Execute qualquer Skill no Manus
com um clique

Execute qualquer Skill no Manus com um clique

Começar

deploy-backend

Estrelas3

Forks0

Atualizado14 de abril de 2026 às 13:01

Deploy do backend Django para Cloud Run (GCP). Usar quando precisar publicar mudancas da API em producao.

Instalação

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

Executar no Manus

Fonte

suportly

suportly/ai-augmented-developer

Abrir repositório GitHub Ver repositórios do creator

Download

Executar no Manus

Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Administradores de redes e sistemas de computadorInformática e Matemática·SOC 15-1244

SKILL.md

readonly

name	deploy-backend
description	Deploy do backend Django para Cloud Run (GCP). Usar quando precisar publicar mudancas da API em producao.
disable-model-invocation	true
allowed-tools	Bash, Read, Grep

Deploy Backend (Cloud Run)

Deploy do {{BACKEND_DIR}} para o Cloud Run na GCP.

Pre-requisitos

Docker rodando localmente
gcloud autenticado (gcloud auth login)
Credenciais de Docker configuradas (gcloud auth configure-docker {{GCP_REGION}}-docker.pkg.dev)

Passos

Verificar mudancas pendentes:
```
cd {{BACKEND_DIR}} && git status
```
- Se houver mudancas nao commitadas, avisar o usuario
Verificar se ha migrations pendentes:
```
cd {{BACKEND_DIR}} && source venv/bin/activate && python manage.py showmigrations | grep "\[ \]"
```
- Se houver migrations nao aplicadas, avisar (precisam ser aplicadas no Cloud SQL tambem)

Build da imagem Docker:

cd {{BACKEND_DIR}}
IMAGE="{{GCP_REGION}}-docker.pkg.dev/{{GCP_PROJECT}}/{{ARTIFACT_REPO}}/{{BACKEND_SERVICE}}:latest"
docker build -f Dockerfile.cloudrun -t $IMAGE .

Push para Artifact Registry:
```
docker push $IMAGE
```

Deploy no Cloud Run:

gcloud run deploy {{BACKEND_SERVICE}} \
  --image $IMAGE \
  --region {{GCP_REGION}} \
  --platform managed \
  --allow-unauthenticated \
  --min-instances 1 \
  --max-instances 10 \
  --memory 1Gi \
  --cpu 1 \
  --timeout 3600 \
  --concurrency 80 \
  --no-cpu-throttling

Verificar deploy:

gcloud run services describe {{BACKEND_SERVICE}} --region {{GCP_REGION}} --format="value(status.url)"

CRITICO

SEMPRE usar --memory 1Gi — 512Mi causa OOM em producao
URL de producao: https://{{PROD_API_URL}}
Cloud SQL: {{GCP_PROJECT}}:us-central1:{{CLOUD_SQL_INSTANCE}}

Mais deste repositório

mesmo repositório

analyze

suportly/ai-augmented-developer

Check for drift between spec.md, plan.md, tasks.md, and the actual code. Reports the gaps; does not fix them.

2026-07-193

checklist

suportly/ai-augmented-developer

Run a category-specific quality pass (security / performance / accessibility / i18n / privacy / observability) against the current plan and code.

2026-07-083

clarify

suportly/ai-augmented-developer

Surface [NEEDS CLARIFICATION] markers in spec.md (or plan.md) to the user, one at a time, and edit the file with the answers.

2026-07-083

constitution

suportly/ai-augmented-developer

Bootstrap or amend constitution.md (framework, preset, or project). Inspects existing project context first; enforces the amendment process: issue first, one article per PR, reviewer non-author.

2026-07-083

help

suportly/ai-augmented-developer

Print the pipeline quick-reference — a one-screen summary of every /aia:* command and its hand-offs, prefixed by a state-aware "Próximo passo" line.

2026-07-083

implement

suportly/ai-augmented-developer

Execute an approved plan + tasks list by dispatching one fresh subagent per task and applying two-stage review (spec compliance, then code quality) before moving on.

2026-07-083

name	deploy-backend
description	Deploy do backend Django para Cloud Run (GCP). Usar quando precisar publicar mudancas da API em producao.
disable-model-invocation	true
allowed-tools	Bash, Read, Grep

Deploy Backend (Cloud Run)

Deploy do {{BACKEND_DIR}} para o Cloud Run na GCP.

Pre-requisitos

Docker rodando localmente
gcloud autenticado (gcloud auth login)
Credenciais de Docker configuradas (gcloud auth configure-docker {{GCP_REGION}}-docker.pkg.dev)

Passos

Verificar mudancas pendentes:
```
cd {{BACKEND_DIR}} && git status
```
- Se houver mudancas nao commitadas, avisar o usuario
Verificar se ha migrations pendentes:
```
cd {{BACKEND_DIR}} && source venv/bin/activate && python manage.py showmigrations | grep "\[ \]"
```
- Se houver migrations nao aplicadas, avisar (precisam ser aplicadas no Cloud SQL tambem)

Build da imagem Docker:

cd {{BACKEND_DIR}}
IMAGE="{{GCP_REGION}}-docker.pkg.dev/{{GCP_PROJECT}}/{{ARTIFACT_REPO}}/{{BACKEND_SERVICE}}:latest"
docker build -f Dockerfile.cloudrun -t $IMAGE .

Push para Artifact Registry:
```
docker push $IMAGE
```

Deploy no Cloud Run:

gcloud run deploy {{BACKEND_SERVICE}} \
  --image $IMAGE \
  --region {{GCP_REGION}} \
  --platform managed \
  --allow-unauthenticated \
  --min-instances 1 \
  --max-instances 10 \
  --memory 1Gi \
  --cpu 1 \
  --timeout 3600 \
  --concurrency 80 \
  --no-cpu-throttling

Verificar deploy:

gcloud run services describe {{BACKEND_SERVICE}} --region {{GCP_REGION}} --format="value(status.url)"

CRITICO

SEMPRE usar --memory 1Gi — 512Mi causa OOM em producao
URL de producao: https://{{PROD_API_URL}}
Cloud SQL: {{GCP_PROJECT}}:us-central1:{{CLOUD_SQL_INSTANCE}}