Prometheus Configuration V2

Prometheus Configuration

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/prometheus-configuration from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Prometheus Configuration Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Purpose, Prometheus Architecture, Configuration File, Scrape Configurations, Validation, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• The task is unrelated to prometheus configuration
• You need a different domain or tool outside this scope
• Set up Prometheus monitoring
• Configure metric scraping
• Create recording rules
• Design alert rules

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Clarify goals, constraints, and required inputs.
2. Apply relevant best practices and validate outcomes.
3. Provide actionable steps and verification.
4. If detailed examples are required, open resources/implementation-playbook.md.
5. "9090:9090"
6. ./prometheus.yml:/etc/prometheus/prometheus.yml
7. prometheus-data:/prometheus

Imported Workflow Notes

Imported: Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

Imported: Installation

Kubernetes with Helm

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm repo update

helm install prometheus prometheus-community/kube-prometheus-stack \
  --namespace monitoring \
  --create-namespace \
  --set prometheus.prometheusSpec.retention=30d \
  --set prometheus.prometheusSpec.storageVolumeSize=50Gi

Docker Compose

version: '3.8'
services:
  prometheus:
    image: prom/prometheus:latest
    ports:
      - "9090:9090"
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
      - prometheus-data:/prometheus
    command:
      - '--config.file=/etc/prometheus/prometheus.yml'
      - '--storage.tsdb.path=/prometheus'
      - '--storage.tsdb.retention.time=30d'

volumes:
  prometheus-data:

Imported: Purpose

Configure Prometheus for comprehensive metric collection, alerting, and monitoring of infrastructure and applications.

Examples

Example 1: Ask for the upstream workflow directly

Use @prometheus-configuration-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @prometheus-configuration-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @prometheus-configuration-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @prometheus-configuration-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• name: api_metrics
• record: job:http_requests:rate5m
• record: job:httprequestserrors:rate5m
• record: job:httprequestserror_rate:percentage
• record: job:httprequestduration:p95
• name: resource_metrics
• record: instance:node_cpu:utilization

Imported Operating Notes

Imported: Recording Rules

Create pre-computed metrics for frequently queried expressions:

# /etc/prometheus/rules/recording_rules.yml
groups:
  - name: api_metrics
    interval: 15s
    rules:
      # HTTP request rate per service
      - record: job:http_requests:rate5m
        expr: sum by (job) (rate(http_requests_total[5m]))

      # Error rate percentage
      - record: job:http_requests_errors:rate5m
        expr: sum by (job) (rate(http_requests_total{status=~"5.."}[5m]))

      - record: job:http_requests_error_rate:percentage
        expr: |
          (job:http_requests_errors:rate5m / job:http_requests:rate5m) * 100

      # P95 latency
      - record: job:http_request_duration:p95
        expr: |
          histogram_quantile(0.95,
            sum by (job, le) (rate(http_request_duration_seconds_bucket[5m]))
          )

  - name: resource_metrics
    interval: 30s
    rules:
      # CPU utilization percentage
      - record: instance:node_cpu:utilization
        expr: |
          100 - (avg by (instance) (rate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)

      # Memory utilization percentage
      - record: instance:node_memory:utilization
        expr: |
          100 - ((node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes) * 100)

      # Disk usage percentage
      - record: instance:node_disk:utilization
        expr: |
          100 - ((node_filesystem_avail_bytes / node_filesystem_size_bytes) * 100)

Reference: See references/recording-rules.md

Imported: Alert Rules

# /etc/prometheus/rules/alert_rules.yml
groups:
  - name: availability
    interval: 30s
    rules:
      - alert: ServiceDown
        expr: up{job="my-app"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Service {{ $labels.instance }} is down"
          description: "{{ $labels.job }} has been down for more than 1 minute"

      - alert: HighErrorRate
        expr: job:http_requests_error_rate:percentage > 5
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "High error rate for {{ $labels.job }}"
          description: "Error rate is {{ $value }}% (threshold: 5%)"

      - alert: HighLatency
        expr: job:http_request_duration:p95 > 1
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "High latency for {{ $labels.job }}"
          description: "P95 latency is {{ $value }}s (threshold: 1s)"

  - name: resources
    interval: 1m
    rules:
      - alert: HighCPUUsage
        expr: instance:node_cpu:utilization > 80
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "High CPU usage on {{ $labels.instance }}"
          description: "CPU usage is {{ $value }}%"

      - alert: HighMemoryUsage
        expr: instance:node_memory:utilization > 85
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "High memory usage on {{ $labels.instance }}"
          description: "Memory usage is {{ $value }}%"

      - alert: DiskSpaceLow
        expr: instance:node_disk:utilization > 90
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "Low disk space on {{ $labels.instance }}"
          description: "Disk usage is {{ $value }}%"

