log-analysis

name	log-analysis
description	Parsing logs, correlation analysis, reconstructing timeline of failures.

Log Analysis

Extracting signal from system logs to understand failure sequences.

Context

You are analyzing logs to find the failure cause. Look for timeline, patterns, correlations.

Domain Context

• Timeline: Reconstruct what happened when; precise ordering matters
• Error Codes: What errors occurred? In what sequence?
• Correlation: Are errors across components? Do they align with infrastructure events?
• Search: Use grep, jq, SQL to find relevant entries
• Context: Include lines before/after errors; context matters

Instructions

1. Establish Timeline: Extract timestamps; create chronological view
2. Filter Noise: Remove expected errors, noise; focus on anomalies
3. Find Correlation: Do errors align? Were requests affected?
4. Look for Cascades: One error triggers others?
5. Check Systems: App logs, infrastructure logs, database logs together
6. Extract Variables: What IDs, values were involved?
7. Visualize: Create timeline or flow diagram

Anti-Patterns

• Relying on log levels (ERROR) alone; logs labeled ERROR might be expected failures
• Not correlating across systems; bug often spans app + infrastructure
• Ignoring INFO logs; they provide context for ERROR understanding
• Timestamps not synchronized; makes correlation impossible
• Logs too verbose (every DB query); filter to signal

Further Reading

• Google Cloud Logging best practices
• ELK Stack (Elasticsearch, Logstash, Kibana) tutorials