Log Aggregation

Overview

Log aggregation centralizes logs from multiple services and hosts into one searchable platform.

Aggregation Pipeline

flowchart LR
    A[Apps and Nodes] --> B[Collectors]
    B --> C[Processing Pipeline]
    C --> D[Central Storage]
    D --> E[Dashboards and Alerts]

Practical Example

pipeline:
  inputs:
    - kubernetes
    - vm-syslog
  processors:
    - parse-json
    - drop-sensitive-fields
  outputs:
    - elasticsearch

Production Example

A platform team aggregates logs from Kubernetes workloads and legacy virtual machines, enabling unified incident timelines.

Common Pitfalls

• No retention policy planning
• High storage cost due to uncontrolled ingestion
• Missing parse rules for diverse log formats

Key Takeaways

• Centralized logs improve incident response speed.
• Parsing, retention, and cost controls are foundational.
• Aggregation quality depends on source log quality.