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Kubernetes architecture and operations primer

Use this primer with Kubernetes Validation Catalog for authorized assessment work. Kubernetes behavior and feature status depend on the server version and enabled admission, networking, storage, and cloud-provider components.

1. Intro

Tester here.

With terms like Pods, Services, and Ingress, it can feel overwhelming—especially if you're coming from a systems engineering or traditional infrastructure background.

As a simple person, I decided to approach Kubernetes with a systems engineering mindset—stepping back to get a 50,000 ft view of the big picture.

2. What & Why Systems Engineering?

A systems engineering approach breaks down complex systems into manageable pieces. This helps us understand, analyze, and eventually build or exploit them.

Let’s oversimplify the process:

1. Need: Define the problem (use cases & feasibility)
2. Requirements: Identify functional, physical, interface, and constraint requirements
3. Architecture & Design: Develop high-level and low-level blueprints
4. Implementation: Build and configure the solution
5. Integration: Connect the new system with existing ones
6. Verification & Validation: Ensure the system works as expected
7. Deployment & Operations: Maintain, monitor, and scale the solution

Let’s apply this to Kubernetes.

3. Enter Kubernetes

3.1 The Problem

Even with Docker, managing multiple containers across different systems is hard:

• What if one crashes?
• How do you scale it to 10 or 100 systems?
• How do you update without downtime?
• How do you ensure logs, storage, and networking are working?

3.2 Kubernetes to the Rescue

Kubernetes is an orchestration system designed to solve all of these problems. It acts like a robotic cluster manager.

With Kubernetes, you can:

• Deploy and run containers at scale
• Automatically restart or reschedule failed containers
• Distribute workloads across many machines
• Manage configuration, secrets, and storage cleanly
• Schedule one-time jobs or recurring tasks

4. Kubernetes from a Systems Engineer's POV

5. Two Use Cases

5.1 Use Case 1: Bob the Researcher

Bob wants to scan websites that he owns or is explicitly authorized to assess. He builds a Docker image with tools like ffuf and nikto. With Kubernetes, he can:

• Write a Job YAML
• Deploy it with kubectl apply
• Collect results from logs or shared volumes
• Scale across an approved target list while enforcing engagement rate limits

Bonus: Bob sets up a CronJob to scan weekly.

5.2 Use Case 2: AtoZ Cyber LLC

AtoZ Cyber LLC does automated recon for clients. They use Kubernetes to:

• Run parallel recon jobs per client
• Route results to object storage
• Expose dashboards via Ingress and TLS
• Use node pools to separate staging vs. prod workloads

This lets their 2-person team handle work like a much bigger company.

6. How it works?

flowchart TD
    subgraph Cluster
        A1[Control Plane]
        A2[Kube-API Server]
        A3[Scheduler]
        A4[Controller Manager]

        A1 --> A2
        A2 --> A3
        A3 --> B1[Worker Node 1]
        A3 --> B2[Worker Node 2]
        A3 --> B3[Worker Node 3]

        B1 --> C1[Pod - Runs Container for Target A]
        B2 --> C2[Pod - Runs Container for Target B]
        B3 --> C3[Pod - Runs Container for Target C]

        D3[CronJob - Schedule] --> D1[Job - One-time Task]
        D1 --> C1
        D2[Job - One-time Task] --> C2
        D4[Deployment] --> C3

        C1 --> E1[Volume - Shared Storage for Results]
        C2 --> E2[Volume - Shared Storage for Results]
        C3 --> E3[Volume - Shared Storage for Results]

        F1[Service - Exposes Results Internally] --> C1
        F2[Ingress - Routes External HTTP Traffic] --> F1

        A1 --> A4
        A4 --> B1
        A4 --> B2
        A4 --> B3
    end

7. Security & Ops Requirements

7.1 General

• Use Role-Based Access Control (RBAC)
• Isolate namespaces by client/team/project
• Use labels/annotations for tracking workloads

7.2 Security

• Use Network Policies to control Pod communication
• Enable TLS on all Ingress routes
• Scan images before use
• Rotate Secrets regularly
• Enable encryption at rest for Secrets, restrict access with least-privilege RBAC, and consider an external secret store

7.3 Performance

• Use Horizontal Pod Autoscaler for burst traffic
• Prefer native container logging (stdout/stderr)

7.4 Resilience

• Use readiness/liveness probes
• Spread workloads across zones or nodes
• Define PodDisruptionBudgets for safety during upgrades