sickn33/antigravity-awesome-skills/devops-deploy

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DevOps e deploy de aplicacoes — Docker, CI/CD com GitHub Actions, AWS Lambda, SAM, Terraform, infraestrutura como codigo e monitoramento.

Install

npx vskill@latest install sickn33/antigravity-awesome-skills/devops-deploy

SKILL.md

DEVOPS-DEPLOY — Da Ideia para Producao

Overview

DevOps e deploy de aplicacoes — Docker, CI/CD com GitHub Actions, AWS Lambda, SAM, Terraform, infraestrutura como codigo e monitoramento. Ativar para: dockerizar aplicacao, configurar pipeline CI/CD, deploy na AWS, Lambda, ECS, configurar GitHub Actions, Terraform, rollback, blue-green deploy, health checks, alertas.

When to Use This Skill

  • When you need specialized assistance with this domain

Do Not Use This Skill When

  • The task is unrelated to devops deploy
  • A simpler, more specific tool can handle the request
  • The user needs general-purpose assistance without domain expertise

Limites de execucao

Os exemplos alteram infraestrutura paga e podem publicar ou apagar recursos. Confirmar conta, regiao, stack, custos e rollback antes de executar. Notificacoes Telegram exigem autorizacao explicita; retirar esse passo quando nao solicitado. Scripts e arquivos da aplicacao nao estao incluidos; fixar versoes e revisar o plano antes de qualquer deploy sem confirmacao.

How It Works

"Move fast and don't break things." — Engenharia de elite nao e lenta.
E rapida e confiavel ao mesmo tempo.

Dockerfile Otimizado (Python)

dockerfile
FROM python:3.11-slim AS builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir --user -r requirements.txt
FROM python:3.11-slim
WORKDIR /app
COPY --from=builder /root/.local /root/.local
COPY . .
ENV PATH=/root/.local/bin:$PATH
ENV PYTHONUNBUFFERED=1
EXPOSE 8000
HEALTHCHECK --interval=30s --timeout=3s CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health', timeout=2)" || exit 1
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

Docker Compose (Dev Local)

yaml
version: "3.9"
services:
app:
build: .
ports: ["8000:8000"]
environment:
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
volumes:
- .:/app
depends_on: [db, redis]
db:
image: postgres:15
environment:
POSTGRES_DB: auri
POSTGRES_USER: auri
POSTGRES_PASSWORD: ${DB_PASSWORD}
volumes:
- pgdata:/var/lib/postgresql/data
redis:
image: redis:7-alpine
volumes:
pgdata:

Sam Template (Serverless)

yaml
## Template.Yaml
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Globals:
Function:
Timeout: 30
Runtime: python3.11
Environment:
Variables:
ANTHROPIC_API_KEY: !Ref AnthropicApiKey
DYNAMODB_TABLE: !Ref AuriTable
Parameters:
AnthropicApiKey:
Type: String
NoEcho: true
Resources:
AuriFunction:
Type: AWS::Serverless::Function
Properties:
CodeUri: src/
Handler: lambda_function.handler
MemorySize: 512
Policies:
- DynamoDBCrudPolicy:
TableName: !Ref AuriTable
AuriTable:
Type: AWS::DynamoDB::Table
Properties:
TableName: auri-users
BillingMode: PAY_PER_REQUEST
AttributeDefinitions:
- AttributeName: userId
AttributeType: S
KeySchema:
- AttributeName: userId
KeyType: HASH
TimeToLiveSpecification:
AttributeName: ttl
Enabled: true

Deploy Commands

bash
## Build E Deploy
sam build
sam deploy --guided # primeira vez
sam deploy # deploys seguintes
## Deploy Rapido (Sem Confirmacao)
sam deploy --no-confirm-changeset --no-fail-on-empty-changeset
## Ver Logs Em Tempo Real
sam logs -n AuriFunction --tail
## Deletar Stack
sam delete

.Github/Workflows/Deploy.Yml

yaml
name: Deploy Auri
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with: { python-version: "3.11" }
- run: pip install -r requirements.txt
- run: pytest tests/ -v --cov=src --cov-report=xml
- uses: codecov/codecov-action@v4
security:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- run: pip install bandit safety
- run: bandit -r src/ -ll
- run: safety check -r requirements.txt
deploy:
needs: [test, security]
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: aws-actions/setup-sam@v2
- uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-east-1
- run: sam build
- run: sam deploy --no-confirm-changeset
- name: Notify Telegram on Success
run: |
curl -s -X POST "https://api.telegram.org/bot${{ secrets.TELEGRAM_BOT_TOKEN }}/sendMessage" \
-d "chat_id=${{ secrets.TELEGRAM_CHAT_ID }}" \
-d "text=Auri deployed successfully! Commit: ${{ github.sha }}"

Health Check Endpoint

python
from fastapi import FastAPI
import time, os
app = FastAPI()
START_TIME = time.time()
@app.get("/health")
async def health():
return {
"status": "healthy",
"uptime_seconds": time.time() - START_TIME,
"version": os.environ.get("APP_VERSION", "unknown"),
"environment": os.environ.get("ENV", "production")
}

Alertas Cloudwatch

python
import boto3
def create_error_alarm(function_name: str, sns_topic_arn: str):
cw = boto3.client("cloudwatch")
cw.put_metric_alarm(
AlarmName=f"{function_name}-errors",
MetricName="Errors",
Namespace="AWS/Lambda",
Dimensions=[{"Name": "FunctionName", "Value": function_name}],
Period=300,
EvaluationPeriods=1,
Statistic="Sum",
Threshold=5,
ComparisonOperator="GreaterThanThreshold",
AlarmActions=[sns_topic_arn],
TreatMissingData="notBreaching"
)

5. Checklist De Producao

  • [ ] Variaveis de ambiente via Secrets Manager (nunca hardcoded)
  • [ ] Health check endpoint respondendo
  • [ ] Logs estruturados (JSON) com request_id
  • [ ] Rate limiting configurado
  • [ ] CORS restrito a dominios autorizados
  • [ ] DynamoDB com backup automatico ativado
  • [ ] Lambda com timeout adequado (10-30s)
  • [ ] CloudWatch alarmes para erros e latencia
  • [ ] Rollback plan documentado
  • [ ] Load test antes do lancamento

6. Comandos

ComandoAcao
/docker-setupDockeriza a aplicacao
/sam-deployDeploy completo na AWS Lambda
/ci-cd-setupConfigura GitHub Actions pipeline
/monitoring-setupConfigura CloudWatch e alertas
/production-checklistRoda checklist pre-lancamento
/rollbackPlano de rollback para versao anterior

Best Practices

  • Provide clear, specific context about your project and requirements
  • Review all suggestions before applying them to production code
  • Combine with other complementary skills for comprehensive analysis

Common Pitfalls

  • Using this skill for tasks outside its domain expertise
  • Applying recommendations without understanding your specific context
  • Not providing enough project context for accurate analysis

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.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
24,155
Repository forks
4,155
Repository npm downloads, 7 days
11,772
7-day trend score
72

Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 19 Mar 2026, 7 months ago.

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