Module 30 Professional Engineering

DevOps and Deployment

Many developers have a strange relationship with deployment: they fear it. Every production push is an anxious moment because they don't fully understand what happens between git push and users seeing the new code. They don't know what Docker is actually doing, why the CI pipeline is configured the way it is, or what to do when a deployment goes wrong. This fear is the direct result of treating deployment as a black box — and it's fixable by understanding the pipeline from the inside out. This module takes you through the complete deployment lifecycle. You'll understand containers from first principles — why they exist, what they actually isolate, and why they're not virtual machines. You'll build CI/CD pipelines that test, build, and deploy automatically, with enough understanding to debug pipeline failures and configure new steps. You'll write infrastructure as code with Terraform to make environments reproducible and changes reviewable. You'll understand the major cloud providers' core services — not to become a cloud architect but to make informed choices about compute, storage, databases, queues, and networking. And you'll understand monitoring, alerting, and incident response as engineering disciplines — not as tools you configure and forget, but as practices that determine how quickly you detect and recover from failures.

What You'll Learn

  • 1
    Containers — Docker from first principles, why containers exist
  • 2
    CI/CD — Automated testing, building, and deployment pipelines
  • 3
    Infrastructure as Code — Terraform, CloudFormation, reproducible infrastructure
  • 4
    Monitoring and Alerting — What to monitor, how to set thresholds
  • 5
    Incident Response — On-call, postmortems, blameless culture
  • 6
    Cloud Architecture — AWS/GCP/Azure core services and when to use each

Capstone Project: Full Deployment Pipeline

Build a complete deployment pipeline for an existing application — Dockerizing it with a multi-stage build that produces a minimal production image, configuring a GitHub Actions CI/CD pipeline that runs tests and deploys on merge to main, writing Terraform configuration for the cloud infrastructure, and setting up monitoring with alerts for the key SLIs. Simulate a production incident and practice the response process including postmortem.

Why This Matters for Your Career

DevOps is not a team — it's a culture that says the engineers who build software should also own it in production. Engineers who understand the full deployment pipeline are more empathetic to operational concerns, write more operationally sound code, and can contribute to deployment discussions rather than handing off and hoping. The trend toward platform engineering and developer self-service makes this knowledge increasingly essential for every engineer, not just specialists. Containers have become the standard unit of deployment for good reason: they make environments reproducible, dependencies explicit, and deployment artifacts consistent across development and production. Engineers who understand Docker well enough to write efficient Dockerfiles, debug container startup issues, and reason about container networking are operating at the standard that modern software development requires. Infrastructure as code is what separates teams that can reliably reproduce environments from those that have snowflake servers that nobody fully understands. Writing Terraform that captures your entire infrastructure as version-controlled, reviewable code is the practice that enables disaster recovery, multi-environment deployments, and infrastructure change management. Engineers who understand IaC contribute to an organizational capability that has significant business value.