Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.
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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.
中文简介正在准备中。当前显示原文说明。
安装前可以查看交给 AI 代理的指令内容。
Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.
Configure Prometheus for comprehensive metric collection, alerting, and monitoring of infrastructure and applications.
┌──────────────┐
│ Applications │ ← Instrumented with client libraries
└──────┬───────┘
│ /metrics endpoint
↓
┌──────────────┐
│ Prometheus │ ← Scrapes metrics periodically
│ Server │
└──────┬───────┘
│
├─→ AlertManager (alerts)
├─→ Grafana (visualization)
└─→ Long-term storage (Thanos/Cortex)
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
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:
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
scrape_configs:
- job_name: 'static-targets'
static_configs:
- targets: ['host1:9100', 'host2:9100']
labels:
env: 'production'
region: 'us-west-2'
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"
}
}
]
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
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
# /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 }}%"
# 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
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'
assets/prometheus.yml.template - Complete configuration templatereferences/scrape-configs.md - Scrape configuration patternsreferences/recording-rules.md - Recording rule examplesscripts/validate-prometheus.sh - Validation scriptgrafana-dashboards - For visualizationslo-implementation - For SLO monitoringdistributed-tracing - For request tracing还没有评价。欢迎分享你的使用感受。
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Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.
中文简介正在准备中。当前显示原文说明。
ハイブリッドモード、段階的コンポーネント書き換え、依存性注入更新を使用してAngularJSからAngularへ移行します。AngularJSアプリケーションのアップグレード、フレームワーク移行の計画、またはレガシーAngularコードのモダナイゼーション時に使用します。
中文简介正在准备中。当前显示原文说明。
開発者を喜ばせる直感的でスケーラブルで保守可能なAPIを構築するために、RESTとGraphQL APIの設計原則をマスターします。新しいAPIの設計、API仕様のレビュー、またはAPI設計標準の確立時に使用してください。
中文简介正在准备中。当前显示原文说明。
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
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Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
中文简介正在准备中。当前显示原文说明。
クリーンアーキテクチャ、ヘキサゴナルアーキテクチャ、ドメイン駆動設計を含む実証済みのバックエンドアーキテクチャパターンを実装します。複雑なバックエンドシステムの設計や、保守性向上のための既存アプリケーションのリファクタリング時に使用します。
中文简介正在准备中。当前显示原文说明。