prometheus-configuration
Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Best use case
prometheus-configuration is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "prometheus-configuration" skill to help with this workflow task. Context: Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/prometheus-configuration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How prometheus-configuration Compares
| Feature / Agent | prometheus-configuration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Prometheus Configuration
Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.
## Do not use this skill when
- The task is unrelated to prometheus configuration
- You need a different domain or tool outside this scope
## 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`.
## Purpose
Configure Prometheus for comprehensive metric collection, alerting, and monitoring of infrastructure and applications.
## Use this skill when
- Set up Prometheus monitoring
- Configure metric scraping
- Create recording rules
- Design alert rules
- Implement service discovery
## Prometheus Architecture
```
┌──────────────┐
│ Applications │ ← Instrumented with client libraries
└──────┬───────┘
│ /metrics endpoint
↓
┌──────────────┐
│ Prometheus │ ← Scrapes metrics periodically
│ Server │
└──────┬───────┘
│
├─→ AlertManager (alerts)
├─→ Grafana (visualization)
└─→ Long-term storage (Thanos/Cortex)
```
## Installation
### Kubernetes with Helm
```bash
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
```yaml
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:
```
## Configuration File
**prometheus.yml:**
```yaml
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`
## Scrape Configurations
### Static Targets
```yaml
scrape_configs:
- job_name: 'static-targets'
static_configs:
- targets: ['host1:9100', 'host2:9100']
labels:
env: 'production'
region: 'us-west-2'
```
### File-based Service Discovery
```yaml
scrape_configs:
- job_name: 'file-sd'
file_sd_configs:
- files:
- /etc/prometheus/targets/*.json
- /etc/prometheus/targets/*.yml
refresh_interval: 5m
```
**targets/production.json:**
```json
[
{
"targets": ["app1:9090", "app2:9090"],
"labels": {
"env": "production",
"service": "api"
}
}
]
```
### Kubernetes Service Discovery
```yaml
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`
## Recording Rules
Create pre-computed metrics for frequently queried expressions:
```yaml
# /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`
## Alert Rules
```yaml
# /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 }}%"
```
## Validation
```bash
# 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`
## 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
**Check scrape targets:**
```bash
curl http://localhost:9090/api/v1/targets
```
**Check configuration:**
```bash
curl http://localhost:9090/api/v1/status/config
```
**Test query:**
```bash
curl 'http://localhost:9090/api/v1/query?query=up'
```
## 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
## Related Skills
- `grafana-dashboards` - For visualization
- `slo-implementation` - For SLO monitoring
- `distributed-tracing` - For request tracingRelated Skills
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