL syntax (log queries, metric queries, label matchers, line filters, parsers: json/logfmt/pattern/regexp/unpack, label filters, line_format), Loki architecture, log ingestion via Alloy/Promtail/Fluent Bit, structured metadata, and Logs Drilldown. Use when writing LogQL queries, configuring Loki, troubleshooting log pipelines, or analyzing logs.
Generate/create Loki configs — ingester, querier, compactor, ruler, S3/GCS/Azure backends.
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.
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.
Production server monitoring stack covering Prometheus, Node Exporter, Grafana, Alertmanager, Loki, and Promtail on bare-metal or VM Linux hosts. USE WHEN: - Setting up monitoring for a new production server or VPS - Configuring Prometheus scrape targets for application or system metrics - Creating Grafana dashboards and datasource provisioning - Writing Alertmanager routing rules with email/Slack notifications - Implementing the PLG stack (Promtail + Loki + Grafana) for log aggregation - Performing live system diagnostics with htop, iotop, nethogs, ss, vmstat, iostat - Setting up uptime monitoring with UptimeRobot or healthchecks.io DO NOT USE FOR: - Kubernetes-native observability (use the kubernetes skill instead) - Application-level APM (distributed tracing with Jaeger/Tempo — use observability skill) - Cloud-managed monitoring (CloudWatch, GCP Monitoring, Azure Monitor) - Windows Server monitoring
Query Ethereum network data via ethpandaops CLI or MCP server. Use when analyzing blockchain data, block timing, attestations, validator performance, network health, or infrastructure metrics. Provides access to ClickHouse (blockchain data), Prometheus (metrics), Loki (logs), and Dora (explorer APIs).
Comprehensive logging and observability patterns for production systems including structured logging, distributed tracing, metrics collection, log aggregation, and alerting. Triggers for this skill - log, logging, logs, trace, tracing, traces, metrics, observability, OpenTelemetry, OTEL, Jaeger, Zipkin, structured logging, log level, debug, info, warn, error, fatal, correlation ID, span, spans, ELK, Elasticsearch, Loki, Datadog, Prometheus, Grafana, distributed tracing, log aggregation, alerting, monitoring, JSON logs, telemetry.
Create a new built-in evlog adapter to send wide events to an external observability platform. Use when adding a new drain adapter (e.g., for Datadog, Sentry, Loki, Elasticsearch, etc.) to the evlog package. Covers source code, build config, package exports, tests, and all documentation.