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HomeBookThe Architecture of Trust: Building Your Cloud Security Skill
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Muhammad Usman Akbar Entity Profile

Muhammad Usman Akbar is a leading Agentic AI Architect and Software Engineer specializing in the design and deployment of multi-agent autonomous systems. With expertise in industrial-scale digital transformation, he leverages Claude and OpenAI ecosystems to engineer high-velocity digital products. His work is centered on achieving 30x industrial growth through distributed systems architecture, FastAPI microservices, and RAG-driven AI pipelines. Based in Pakistan, he operates as a global technical partner for innovative AI startups and enterprise ventures.

USMAN’S INSIGHTS
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Transforming businesses into autonomous AI ecosystems. Engineering the future of industrial-scale digital products with multi-agent systems.

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Build Your Cloud Security Skill

In January 2024, a major cryptocurrency exchange lost $230 million because an attacker exploited misconfigured Kubernetes RBAC—a service account with cluster-admin privileges was exposed through a debugging pod left running in production. The attacker didn't break encryption or exploit zero-days. They walked through a door that should have been locked.

Your Task API is running in Kubernetes. Before learning how to protect it—configuring RBAC, isolating network traffic, enforcing Pod Security Standards—you will own a cloud-security skill that generates secure configurations from day one.

This skill becomes a component of your sellable Digital FTE portfolio. By the end of this chapter, you will have a production-tested skill that implements defense-in-depth security for any Kubernetes workload.


Step 1: Get the Skills Lab

  1. Go to github.com/fistasolutions/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
bash
cd claude-code-skills-lab

Output:

bash
Claude Code v1.0.0 Type your message or ? for help >

Step 2: Write Your LEARNING-SPEC.md

Before asking Claude to build your skill, define what you want to learn. Create a file named LEARNING-SPEC.md:

markdown
# Cloud Security Learning Specification ## What A skill for securing Kubernetes workloads using: - RBAC (Roles, RoleBindings, ServiceAccounts) - NetworkPolicies (default deny, explicit allow) - Pod Security Standards (PSS enforcement) - Secrets management (External Secrets Operator patterns) - Image scanning (Trivy integration) - Dapr security (mTLS, component scopes) ## Why Production AI agents handle sensitive data and make autonomous decisions. A single misconfiguration—an overprivileged service account, missing network isolation, a container running as root—can expose the entire cluster. The 4C security model (Cloud, Cluster, Container, Code) provides defense-in-depth. ## Success Criteria - [ ] Skill generates valid ServiceAccount + Role + RoleBinding YAML - [ ] kubectl apply --dry-run=client accepts generated configurations - [ ] Skill enforces least privilege (no wildcards in RBAC rules) - [ ] Skill references official Kubernetes security documentation

Output:

bash
LEARNING-SPEC.md created (892 bytes)

This specification tells Claude exactly what you need and how you will measure success.


Step 3: Fetch Official Documentation

Ask Claude to gather the authoritative source material:

bash
Using your Context7 skill, fetch the official Kubernetes security documentation. I need to understand RBAC (Roles, ClusterRoles, RoleBindings), NetworkPolicy, and Pod Security Standards.

Claude will retrieve documentation from the official Kubernetes project, giving your skill accurate, up-to-date patterns rather than hallucinated configurations.

Output:

text
Fetching Kubernetes security documentation via Context7... Retrieved: - RBAC authorization patterns - NetworkPolicy specification - Pod Security Standards (Privileged, Baseline, Restricted) - Secrets management best practices - Security context configuration Documentation ready for skill creation.

Step 4: Create Your Skill

Now prompt Claude to build the skill using the fetched documentation:

bash
Using your skill creator skill, create a new skill for Kubernetes security. I will use it to secure Python/FastAPI applications from dev to production. Cover RBAC, NetworkPolicies, Pod Security Standards, secrets management, image scanning with Trivy, and Dapr security. Use the Kubernetes security docs you just fetched.

Claude will:

  1. Study the fetched documentation
  2. Ask clarifying questions about your security requirements
  3. Create the skill with security templates and best practices

Output:

text
Creating cloud-security skill... Questions: 1. Should I include patterns for External Secrets Operator? 2. What base PSS level should be the default (baseline or restricted)? 3. Do you need Dapr-specific security patterns? [After your answers] Skill created at .claude/skills/cloud-security/ - SKILL.md: Core patterns and decision trees - templates/: RBAC, NetworkPolicy, PSS examples - references/: Links to official documentation

Your skill appears at .claude/skills/cloud-security/.


Step 5: Test Your Skill

Verify your new skill generates valid Kubernetes YAML:

bash
Using my cloud-security skill, show me how to create a dedicated Service Account for my Task API with minimal permissions.

Output:

yaml
# task-api-rbac.yaml apiVersion: v1 kind: ServiceAccount metadata: name: task-api-sa namespace: task-api automountServiceAccountToken: false --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: task-api-role namespace: task-api rules: - apiGroups: [""] resources: ["configmaps"] verbs: ["get", "list"] --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: task-api-role-binding namespace: task-api subjects: - kind: ServiceAccount name: task-api-sa roleRef: kind: Role name: task-api-role apiGroup: rbac.authorization.k8s.io

Save the output and validate:

bash
kubectl apply --dry-run=client -f task-api-rbac.yaml

Output:

bash
serviceaccount/task-api-sa created (dry run) role.rbac.authorization.k8s.io/task-api-role created (dry run) rolebinding.rbac.authorization.k8s.io/task-api-role-binding created (dry run)

If dry-run succeeds, your skill generates valid RBAC configurations following least privilege principles. Notice that the Role specifies only configmaps with get and list verbs—no wildcards, no cluster-wide access.


Done

You now own a cloud-security skill built from official Kubernetes security documentation. The rest of this chapter teaches you what it knows—and how to make it better.

Next Lesson: The 4C Security Model


Try With AI

Now that you have a working skill, test its gap identification capabilities.

Prompt 1:

bash
Using my cloud-security skill, show me how to create a dedicated Service Account for my Task API with minimal permissions.

What you're learning: How your skill generates RBAC patterns following least privilege. Notice whether it avoids wildcards (*) in verbs and resources, and whether it suggests automountServiceAccountToken: false by default.

Prompt 2:

bash
What's missing from this skill for production workloads?

What you're learning: Gap identification is a critical meta-skill. Your skill might be missing NetworkPolicy defaults, PSS enforcement labels, Trivy scanning integration, or Dapr component scopes. Each gap becomes a learning target for this chapter's lessons.

Security Reminder

Never test security configurations on production clusters. Always use --dry-run=client first, then apply to a development namespace. Security misconfigurations can expose your entire cluster.