技能详情(站内镜像,无评论)
作者:Alireza Rezvani @alirezarezvani
许可证:MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本:v2.1.1
统计:⭐ 7 · 3.5k · 19 current installs · 19 all-time installs
⭐ 7
安装量(当前) 19
🛡 VirusTotal :良性 · OpenClaw :可疑
Package:alirezarezvani/senior-devops
安全扫描(ClawHub)
- VirusTotal :良性
- OpenClaw :可疑
OpenClaw 评估
The skill's description promises full cloud CI/CD and infra automation, but the included scripts are lightweight placeholders and the instructions/examples reference external cloud operations without requesting or implementing the credentials and tooling needed — this mismatch is concerning.
目的
The name/description claim comprehensive CI/CD, Terraform, and cloud deployments (AWS/GCP/Azure). However, the three included Python scripts are simple scaffolding/placeholders that only validate a path, produce an empty 'findings' list, and print a report — they do not implement Terraform, AWS/GCP/Azure SDK/CLI calls, container orchestration, or actual pipeline generation. The declared requirements list no cloud credentials or binaries (terra…
说明范围
SKILL.md instructs running the included scripts and provides examples that show terraform validate/plan, aws ecs update-service, Docker build/push, and Kubernetes blue/green deployment YAML. Those examples will require external CLIs/credentials in practice, but the runtime instructions do not request those env vars or explain prerequisites. The README examples could mislead users into thinking the scripts perform those actions when the current…
安装机制
No install spec is present and the skill is instruction-only with bundled scripts and docs. Nothing will be downloaded from external URLs during install, so there is low install-time risk. The included Python files are local and human-readable.
证书
The skill declares no required environment variables or primary credential despite providing examples that would normally require AWS/GCP/Azure credentials and CLI tools. This omission is an inconsistency: a legitimate DevOps skill that performs cloud operations would normally require and document credentials and local tooling prerequisites.
持久
The skill is not force-included (always:false) and does not request persistent system-wide privileges. It does not modify other skills' configs or request elevated presence. Autonomous invocation remains enabled by default (normal), but there are no additional privilege requests.
安装(复制给龙虾 AI)
将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「Senior Devops」。简介:Comprehensive DevOps skill for CI/CD, infrastructure automation, containerizati…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/alirezarezvani/senior-devops/SKILL.md
(来源:yingzhi8.cn 技能库)
SKILL.md
---
name: "senior-devops"
description: Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.
---
# Senior Devops
Complete toolkit for senior devops with modern tools and best practices.
## Quick Start
### Main Capabilities
This skill provides three core capabilities through automated scripts:
```bash
# Script 1: Pipeline Generator — scaffolds CI/CD pipelines for GitHub Actions or CircleCI
python scripts/pipeline_generator.py ./app --platform=github --stages=build,test,deploy
# Script 2: Terraform Scaffolder — generates and validates IaC modules for AWS/GCP/Azure
python scripts/terraform_scaffolder.py ./infra --provider=aws --module=ecs-service --verbose
# Script 3: Deployment Manager — orchestrates container deployments with rollback support
python scripts/deployment_manager.py deploy --env=production --image=app:1.2.3 --strategy=blue-green
```
## Core Capabilities
### 1. Pipeline Generator
Scaffolds CI/CD pipeline configurations for GitHub Actions or CircleCI, with stages for build, test, security scan, and deploy.
**Example — GitHub Actions workflow:**
```yaml
# .github/workflows/ci.yml
name: CI/CD Pipeline
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: '20'
cache: 'npm'
- run: npm ci
- run: npm run lint
- run: npm test -- --coverage
- name: Upload coverage
uses: codecov/codecov-action@v4
build-docker:
needs: build-and-test
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Build and push image
uses: docker/build-push-action@v5
with:
push: ${{ github.ref == 'refs/heads/main' }}
tags: ghcr.io/${{ github.repository }}:${{ github.sha }}
deploy:
needs: build-docker
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
steps:
- name: Deploy to ECS
run: |
aws ecs update-service
--cluster production
--service app-service
--force-new-deployment
```
**Usage:**
```bash
python scripts/pipeline_generator.py <project-path> --platform=github|circleci --stages=build,test,deploy
```
### 2. Terraform Scaffolder
Generates, validates, and plans Terraform modules. Enforces consistent module structure and runs `terraform validate` + `terraform plan` before any apply.
