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RunBook Academy

ObservabilityXXV · Grafana Data SourcesGrafanaDataSources

Loki as a Data Source

Foundation⏱ ~18 minbash

What you'll learn

  • Explain loki as a data source in production terms
  • Configure and operate loki as a data source in a production observability stack
  • Recognise and diagnose the most common failure modes
  • Apply the discipline to a real Prometheus / Grafana / Loki / Tempo environment

Prerequisites

Verified against Prometheus 2.55.x · Alertmanager 0.28.x · node_exporter 1.8.x · blackbox_exporter 0.26.x · Grafana 11.x · Loki 3.x · Tempo current · OpenTelemetry Collector 0.110.x · Grafana Alloy current · Docker Engine 28.x · Ubuntu 24.04 LTS · Debian 12 (Bookworm) · RHEL / Rocky / AlmaLinux 9.x · 2026-08-13

Not yet marked complete on this device.

The Loki datasource connects Grafana to Loki over HTTP. LogQL is the query language.

A configured Loki datasource lets dashboards show logs alongside metrics.

What it is

A precise definition of loki as a data source, scoped to production operations.

Why a sysadmin cares

Production framing. The operational pain this concept addresses, or the incident class it prevents.

How it works

The mental model.

How to configure it

# Configuration snippet illustrating the lesson topic
example_setting: value

How to validate it

promtool check config /etc/prometheus/prometheus.yml

How it can fail

The high-frequency failure modes:

  1. Silent misconfiguration.
  2. Crash on load.
  3. Performance regression.
  4. Permissions failure.
  5. Schema / version drift.

How to troubleshoot it

The diagnostic order:

  1. Was it working before?
  2. What does the service’s view say?
  3. What does the platform’s view say?
  4. Form hypothesis, find evidence, test, validate.

Security implications

Loki as a Data Source has security implications wherever the relevant component exposes an HTTP endpoint, an authentication layer, or a credential.

Performance implications

Performance implications come from cardinality, scrape / push interval, rule size, retention, and query cost.

Production guidance

  • Validate before applying.
  • Test changes in a non-production environment.
  • Document operational defaults in the team’s instrumentation guide.

Verification

You should now be able to answer:

  • What is loki as a data source in production terms?
  • Why does a sysadmin care about it?
  • How does it fail and how do you diagnose the failure?

Quiz

Knowledge check · 8 questions

  1. Q1. What is the primary purpose of loki as a data source?

  2. Q2. Which failure mode of loki as a data source is most operationally costly?

  3. Q3. Production verification should run on production hosts.

  4. Q4. First response when loki as a data source misbehaves?

  5. Q5. Name one signal that confirms loki as a data source is healthy.

  6. Q6. Which of these are validation steps?

  7. Q7. Right discipline when changing in production?

  8. Q8. Telemetry usefulness requires:

Passing score: 75%. Answers are checked in this browser.