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Logging Overview

The Coderz Stack runs two parallel log pipelines. Each has different strengths and serves different use cases.

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Pipeline 1: Loki + Promtail (Fast & Simple)

Docker container stdout/stderr
        │
        ▼
   Promtail (log collector)
        │
        ▼
     Loki :3100 (log storage)
        │
        ▼
   Grafana (log viewer)
Best for:
  • Live log tailing during incidents
  • Correlating logs with metrics on the same Grafana dashboard
  • Simple keyword searches
  • Low resource usage

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Pipeline 2: ELK Stack (Deep Analytics)

Docker container logs + System logs
        │
        ▼
   Filebeat (log shipper)
        │
        ▼
  Logstash :5044 (processing & enrichment)
        │
        ▼
Elasticsearch :9200 (indexed storage)
        │
        ▼
   Kibana :5601 (search & analytics)
Best for:
  • Complex log searches with filters
  • Structured log parsing (JSON, grok patterns)
  • API request logs with IP, duration, status codes
  • Building saved searches and visualizations
  • Compliance and audit trails

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Which One to Use?

ScenarioUse
”Show me logs from the last 5 minutes”Loki in Grafana
”Find all 500 errors from the .NET API today”Kibana
”Which IP hit the API most in the last hour?”Kibana
”Correlate a CPU spike with application logs”Loki in Grafana
”Show slow queries that took > 1 second”Kibana
”Live log stream during a deployment”Loki in Grafana

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Kibana Data Views

Index PatternData
filebeat-*System logs + all Docker container logs
logstash-*Logstash-processed and enriched logs

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Pre-Built Saved Searches in Kibana

  • Error & Critical Logs
  • Warning Logs
  • Docker Container Logs
  • Coderz Stack Logs
  • Logstash Logs
  • System Logs