Imported: Best Practices

1. Use consistent naming for metrics (prefix_name_unit)
2. Set appropriate scrape intervals (15-60s typical)
3. Use recording rules for expensive queries
4. Implement high availability (multiple Prometheus instances)
5. Configure retention based on storage capacity
6. Use relabeling for metric cleanup
7. Monitor Prometheus itself
8. Implement federation for large deployments
9. Use Thanos/Cortex for long-term storage
10. Document custom metrics

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/prometheus-configuration, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Imported Troubleshooting Notes

Imported: Troubleshooting

Check scrape targets:

curl http://localhost:9090/api/v1/targets

Check configuration:

curl http://localhost:9090/api/v1/status/config

Test query:

curl 'http://localhost:9090/api/v1/query?query=up'

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Reference Files

• assets/prometheus.yml.template - Complete configuration template
• references/scrape-configs.md - Scrape configuration patterns
• references/recording-rules.md - Recording rule examples
• scripts/validate-prometheus.sh - Validation script

Imported: Prometheus Architecture

┌──────────────┐
│ Applications │ ← Instrumented with client libraries
└──────┬───────┘
       │ /metrics endpoint
       ↓
┌──────────────┐
│  Prometheus  │ ← Scrapes metrics periodically
│    Server    │
└──────┬───────┘
       │
       ├─→ AlertManager (alerts)
       ├─→ Grafana (visualization)
       └─→ Long-term storage (Thanos/Cortex)

Imported: Configuration File

prometheus.yml:

global:
  scrape_interval: 15s
  evaluation_interval: 15s
  external_labels:
    cluster: 'production'
    region: 'us-west-2'

# Alertmanager configuration
alerting:
  alertmanagers:
    - static_configs:
        - targets:
          - alertmanager:9093

# Load rules files
rule_files:
  - /etc/prometheus/rules/*.yml

# Scrape configurations
scrape_configs:
  # Prometheus itself
  - job_name: 'prometheus'
    static_configs:
      - targets: ['localhost:9090']

  # Node exporters
  - job_name: 'node-exporter'
    static_configs:
      - targets:
        - 'node1:9100'
        - 'node2:9100'
        - 'node3:9100'
    relabel_configs:
      - source_labels: [__address__]
        target_label: instance
        regex: '([^:]+)(:[0-9]+)?'
        replacement: '${1}'

  # Kubernetes pods with annotations
  - job_name: 'kubernetes-pods'
    kubernetes_sd_configs:
      - role: pod
    relabel_configs:
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
        action: replace
        target_label: __metrics_path__
        regex: (.+)
      - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
        action: replace
        regex: ([^:]+)(?::\d+)?;(\d+)
        replacement: $1:$2
        target_label: __address__
      - source_labels: [__meta_kubernetes_namespace]
        action: replace
        target_label: namespace
      - source_labels: [__meta_kubernetes_pod_name]
        action: replace
        target_label: pod

  # Application metrics
  - job_name: 'my-app'
    static_configs:
      - targets:
        - 'app1.example.com:9090'
        - 'app2.example.com:9090'
    metrics_path: '/metrics'
    scheme: 'https'
    tls_config:
      ca_file: /etc/prometheus/ca.crt
      cert_file: /etc/prometheus/client.crt
      key_file: /etc/prometheus/client.key

Reference: See assets/prometheus.yml.template

Imported: Scrape Configurations

Static Targets

scrape_configs:
  - job_name: 'static-targets'
    static_configs:
      - targets: ['host1:9100', 'host2:9100']
        labels:
          env: 'production'
          region: 'us-west-2'

File-based Service Discovery

scrape_configs:
  - job_name: 'file-sd'
    file_sd_configs:
      - files:
        - /etc/prometheus/targets/*.json
        - /etc/prometheus/targets/*.yml
        refresh_interval: 5m

targets/production.json:

[
  {
    "targets": ["app1:9090", "app2:9090"],
    "labels": {
      "env": "production",
      "service": "api"
    }
  }
]

Kubernetes Service Discovery

scrape_configs:
  - job_name: 'kubernetes-services'
    kubernetes_sd_configs:
      - role: service
    relabel_configs:
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
        action: replace
        target_label: __scheme__
        regex: (https?)
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
        action: replace
        target_label: __metrics_path__
        regex: (.+)

Reference: See references/scrape-configs.md

Imported: Validation

# Validate configuration
promtool check config prometheus.yml

# Validate rules
promtool check rules /etc/prometheus/rules/*.yml

# Test query
promtool query instant http://localhost:9090 'up'

Reference: See scripts/validate-prometheus.sh

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.