**Example — AWS ECS service module:**
```hcl
# modules/ecs-service/main.tf
resource "aws_ecs_task_definition" "app" {
family = var.service_name
requires_compatibilities = ["FARGATE"]
network_mode = "awsvpc"
cpu = var.cpu
memory = var.memory
container_definitions = jsonencode([{
name = var.service_name
image = var.container_image
essential = true
portMappings = [{
containerPort = var.container_port
protocol = "tcp"
}]
environment = [for k, v in var.env_vars : { name = k, value = v }]
logConfiguration = {
logDriver = "awslogs"
options = {
awslogs-group = "/ecs/${var.service_name}"
awslogs-region = var.aws_region
awslogs-stream-prefix = "ecs"
}
}
}])
}
resource "aws_ecs_service" "app" {
name = var.service_name
cluster = var.cluster_id
task_definition = aws_ecs_task_definition.app.arn
desired_count = var.desired_count
launch_type = "FARGATE"
network_configuration {
subnets = var.private_subnet_ids
security_groups = [aws_security_group.app.id]
assign_public_ip = false
}
load_balancer {
target_group_arn = aws_lb_target_group.app.arn
container_name = var.service_name
container_port = var.container_port
}
}
```
**Usage:**
```bash
python scripts/terraform_scaffolder.py <target-path> --provider=aws|gcp|azure --module=ecs-service|gke-deployment|aks-service [--verbose]
```
### 3. Deployment Manager
Orchestrates deployments with blue/green or rolling strategies, health-check gates, and automatic rollback on failure.
**Example — Kubernetes blue/green deployment (blue-slot specific elements):**
```yaml
# k8s/deployment-blue.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: app-blue
labels:
app: myapp
slot: blue # slot label distinguishes blue from green
spec:
replicas: 3
selector:
matchLabels:
app: myapp
slot: blue
template:
metadata:
labels:
app: myapp
slot: blue
spec:
containers:
- name: app
image: ghcr.io/org/app:1.2.3
readinessProbe: # gate: pod must pass before traffic switches
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 10
periodSeconds: 5
resources:
requests:
cpu: "250m"
memory: "256Mi"
limits:
cpu: "500m"
memory: "512Mi"
```
**Usage:**
```bash
python scripts/deployment_manager.py deploy
--env=staging|production
--image=app:1.2.3
--strategy=blue-green|rolling
--health-check-url=https://app.example.com/healthz
python scripts/deployment_manager.py rollback --env=production --to-version=1.2.2
python scripts/deployment_manager.py --analyze --env=production # audit current state
```
## Resources
- Pattern Reference: `references/cicd_pipeline_guide.md` — detailed CI/CD patterns, best practices, anti-patterns
- Workflow Guide: `references/infrastructure_as_code.md` — IaC step-by-step processes, optimization, troubleshooting
- Technical Guide: `references/deployment_strategies.md` — deployment strategy configs, security considerations, scalability
- Tool Scripts: `scripts/` directory
## Development Workflow
### 1. Infrastructure Changes (Terraform)
```bash
# Scaffold or update module
python scripts/terraform_scaffolder.py ./infra --provider=aws --module=ecs-service --verbose
# Validate and plan — review diff before applying
terraform -chdir=infra init
terraform -chdir=infra validate
terraform -chdir=infra plan -out=tfplan
# Apply only after plan review
terraform -chdir=infra apply tfplan
# Verify resources are healthy
aws ecs describe-services --cluster production --services app-service
--query 'services[0].{Status:status,Running:runningCount,Desired:desiredCount}'
```
### 2. Application Deployment
```bash
# Generate or update pipeline config
python scripts/pipeline_generator.py . --platform=github --stages=build,test,security,deploy
# Build and tag image
docker build -t ghcr.io/org/app:$(git rev-parse --short HEAD) .
docker push ghcr.io/org/app:$(git rev-parse --short HEAD)
# Deploy with health-check gate
python scripts/deployment_manager.py deploy
--env=production
--image=app:$(git rev-parse --short HEAD)
--strategy=blue-green
--health-check-url=https://app.example.com/healthz
# Verify pods are running
kubectl get pods -n production -l app=myapp
kubectl rollout status deployment/app-blue -n production
# Switch traffic after verification
kubectl patch service app-svc -n production
-p '{"spec":{"selector":{"slot":"blue"}}}'
```
### 3. Rollback Procedure
```bash
# Immediate rollback via deployment manager
python scripts/deployment_manager.py rollback --env=production --to-version=1.2.2
# Or via kubectl
kubectl rollout undo deployment/app -n production
kubectl rollout status deployment/app -n production
# Verify rollback succeeded
kubectl get pods -n production -l app=myapp
curl -sf https://app.example.com/healthz || echo "ROLLBACK FAILED — escalate"
```
## Troubleshooting
Check the comprehensive troubleshooting section in `references/deployment_strategies.md`.