kubernetes logging

kubernetes_logging.md

flowchart TD
    A[Kubernetes Cluster] --> B[Metrics Collection]
    A --> C[Log Collection]

    %% Metrics Branch
    B --> D[Prometheus]
    B --> Z[VictoriaMetrics Stack]
    D --> E[Grafana]
    D --> F[Alertmanager]
    D --> G[Mimir]
    Z --> ZA[VictoriaMetrics]
    Z --> ZB[VMAlert]
    Z --> ZC[VMUI]
    Z --> ZD[Grafana]

    %% Log Branch
    C --> H[EFK Stack]
    C --> I[Loki]
    C --> J[Fluent Bit / Promtail / Vector]

    %% EFK Details
    H --> K[Fluentd]
    H --> L[Elasticsearch]
    H --> M[Kibana]

    %% Loki Details
    I --> N[Promtail]
    I --> O[Loki]
    I --> P[Grafana]

    %% Lightweight Alternatives
    J --> Q[File/S3 Storage]
    J --> R[Loki]
    J --> S[External/Cloud Solutions]

    %% Monitoring vs Logging
    B -.-> T[Use for Performance, Health, Alerts]
    C -.-> U[Use for Troubleshooting, Auditing, Compliance]

    %% User Actions
    E --> V[Query Metrics]
    F --> W[Get Alerts]
    M --> X[Query Logs]
    P --> Y[Query Logs]
    ZD --> V
    ZB --> W
    ZC --> V
    ZA --> ZC
    ZA --> ZB

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Prometheus stack and EFK stack serve different purposes when it comes to Kubernetes logging and monitoring:

---

Prometheus Stack

• Components: Prometheus (metrics collection), Alertmanager (alerts), Grafana (visualization).
• Main Focus: Metrics (CPU, memory, latency, request counts, error rates, etc.).
• Logging Support: Prometheus itself does not collect or store logs. It can scrape log-based metrics (e.g., via exporters or Loki), but it’s not a log aggregation solution.
• Use Case: Monitoring cluster and application health, performance, and alerting.

---

EFK Stack (Elasticsearch, Fluentd, Kibana)

• Components: Fluentd (log collector/forwarder), Elasticsearch (log indexing/storage), Kibana (log visualization/search).
• Main Focus: Log collection, aggregation, storage, and querying.
• Logging Support: Purpose-built for collecting application, system, and cluster logs.
• Use Case: Centralized log management, troubleshooting, search, compliance.

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Summary Table

Stack	Main Purpose	Logging Support	Metric Support	Visualization
Prometheus	Metrics/Monitoring	❌ (not for logs)	✅	Grafana
EFK	Log Aggregation/Search	✅	❌ (not for metrics)	Kibana

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Which is More Suitable for Log Collection?

• EFK stack is more suitable for log collection in a Kubernetes (including K3s) environment.
• If you want centralized, searchable logs, use EFK (or its alternatives: ELK, Loki, etc.).
• Prometheus stack is for metrics—not logs.