Log Aggregation
This walks you through setting up centralized logging with ELK Stack, Loki, or Splunk to collect and analyze logs across your infrastructure. You get Docker Compose configurations for the full ELK stack, Logstash pipeline configs for parsing, Filebeat setup for log shipping, and Kibana dashboard templates. The reference guides cover both traditional and Kubernetes deployments. Honestly, the best practices section is the most valuable part here because log aggregation is easy to set up badly. It'll save you from common mistakes like logging PII, ignoring retention costs, or running DEBUG level in production. Good starting point if you're moving past grepping server logs manually.
- skills.sh installs
- 453
- GitHub stars
- 379
- last updated
- Aug 21, 2026
Install
$ npx -y skills add aj-geddes/useful-ai-prompts --skill log-aggregation --agent claude-codeInstalls into .claude/skills of the current project.
Files
Log Aggregation
Table of Contents
Overview
Build comprehensive log aggregation systems to collect, parse, and analyze logs from multiple sources, enabling centralized monitoring, debugging, and compliance auditing.
When to Use
- Centralized log collection
- Distributed system debugging
- Compliance and audit logging
- Security event monitoring
- Application performance analysis
- Error tracking and alerting
- Historical log retention
- Real-time log searching
Quick Start
Minimal working example:
# docker-compose.yml - ELK Stack setup
version: "3.8"
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- Repository
- github.com/aj-geddes/useful-ai-prompts
- Categories
- DevOps & CI/CD, AI & Agent Building, Cloud & Infrastructure
- First seen
- Jun 3, 2026
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- Continuous Testing441
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