npx skills add nomadicmehul/CloudCaptain   # installs the tutor into Claude Code, Cursor, Codex or any agent that reads SKILL.md

Then ask your agent to /captain-start: a short placement quiz, a learning path, and the first lesson.

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What you build

Every lesson starts from a production problem, has you build the mechanism yourself in plain Python or Bash with tests, then do the same job with the real tool, so every flag and every error message maps onto code you wrote.

Phase	You build	Then you run
00 · Setup & Lab	a lab doctor that probes your machine and prints the install plan	kind, Docker, your coding agent
01 · Linux & Systems	a PID 1 supervisor, an fd leak detector, an strace analyser, a capability decoder, systemd units, cgroups by hand, a mount table reader, a USE-method dashboard	strace, capsh, systemctl, findmnt, PSI
02 · Networking	a route lookup like ip route get, an iterative DNS resolver, a TCP socket-state analyser, a pcap reader with tcpdump filters, a TLS ClientHello parser and certificate-chain verifier, an HTTP/1.1 server and reverse proxy, a load balancer with health checks, an RFC 9111 caching proxy	ip, dig, ss, tcpdump, openssl, curl, nginx, HAProxy, CoreDNS
03 · Git & Collaboration	a content-addressed object store that git fsck accepts, a diff and three-way merge engine, a packfile and smart-HTTP clone client, a merge queue with CODEOWNERS and rulesets, staged-only hooks with a pre-receive policy, bisect and blame over the commit graph	git plumbing, git merge-file, GIT_TRACE_PACKET, rulesets, the merge queue, pre-commit, git bisect run
04 · Scripting & Automation	a Bash linter with strict-mode checks, a CLI framework, an API client with retries and rate limits, jq and awk subsets, a cron and OnCalendar scheduler, a reproducible wheel builder	ShellCheck, curl, urllib3, jq, awk, croniter, systemd-analyze, pip and build
05 · Containers	a container runtime, an image auditor, a registry client, an image builder without a Dockerfile, a veth/bridge network, Compose, rootless user namespaces, a seccomp generator	Docker, Podman, OCI registries
06 · Orchestration	a reconciler, a scheduler, a kubelet, kube-proxy rules and cluster DNS, an RBAC authorizer, Helm, an operator, a Gateway API router	Kubernetes on kind, Helm, Envoy Gateway
07 · Infrastructure as Code	a plan/apply engine, a dependency graph, modules, a locking state server, drift detection, a policy engine, Pulumi and Crossplane front ends, an idempotent config manager	OpenTofu, conftest/OPA, Pulumi, Ansible
08 · CI/CD & GitOps	a workflow runner, a workflow security auditor, an OIDC issuer and verifier, an SBOM generator, a signer with a transparency log, a GitOps reconciler, a canary controller, a release tool	GitHub Actions and act, zizmor, cosign, syft, Argo CD, Argo Rollouts, git-cliff
09 · Cloud (AWS first)	an IAM policy evaluator, a VPC reachability analyser, SigV4 signing and an S3 server, the Lambda runtime API, an Auto Scaling group, a FOCUS cost allocator, a security posture scanner	the AWS CLI against moto, the Lambda emulator, Checkov
10 · Observability & SRE	a TSDB with Gorilla chunks, a PromQL engine, an alert router, a log pipeline with a LogQL subset, a tracer with tail sampling, SLO burn-rate rules, an incident service, chaos experiments	Prometheus, promtool, the OpenTelemetry Collector, Jaeger, Sloth, Alertmanager, Loki, Grafana Alloy, Chaos Mesh
11 · Security & DevSecOps	a secrets service with leases and Shamir unsealing, an admission webhook with a CEL subset, a Falco-style rule engine, a NetworkPolicy evaluator, a secret scanner, SPIFFE identities with mTLS, a CVE prioritiser with CVSS, EPSS and VEX, a CIS benchmark runner	OpenBao, ValidatingAdmissionPolicy, Kyverno, Falco, gitleaks, SPIRE, Trivy, Grype, kube-bench
12 · Platform Engineering	a service-template scaffolder with safe updates, a service catalog with owners and dependencies, DORA metrics from Git, deploys and incidents, per-PR preview environments, a platform API that expands one spec into Kubernetes objects	copier, the Backstage catalog model, DuckDB, kubectl auth can-i, score-k8s
13 · AI Infrastructure	a GPU scheduler with DRA, an LLM serving simulator, a token-counting gateway, a queue-based autoscaler, a prefix-cache router, HNSW and IVF indexes, a model artifact inspector, a token cost model	llama.cpp on CPU, LiteLLM, pgvector, llm-d, ORAS
14 · AIOps & Agentic Ops	an MCP server for kubectl, an incident-triage agent, AI log analysis, OpenTelemetry for LLM calls, agent sandboxes, safe write tools, agent evals	Claude Code, the Claude API, OpenTelemetry, promptfoo
15 · MLOps & LLMOps	content-addressed dataset versioning, an MLflow-compatible tracking server and model registry, a cached pipeline DAG compiled like Kubeflow's, an LLM eval gate, a shadow-and-canary model router, drift detection	DVC, MLflow, Kubeflow Pipelines, Argo Workflows, promptfoo, Argo Rollouts, Evidently

One more phase (capstones) is on the roadmap.

