Build Your Cloud Deployment Skill

Before learning real cloud deployment—provisioning Kubernetes clusters on DigitalOcean, Hetzner, and other providers—you'll own a multi-cloud deployment skill.

Step 1: Get the Skills Lab

1. Go to github.com/panaversity/claude-code-skills-lab
2. Click the green Code button
3. Select Download ZIP
4. Extract the ZIP file
5. Open the extracted folder in your terminal

cd claude-code-skills-lab
claude

Step 2: Create Your Skill

Copy and paste this prompt:

Using your skill creator skill create a new skill for multi-cloud Kubernetes deployment.
I will use it to provision and manage K8s clusters on budget-friendly providers like
DigitalOcean (DOKS) and Hetzner (k3s via hetzner-k3s CLI). The skill should cover:

- DigitalOcean DOKS cluster provisioning with doctl
- Hetzner K3s cluster provisioning with hetzner-k3s CLI
- Multi-cloud portability (provision → connect → deploy pattern)
- Cost comparison and optimization strategies

Use context7 skill to study official documentation for doctl, hetzner-k3s, and kubectl.
Build it from official docs so no self-assumed knowledge.

Claude will:

1. Fetch official DigitalOcean and Hetzner documentation via Context7
2. Ask you clarifying questions (cluster size, node pools, cost thresholds)
3. Create the complete skill with CLI references and deployment templates

Your skill appears at .claude/skills/multi-cloud-deployer/.

Reflect on Your Skill

Your multi-cloud-deployer skill is now ready. Throughout this chapter, you'll:

1. Test it against real cloud scenarios (provisioning, connecting, deploying)
2. Identify gaps as you learn manual steps
3. Improve it by adding provider-specific patterns

After each lesson, return here to verify: Does my skill handle what I just learned?

Next: Lesson 1 — Why Real Cloud Deployment Matters

Core Concept

Start Chapter 90 by creating a cloud-deployment skill that captures patterns for provisioning clusters, networking, secrets, and app rollout—built from official docs and refined through the chapter.

Key Mental Models

• Skill-first: Build the asset before deeper lessons; iterate with each deployment task.
• Spec-driven: Define cluster, network, DNS, and secret requirements up front.
• Provider-agnostic: Encode reusable patterns that adapt across clouds.

Critical Patterns

• Use /skill-creator with fetched provider/Kubernetes docs to build the deployment skill.
• Include provisioning, load balancer/DNS, secret management, and app rollout templates.
• Set success criteria in LEARNING-SPEC and validate generated manifests/commands.

Common Mistakes

• Building from memory instead of docs, leading to broken IaC patterns.
• Ignoring DNS/secrets/ingress in the skill scope, forcing ad hoc fixes later.
• Treating the initial skill as final rather than improving after each lesson.

Connections

• Builds on: Earlier skill-first chapters and Kubernetes/Docker foundations.
• Leads to: Practical cloud setup and deployment steps in the remaining lessons.