Log Management Best Practices Cheat Sheet

Patterns for structured logging, centralized log aggregation, retention, and querying across distributed systems.

2 PagesIntermediateFeb 2, 2026

Standard Log Levels

Common severity levels and when to use them.

DEBUG- Detailed diagnostic info, disabled in production by default
INFO- Routine operational events, e.g. request handled, job started
WARN- Unexpected but recoverable condition
ERROR- Operation failed, requires attention but process continues
FATAL/CRITICAL- Unrecoverable error, process is about to exit

Structured JSON Logging

Emit logs as JSON so they're machine-parseable by aggregators.

json

{  "timestamp": "2026-07-08T10:22:31Z",  "level": "error",  "service": "checkout-api",  "trace_id": "a1b2c3d4",  "message": "payment gateway timeout",  "http_status": 504,  "user_id": "u_9182"}

Elasticsearch / Kibana Query (KQL)

Query syntax for filtering logs in Kibana Discover.

text

# Find errors from a specific service in the last 15mservice: "checkout-api" and level: "error"# Range query on a numeric fieldhttp_status >= 500 and http_status < 600# Wildcard search on message textmessage: *timeout*

logrotate Config

Rotate and compress local log files to control disk usage.

bash

# /etc/logrotate.d/myapp/var/log/myapp/*.log {    daily    rotate 14    compress    delaycompress    missingok    notifempty    create 0640 appuser appgroup}

Centralized Logging Pipeline

Typical components in a log aggregation pipeline.

Shipper (Filebeat/Fluent Bit)- Lightweight agent that tails log files and forwards them
Aggregator (Logstash/Fluentd)- Parses, enriches, and transforms log events before storage
Storage (Elasticsearch/Loki)- Indexed store optimized for full-text or label-based search
Visualization (Kibana/Grafana)- Dashboards and ad-hoc search UI over stored logs

Pro Tip

Always propagate a trace/correlation ID through every log line for a request — it turns scattered logs into a single searchable thread across microservices.

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