DevOps & Pipeline Automation

Understand what DevOps is and why it exists. This module covers the CALMS framework (Culture, Automation, Lean, Measurement, Sharing) and the Three Ways (flow, feedback, and continual learning) that underpin every practice in the rest of the course.

• 1.1 What DevOps Is (and Is Not)
  Preview 18:40
• 1.2 The CALMS Framework
  42:05
• 1.3 The Three Ways: Flow, Feedback, Learning
  38:15
• 1.4 Measuring Delivery: The DORA Metrics
  26:30
• 1.5 Lab: Mapping Your Value Stream
  45:00

Choose a branching model that enables continuous integration rather than blocking it. Compare trunk-based development, GitFlow, and GitHub Flow, and learn how pull requests, code review, and protected branches form the entry gate to your pipeline.

• 2.1 Trunk-Based Development vs GitFlow vs GitHub Flow
  44:20
• 2.2 Pull Requests, Code Review & Protected Branches
  39:10
• 2.3 Semantic Versioning & Conventional Commits
  31:55
• 2.4 Feature Flags for Continuous Delivery
  35:40
• 2.5 Lab: Set Up a Trunk-Based Repo with Branch Protection
  52:30

Build your first continuous integration pipelines. Learn the anatomy of a pipeline: triggers, jobs, steps, runners, artifacts, and caching, implemented in both GitHub Actions (YAML workflows) and GitLab CI (.gitlab-ci.yml).

• 3.1 Anatomy of a CI Pipeline
  40:15
• 3.2 GitHub Actions: Workflows, Jobs & Actions
  55:30
• 3.3 GitLab CI: Stages, Jobs & Runners
  51:20
• 3.4 Caching, Artifacts & Matrix Builds
  43:45
• 3.5 Managing Secrets & Environment Variables
  34:10
• 3.6 Lab: Build a Lint-and-Build Workflow
  58:00

Turn tests into automated quality gates. Apply the test pyramid to balance unit, integration, and end-to-end tests, enforce coverage thresholds, and add static analysis and security scanning so broken code never reaches the main branch.

• 4.1 The Test Pyramid in CI
  37:25
• 4.2 Coverage Gates & Quality Thresholds
  33:50
• 4.3 Static Analysis & Linting Gates
  29:40
• 4.4 Dependency & Container Security Scanning
  36:15
• 4.5 Lab: Add a Test-and-Scan Stage to Your Pipeline
  54:20

Package applications so they run the same everywhere. Write efficient Dockerfiles with multi-stage builds, manage images and registries, and orchestrate local multi-service environments with docker compose.

• 5.1 Images, Containers & Layers
  41:30
• 5.2 Writing Efficient Dockerfiles
  48:15
• 5.3 Multi-Stage Builds & Image Optimization
  39:50
• 5.4 Registries: Tagging, Pushing & Pulling
  32:25
• 5.5 Multi-Service Apps with Docker Compose
  44:00
• 5.6 Lab: Containerize and Build an Image in CI
  56:40

Run containers at scale. Learn the Kubernetes object model: Pods, Deployments, Services, ConfigMaps, and Secrets, and how to apply manifests with kubectl, perform rolling updates, and scale workloads up and down.

• 6.1 Kubernetes Architecture & Core Objects
  46:35
• 6.2 Pods, Deployments & ReplicaSets
  50:10
• 6.3 Services, Ingress & Networking
  45:20
• 6.4 ConfigMaps, Secrets & Resource Limits
  38:55
• 6.5 Rolling Updates & Health Probes
  42:40
• 6.6 Lab: Deploy a Service to a Local Cluster
  60:30

Define cloud infrastructure declaratively and version it like code. Write HCL configurations, understand how Terraform tracks state, structure reusable modules, and run terraform plan and terraform apply from a pipeline.

• 7.1 Declarative Infrastructure & HCL Basics
  43:15
• 7.2 Providers, Resources & State
  47:30
• 7.3 Variables, Outputs & Reusable Modules
  41:05
• 7.4 Remote State & Plan/Apply in CI
  38:20
• 7.5 Lab: Provision a Cluster with Terraform
  57:50

Automate the configuration of servers and services. Write idempotent Ansible playbooks, organize tasks into roles, manage inventories, and keep secrets safe with Ansible Vault.

• 8.1 Inventories, Modules & Idempotency
  40:10
• 8.2 Writing Playbooks & Tasks
  45:35
• 8.3 Roles, Templates & Ansible Vault
  42:25
• 8.4 Lab: Configure a Host with a Playbook
  51:15

Know what your systems are doing in production. Collect metrics with Prometheus, build dashboards in Grafana, centralize logs, understand the three pillars of observability (metrics, logs, traces), and define meaningful alerts and SLOs.

• 9.1 Metrics, Logs & Traces: The Three Pillars
  39:45
• 9.2 Collecting Metrics with Prometheus
  47:20
• 9.3 Dashboards with Grafana
  41:50
• 9.4 Centralized Logging & Alerting on SLOs
  38:30
• 9.5 Lab: Instrument and Monitor Your Service
  55:10

Release changes safely and tie everything together. Compare rolling, blue-green, and canary deployments, learn rollback and progressive delivery, then build an end-to-end CI/CD pipeline as your capstone project.

• 10.1 Rolling, Blue-Green & Canary Compared
  44:15
• 10.2 Implementing Blue-Green Deployments
  41:40
• 10.3 Canary Releases & Progressive Delivery
  39:25
• 10.4 Rollbacks & Automated Recovery
  33:10
• 10.5 Capstone Brief & Architecture
  22:30
• 10.6 Capstone: Build an End-to-End CI/CD Pipeline
  75:00
• 10.7 Capstone: Deploy with a Canary Rollout
  62:20