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Compute Central

Practical, lab-tested guides for the infrastructure you actually run — Linux, containers, Kubernetes, automation, CI/CD, observability, and AI engineering, explained from first principles all the way to production.

Start with Docker Explore all tracks
  • Free and open source
  • Hands-on labs and case studies
  • Updated September 2026
$ docker compose up -d✔ Container caddylab-db-1      Healthy✔ Container caddylab-api-1     Started✔ Container caddylab-caddy-1   Started$ curl -s localhost/api/todos | jq length3
Open the Docker guide →

0 Guides and lab-tested chapters

0 Learning tracks, foundations to production

0 Hands-on labs and case studies

2016 Notes and lessons collected since

Learning tracks

Pick a track, or filter by what you're working on. Every track stands on its own.

Docker and Linux Containers From namespaces and cgroups to images, networking, storage, Compose, Podman, and production troubleshooting. 25 chapters + quick reference

Kubernetes and OpenShift Core objects, networking and Gateway API, security, GitOps, labs, case studies, and interview prep. 17 sections · 108 pages

Ansible Automation Playbooks, roles, collections, custom modules, Vault, Molecule, and real deployment case studies. 17 sections · 104 pages

Terraform Infrastructure as code from a first project to remote state, modules, environments, testing, and CI/CD. 8 guides

CI/CD Pipelines GitHub Actions, GitLab CI, Jenkins, and ArgoCD — from commit to tested image to a GitOps deployment. 7 guides

Code Quality SonarQube quality gates, open-source linters and scanners, and the paid platforms that compete with them. 7 guides

Monitoring and SRE Prometheus, Grafana, Alertmanager, Loki with Grafana Alloy, OpenTelemetry, and synthetic checks. 12 guides

AI Engineering LLM fundamentals, RAG, tools and MCP, agents, and evaluation for platform and DevOps teams. 5 guides

Shell Scripts Safe Bash structure, health checks, log scanners, backups, deployment helpers, and debugging. 6 example scripts

The path through this site

Most readers move left to right — but jump in wherever your work is today.

  1. 1Linux & shellSafe scripts and system basics
  2. 2ContainersHow Docker really works
  3. 3KubernetesOrchestrate workloads
  4. 4AutomationAnsible and Terraform
  5. 5DeliveryCI/CD and code quality
  6. 6ObservabilityMetrics, logs, traces
  7. 7AI engineeringLLMs, RAG, and agents

What's new

New Terraform learning pathState and S3 native locking, modules, environments, and CI/CD with OIDC.

New Gateway APIThe successor to Ingress, and how to migrate off retired ingress-nginx.

Expanded Docker course labsBuild a container by hand, then run a four-tier app on segmented networks.

Updated Loki with Grafana AlloyPromtail is end-of-life — the supported collector and migration path.

Learning paths by goal

Pick the goal closest to yours — each tab is a short, ordered route through the material.

Start with the Docker and Linux Containers course, then move to Kubernetes core concepts.

Try the Minikube lab, the kind lab, or the Podman lab.

Provision with Terraform, configure hosts with Ansible, and glue it together with shell scripts.

Start with the CI/CD overview and GitHub Actions, add SonarQube quality gates, then wire in Kubernetes CI/CD.

Stand up the monitoring stack and review Kubernetes troubleshooting.

Start with the AI Engineering Guide, then LLM fundamentals and AI evaluation.

How to use this site

Start with the topic you need, then follow the examples in a local or test environment before using them in production. Most pages explain the reason behind each step, not just the command.

Best way to learn

Read the short explanation first, run the example safely, then write down what changed and why it worked.

Production reminder

Always review commands, credentials, namespaces, and environment names before running anything against shared or production systems.

Browse every section

About

I’m Sameer Alam, a DevOps Engineer and SRE practitioner focused on reliable, automated, observable, and secure systems. My work spans infrastructure design, deployment automation, monitoring, incident response, and platform operations.

I started documenting what I learned in 2016. Compute Central brings those notes, experiments, and real-world lessons into one organized place.

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