Track · ~8 months · 38 nodes

DevOps.

Linux, Docker, CI/CD, cloud, and the on-call mindset.

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Foundations

Linux, the shell, git, and the network underneath it all.

  1. Linux fundamentalsThe filesystem, processes, permissions, and the package manager.
  2. Shell scriptingBash, pipes, variables, and automating repetitive work.
  3. Git deep diveBranches, rebase, hooks, and git as a deployment trigger.
  4. Networking for DevOpsIP, DNS, ports, firewalls, and load balancers in practice.
  5. SSH & keysKey pairs, agents, config, and secure remote access.

Containers & orchestration

Package once, run anywhere, and run a lot of it.

  1. Docker basicsImages, containers, registries, and reproducible runtimes.
  2. Dockerfile best practicesLayer caching, multi-stage builds, and small secure images.
  3. Docker ComposeDefining multi-container local environments in one file.
  4. Kubernetes basicsPods, deployments, services, and the control loop.
  5. HelmPackaging and templating Kubernetes manifests.
  6. Kubernetes in productionResource limits, probes, autoscaling, and rollouts.

Infrastructure as code

Describe infrastructure in files, not in clicks.

  1. Terraform fundamentalsDeclaring infrastructure, providers, and the plan/apply loop.
  2. Terraform stateRemote state, locking, and not corrupting your infrastructure.
  3. Ansible basicsConfiguration management with idempotent playbooks.
  4. Pulumi vs TerraformIaC in a real language versus a declarative DSL.
  5. Drift & importsReconciling real infrastructure with your code.

CI/CD

Automated test, build, and deploy pipelines.

  1. GitHub ActionsWorkflows, jobs, runners, and the marketplace.
  2. Jenkins & alternativesSelf-hosted CI, pipelines as code, and when to use it.
  3. Deployment strategiesRolling, blue-green, and canary releases.
  4. Secrets in pipelinesInjecting credentials without leaking them into logs.

Cloud

The big providers, and the IAM that ties them together.

  1. AWS essentialsEC2, S3, VPC, and the services you actually start with.
  2. GCP essentialsCompute, storage, and networking on Google Cloud.
  3. Azure essentialsThe core Azure services and where they differ.
  4. Cloud IAMIdentities, roles, policies, and least privilege.
  5. Multi-cloud pragmatismWhen multi-cloud helps and when it just adds pain.

Observability

Logs, metrics, traces, and the on-call mindset.

  1. Logs, metrics & tracesThe three pillars and what each one answers.
  2. Prometheus & GrafanaScraping metrics and building dashboards that matter.
  3. On-call fundamentalsAlerts, escalation, runbooks, and sustainable rotations.
  4. Incident postmortemsBlameless reviews that actually prevent the next outage.

Security & reliability

Hardening, policies, and engineering for failure.

  1. System hardeningReducing attack surface on servers and containers.
  2. Network policiesSegmenting traffic and enforcing least-connectivity.
  3. SLIs, SLOs & error budgetsDefining reliability targets and spending them wisely.
  4. Chaos engineering (light)Injecting failure on purpose to find weakness first.

Beyond the basics

Platform engineering, certs, and the job hunt.

  1. Platform engineering basicsBuilding the paved road other teams deploy on.
  2. DevOps with AI toolsUsing AI for scripts, configs, and incident triage safely.
  3. System design for opsReliability, scaling, and failure as design inputs.
  4. Certifications: when they matterWhich cloud and Kubernetes certs are worth your time.
  5. Get hired (DevOps)Portfolio infra, resume, and the interview rounds.

Outcomes

When you finish this track:

Schedule

~212 hours total.

At 8–10 hours a week, that’s about 8 months. Each stage has its own pace.

  1. Foundations5 nodes33–43h
  2. Containers & orchestration6 nodes42–55h
  3. Infrastructure as code5 nodes25–33h
  4. CI/CD4 nodes18–23h
  5. Cloud5 nodes29–38h
  6. Observability4 nodes18–23h
  7. Security & reliability4 nodes18–23h
  8. Beyond the basics5 nodes29–38h

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