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Grafana Loki: from discovery to expertise

Complete course on Grafana Loki: architecture, installation, collection with Alloy, LogQL, object storage, alerting and production operations.

8 chapters17 lessonsEN
At your pace, through practice.

By the end of this course you will be able to

  • Deploy Loki and collect logs with Alloy
  • Write LogQL log and metric queries
  • Configure object storage, retention and multi-tenancy
  • Alert on logs with the Ruler

🎯 Level : Intermediate👥 Who it is for : Operators and developers who centralise logs at low cost

LEARNING PATH

Course curriculum

0Course overview1 lesson
  1. Assessment quizQuiz · ⏱ 10 min
1Introduction and architecture4 lessons

Understand Loki's philosophy and deploy a first instance.

  1. What is Grafana Loki?Article · ⏱ 4 min
  2. Loki or Elasticsearch?Article · ⏱ 3 min
  3. Installing LokiArticle · ⏱ 19 min
  4. Lab: Deploy Loki and send your first logsHands-on lab · ⏱ 30 min · Level 1/5
2Log collection3 lessons

Send logs from files, containers and Kubernetes with Alloy.

  1. Collecting logs into LokiArticle · ⏱ 13 min
  2. Log management with AlloyArticle · ⏱ 5 min
  3. Lab: Collect container and file logs with AlloyHands-on lab · ⏱ 40 min · Level 2/5
3LogQL3 lessons

Query logs and turn them into metrics.

  1. LogQL: querying logsArticle · ⏱ 8 min
  2. LogQL: turning logs into metricsArticle · ⏱ 7 min
  3. Lab: Mastering LogQLHands-on lab · ⏱ 40 min · Level 2/5
4Storage and retention1 lesson

TSDB index, object storage, compactor and retention.

  1. Storage, TSDB index and retentionArticle · ⏱ 11 min
5Alerting with the Ruler2 lessons

Alert on logs and precompute metrics.

  1. The Loki RulerArticle · ⏱ 8 min
  2. Lab: Alerting on logs with the RulerHands-on lab · ⏱ 40 min · Level 3/5
6Running in production2 lessons

Multi-tenancy, limits, cardinality and monitoring.

  1. Running Loki in productionArticle · ⏱ 10 min
  2. Final Lab: Log platform with MinIO, retention and multi-tenancyHands-on lab · ⏱ 1 h · Level 4/5
7Best practices1 lesson

Recommended practices for running the product in production.

  1. Loki best practicesArticle · ⏱ 9 min

LEARN BY DOING

Use cases & applications

Kubernetes container logs

Centralise the logs of every pod with the same labels as the metrics.

Metrics - logs - traces correlation

Go from an alert to its logs and then to the matching trace in Grafana.

Long-term auditing

Keep audit logs for years at low cost on object storage.

Alerts on logs

Trigger alerts when a pattern appears or when a service goes silent.

Recommended prerequisites

Grafana: From Discovery to Expertise

What next?

Grafana Tempo: from discovery to expertiseFluent Bit and Vector: lightweight log collectionAlloy: From Discovery to Expertise

Frequently asked questions

What is Grafana Loki?

A log aggregation system from Grafana Labs, inspired by Prometheus: it only indexes stream labels and stores the compressed content in object storage, which makes it cost-effective.

Does Loki replace Elasticsearch?

For application and infrastructure logs, often yes. If you need full-text search over large volumes without context, Elasticsearch remains a better fit.

Which language is used to query Loki?

LogQL, which is close to PromQL: label selectors, line filters, parsers and metric functions.

Which agent should I use to send logs?

Grafana Alloy is the recommended collector; Promtail is deprecated.