Skill

Automate Application Deployment with CI/CD

DEVOPS-DEPLOY takes an app from idea to production with ready Docker, AWS SAM/Lambda, Terraform, and GitHub Actions CI/CD templates.

Works with dockergithubawslambdaecs

91
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out of 100
Updated last month
Version 13.6.1

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Why it matters

Streamline your development lifecycle by automating application deployment from idea to production. This skill sets up robust CI/CD pipelines, containerizes your applications, and manages infrastructure as code for reliable and efficient releases.

Outcomes

What it gets done

01

Dockerize applications for consistent environments.

02

Configure CI/CD pipelines using GitHub Actions.

03

Deploy applications to AWS services like Lambda and ECS.

04

Implement infrastructure as code with Terraform.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-devops-deploy | bash

Overview

DEVOPS-DEPLOY - From Idea to Production

A DevOps skill for dockerizing apps and deploying them to AWS via SAM/Lambda, with ready Docker, Docker Compose, GitHub Actions, health check, and CloudWatch alerting templates plus a production readiness checklist. Use for Docker, CI/CD, AWS Lambda/SAM, Terraform, or monitoring setup tasks - not for general assistance or domains outside DevOps deployment.

What it does

DEVOPS-DEPLOY ("Da Ideia para Producao") is a critical-risk DevOps and deployment skill covering Docker, CI/CD with GitHub Actions, AWS Lambda, SAM, Terraform, infrastructure as code, and monitoring. It activates for tasks like dockerizing an application, configuring a CI/CD pipeline, deploying to AWS Lambda or ECS, setting up GitHub Actions or Terraform, planning rollbacks, blue-green deploys, health checks, or alerting.

It ships concrete, ready-to-use templates rather than abstract advice: a multi-stage Python Dockerfile with a non-root builder stage and a HEALTHCHECK directive, a Docker Compose file wiring an app service to Postgres and Redis for local development, a SAM template.yaml defining a serverless Lambda function backed by a pay-per-request DynamoDB table with TTL, and a GitHub Actions workflow that runs tests with coverage, security-scans the code with bandit and safety, and then builds and deploys via SAM on merge to main - including a Telegram notification step on successful deploy. It also provides a FastAPI /health endpoint returning uptime and version, and a CloudWatch alarm helper (via boto3) that pages on Lambda error thresholds.

Deploys run through the SAM CLI:

sam build
sam deploy --guided        # first time
sam deploy                 # subsequent deploys
sam deploy --no-confirm-changeset --no-fail-on-empty-changeset  # fast, no confirmation
sam logs -n AuriFunction --tail
sam delete

Before calling a deploy production-ready, the skill runs through a checklist: environment variables via Secrets Manager (never hardcoded), a responding health check endpoint, structured JSON logs with a request ID, rate limiting, CORS restricted to authorized domains, automatic DynamoDB backups, an appropriately sized Lambda timeout (10-30s), CloudWatch alarms for errors and latency, a documented rollback plan, and a load test before launch. It also exposes shorthand commands: /docker-setup, /sam-deploy, /ci-cd-setup, /monitoring-setup, /production-checklist, and /rollback.

When to use - and when NOT to

Use this skill for specialized DevOps and deployment work matching its domain - Docker, CI/CD, AWS Lambda/SAM, Terraform, or production monitoring. Do not use it for tasks unrelated to DevOps deployment, when a simpler and more specific tool can already handle the request, or when the user needs general-purpose assistance without domain-specific expertise. Review all suggestions before applying them to production code, provide clear and specific project context for accurate analysis, and combine it with complementary skills for a fuller picture rather than relying on it alone. Do not treat its output as a substitute for environment-specific validation, testing, or expert review, and stop to ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Who it's for

Backend and DevOps engineers deploying Python/FastAPI-based applications to AWS, particularly serverless Lambda workloads via SAM, who want a production checklist and working CI/CD, monitoring, and containerization templates rather than building them from scratch.

FAQ

Common questions

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