How a lesson works

The Problem  →  The Concept  →  Build It  →  Use It  →  Ship It  →  Quiz
 a real          one diagram     standard     the real    a skill,    six questions,
 incident                        library +    tool, same  prompt or   before and
                                 tests        job         MCP server  after

• Runnable and tested. Every lesson has code with unit tests that run anywhere (no root, no Docker, no cloud account) and a smoke.sh that runs the Linux-only steps and the real tools on a CI runner with Docker, kind and OpenTofu. A lesson shows "last verified" only after that passes.
• Current. Tool versions are tracked weekly, retired technology (ingress-nginx, PodSecurityPolicy, Swarm, Bitnami images) is flagged wherever it appears, and AI lessons use today's models and APIs.
• Yours to keep. Each lesson ships an agent skill, a prompt or an MCP server into outputs/, so you finish with a toolbox, not just notes.

Learning paths

Path	For	Lessons
DevOps Engineer	from a single Linux process to Kubernetes, IaC, cloud and AIOps	102
Site Reliability Engineer	metrics, alerts, logs, traces, SLOs, incidents and chaos on top of Linux and Kubernetes	38
DevSecOps Engineer	secrets, admission, runtime detection, network policy, supply chain and cloud IAM	42
AI Platform Engineer	engineers asked to run models: GPUs, serving, gateways, routing, cost	23
AIOps Engineer	putting agents to work on infrastructure safely	9

The tutor in your agent

npx skills add nomadicmehul/CloudCaptain installs four skills: captain-start (placement quiz and a plan in LEARNING.md), captain-learn (one lesson per session, Build It → Use It → Ship It, with the quiz and tests), captain-guide (where do I learn X, what does role Y need) and captain-check (a Socratic review of a phase). They work in Claude Code, Cursor, Codex and any agent that reads SKILL.md.

The reference library

Alongside the curriculum, cloudcaptain.io/docs keeps the long-form guides CloudCaptain started with: 150+ pages of original writing, 21 command cheat sheets, 19 interview question sets, 5 certification exam-prep guides (CKA/CKAD/CKS, Terraform, AWS, Azure, GCP), 7 learning paths and 8 career paths. Lessons link into it rather than repeating it, and the reference pages that a lesson builds on link back with a "Build this from scratch" card.

The site's Captain's Bridge reading mode tracks progress per section, and /progress remembers lessons, quiz scores and reading in your browser. No account, no tracking.

Why CloudCaptain

	CloudCaptain	roadmap.sh	devops-exercises	awesome-* lists
Build each tool from scratch, with tests	✅ 110 lessons	❌	❌	❌
Verified against the real tools in CI	✅ every lesson	❌	❌	❌
AI infrastructure and AIOps	✅ 15 lessons	partial	❌	links
An agent tutor you install	✅ npx skills add	❌	❌	❌
Long-form guides, cheat sheets, interview Q&A, exam prep	✅	roadmap nodes link out	Q&A	links
Reading and quiz progress	✅ in your browser	✅	❌	❌

Run it locally

git clone https://github.com/nomadicmehul/CloudCaptain.git
cd CloudCaptain/website
npm install
npm start                                  # http://localhost:3000, lessons at /learn
npm run curriculum:test -- linux/pid1-supervisor   # one lesson's tests

Each lesson is a folder: curriculum/phases/NN-phase/NN-lesson/ with docs/en.md, code/ (with tests and smoke.sh), quiz.json and outputs/. The contract is LESSON_TEMPLATE.md; the repo map is AGENTS.md.

Contributing

Lessons, fixes and translations are all welcome; see CONTRIBUTING.md. A new lesson starts with npm run curriculum:scaffold, must pass the validator and its tests, and gets verified by the smoke run on its pull request. Outdated content has its own issue template, and every pull request gets a preview deployment.

Teaching with CloudCaptain at a bootcamp, university or company? FORKING.md explains how to fork and adapt it. To support the work, see SPONSORS.md.

Site traffic

License

MIT, see LICENSE. Use it, fork it, teach with it.

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