MR
Mayur Rathi
@sickn33
⭐ 47.3k GitHub stars

loki-logging

loki-logging is an engineering AI skill with a core value of Configure Grafana Loki for log aggregation and analysis. It helps developers solve real-world problems in the engineering domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

Configure Grafana Loki for log aggregation and analysis.

Last verified on: 2026-10-06

Quick Facts

Category engineering
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 47.3k
Last Verified 2026-10-06
Risk Level Low
mkdir -p ./skills/loki-logging && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/loki-logging/SKILL.md -o ./skills/loki-logging/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Grafana Loki


Aggregate and query logs with Grafana Loki, the Prometheus-inspired logging system.


When to Use This Skill


Use this skill when:

- Implementing cost-effective log aggregation

- Building logging for Kubernetes environments

- Integrating logs with Grafana dashboards

- Querying logs with label-based filtering

- Preferring lighter-weight alternative to ELK


Prerequisites


- Docker or Kubernetes

- Grafana for visualization

- Promtail or other log shipper


Architecture Overview


text 
┌─────────────┐     ┌──────────┐     ┌──────────┐
│ Application │────▶│ Promtail │────▶│   Loki   │
└─────────────┘     └──────────┘     └──────────┘
                                          │
                                          ▼
                                     ┌──────────┐
                                     │ Grafana  │
                                     └──────────┘

Docker Deployment


yaml 
# docker-compose.yml
version: '3.8'

services:
  loki:
    image: grafana/loki:2.9.0
    ports:
      - "3100:3100"
    volumes:
      - ./loki-config.yaml:/etc/loki/local-config.yaml
      - loki-data:/loki
    command: -config.file=/etc/loki/local-config.yaml

  promtail:
    image: grafana/promtail:2.9.0
    volumes:
      - ./promtail-config.yaml:/etc/promtail/config.yaml
      - /var/log:/var/log:ro
      - /var/lib/docker/containers:/var/lib/docker/containers:ro
    command: -config.file=/etc/promtail/config.yaml

  grafana:
    image: grafana/grafana:10.2.0
    ports:
      - "3000:3000"
    volumes:
      - grafana-data:/var/lib/grafana
      - ./grafana/provisioning:/etc/grafana/provisioning
    environment:
      - GF_AUTH_ANONYMOUS_ENABLED=true
      - GF_AUTH_ANONYMOUS_ORG_ROLE=Admin

volumes:
  loki-data:
  grafana-data:

Loki Configuration


yaml 
# loki-config.yaml
auth_enabled: false

server:
  http_listen_port: 3100

common:
  path_prefix: /loki
  storage:
    filesystem:
      chunks_directory: /loki/chunks
      rules_directory: /loki/rules
  replication_factor: 1
  ring:
    kvstore:
      store: inmemory

schema_config:
  configs:
    - from: 2020-10-24
      store: boltdb-shipper
      object_store: filesystem
      schema: v11
      index:
        prefix: index_
        period: 24h

storage_config:
  boltdb_shipper:
    active_index_directory: /loki/index
    cache_location: /loki/cache
    shared_store: filesystem

limits_config:
  reject_old_samples: true
  reject_old_samples_max_age: 168h
  max_query_series: 5000
  max_query_parallelism: 2

chunk_store_config:
  max_look_back_period: 168h

table_manager:
  retention_deletes_enabled: true
  retention_period: 168h

Promtail Configuration


yaml 
# promtail-config.yaml
server:
  http_listen_port: 9080
  grpc_listen_port: 0

positions:
  filename: /tmp/positions.yaml

clients:
  - url: http://loki:3100/loki/api/v1/push

scrape_configs:
  # System logs
  - job_name: system
    static_configs:
      - targets:
          - localhost
        labels:
          job: varlogs
          __path__: /var/log/*.log

  # Docker container logs
  - job_name: docker
    docker_sd_configs:
      - host: unix:///var/run/docker.sock
        refresh_interval: 5s
    relabel_configs:
      - source_labels: ['__meta_docker_container_name']
        regex: '/(.*)'
        target_label: 'container'
      - source_labels: ['__meta_docker_container_log_stream']
        target_label: 'stream'

  # Application logs with parsing
  - job_name: application
    static_configs:
      - targets:
          - localhost
        labels:
          job: application
          __path__: /var/log/app/*.log
    pipeline_stages:
      - json:
          expressions:
            level: level
            message: message
            timestamp: timestamp
      - labels:
          level:
      - timestamp:
          source: timestamp
          format: RFC3339

Kubernetes Deployment


bash 
# Using Helm
helm repo add grafana https://grafana.github.io/helm-charts
helm ins

🎯 Best For

  • Claude users
  • AI users

💡 Use Cases

  • Using loki-logging in daily workflow
  • Automating repetitive engineering tasks

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply loki-logging to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install loki-logging?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/loki-logging/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Not reading the full skill

Skills contain important context and edge cases beyond the quick start.

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