We Cut Log Costs by 35% Using Vector 0.30 and Loki 3.0: Lessons from a 3-Month Tuning

The provided code examples showcase configurations and scripts related to log management systems such as Vector, Filebeat, Loki, and Elasticsearch. Here's a detailed breakdown of each:

Code Example 1: Vector Configuration for Log Egress

This YAML configuration file sets up Vector to collect logs from various sources (e.g., Docker containers) and send them to Loki via HTTP POST requests.

• Sources: Configured to read logs from /var/log/containers/*.log.
• Transforms: Applies a transformation to add Kubernetes metadata to each log entry.
• Sinks: Sends the transformed log entries to Loki using an HTTP sink with specific headers (e.g., X-Scope-OrgID).

Code Example 2: Loki Configuration

This YAML file configures Loki, a horizontally-scalable, highly-available multi-tenant log aggregation system.

• Ingester: Defines how logs are chunked and stored. It includes settings for chunk size, idle period before flushing to storage, and maximum series per query.
• Storage Config: Specifies the use of GCS (Google Cloud Storage) for long-term retention of chunks and TSDB index for short-term indexing.
• Compactor: Sets up periodic compaction tasks that merge

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