Logging

11 items tagged with "logging"

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Best Practices1

Structured Logging

Emitting logs as machine-parseable key-value records (typically JSON) with consistent fields, so logs can be searched, filtered, and correlated at scale.

Patterns1

Pattern

Correlation ID

Assigns a unique identifier to a request and propagates it through every service and log, so related events across a distributed system can be tied together.

Anti-Patterns2

Anti-Pattern

Log Everything (Logging Noise)

Logging indiscriminately at high verbosity, burying useful signal in a flood of low-value messages while driving up storage cost and slowing search.

Anti-Pattern

Logging Sensitive Data

Writing passwords, tokens, PII, or payment data into logs, where it spreads to aggregators and backups far beyond its intended access controls.

Tutorials1

Tutorial

How to Centralize Logs with Grafana Loki

Ship structured logs to Loki, label them effectively, and query with LogQL to investigate incidents from one place.

Stacks3

Stack

ELK Analytics Stack

Elasticsearch, Logstash, and Kibana for ingesting, indexing, searching, and visualizing logs, metrics, and events at scale.

Stack

PLG Stack (Prometheus + Loki + Grafana)

Open-source observability stack: Prometheus collects metrics, Loki aggregates logs, and Grafana unifies visualization, dashboards, and alerting.

Stack

Elastic Observability Stack

Observability built on the Elastic Stack: Beats and APM agents feed Elasticsearch, with Kibana unifying logs, metrics, and traces in one platform.

Comparisons2

Comparison

Grafana vs Kibana

Grafana is a source-agnostic visualization and dashboarding tool; Kibana is the visualization layer of the Elastic Stack, optimized for log and search analytics.

Comparison

ELK Stack vs Grafana Loki

The ELK Stack indexes full log content for powerful search; Grafana Loki indexes only labels for cheaper, lighter log aggregation.

FAQs1

FAQ

What are the three pillars of observability?

The three pillars of observability are metrics, logs, and traces. Metrics are numeric time-series data, such as request rate or error count, that are ...