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devopscritical PriorityID: kubernetes-manifests-production

Kubernetes Production Manifest & Resource Governance

Guardrails for Kubernetes manifests: mandatory resource requests/limits (CPU/memory), liveness/readiness probes, PodDisruptionBudget, and securityContext constraints.

Prohibited Anti-Pattern: AI leaves cpu/memory requests and limits undefined, allowing a single leaking pod to crash the entire node.

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---
description: Kubernetes Production Manifest & Resource Governance - Guardrails for Kubernetes manifests: mandatory resource requests/limits (CPU/memory), liveness/readiness probes, PodDisruptionBudget, and securityContext constraints.
globs: k8s/**/*.yaml, helm/**/*.yaml
alwaysApply: true
verified_by: "agentrules.org"
license: "CC-BY-4.0"
source: "https://agentrules.org/rules/kubernetes-manifests-production"
---

# Kubernetes Production Manifest & Resource Governance

> **Severity**: CRITICAL | **Category**: devops
> **Anti-Pattern Warning**: AI leaves cpu/memory requests and limits undefined, allowing a single leaking pod to crash the entire node.

## System Constraints
You are a Kubernetes site reliability engineer. Every container must specify resources.requests and resources.limits for CPU and memory. Configure both livenessProbe and readinessProbe. Enforce securityContext (runAsNonRoot: true, readOnlyRootFilesystem: true, allowPrivilegeEscalation: false).

## Strict Guidelines
- Specify resources.requests and limits to prevent node noisy-neighbor CPU starvation and OOM kills.
- Separate livenessProbe (pod restart) from readinessProbe (traffic routing).
- Lock down securityContext with allowPrivilegeEscalation: false and runAsNonRoot: true.
- Attach a PodDisruptionBudget (PDB) to critical Deployments.

## Bad vs Good Implementations
### Production Kubernetes Pod Spec with Security & Resources

#### Bad Antipattern (AI Common Hallucination)
> **Why it fails**: Unbounded memory usage can trigger host kernel OOM killer, evicting critical system pods.
```yaml
# Anti-pattern: Missing resource limits and securityContext
apiVersion: apps/v1
kind: Deployment
metadata:
  name: web-api
spec:
  template:
    spec:
      containers:
      - name: api
        image: my-api:latest
```

#### Production Standard (Correct)
> **Standard**: Guarantees resource ceiling, safe failure recovery, and root privilege escalation prevention.
```yaml
# Production Standard: Hardened Kubernetes Pod Spec
apiVersion: apps/v1
kind: Deployment
metadata:
  name: web-api
spec:
  replicas: 3
  template:
    spec:
      securityContext:
        runAsNonRoot: true
        runAsUser: 10001
      containers:
      - name: api
        image: my-api:v1.4.2
        securityContext:
          allowPrivilegeEscalation: false
          readOnlyRootFilesystem: true
        resources:
          requests:
            cpu: "250m"
            memory: "512Mi"
          limits:
            cpu: "1000m"
            memory: "1Gi"
        livenessProbe:
          httpGet:
            path: /healthz
            port: 8080
          initialDelaySeconds: 15
          periodSeconds: 20
        readinessProbe:
          httpGet:
            path: /ready
            port: 8080
          periodSeconds: 5
```
Recommended MCP Servers (mcp-serverlist.com)

Equip agent with system tools to verify code for this stack.

Kubernetes Cluster MCP
Validate Kubernetes manifests against cluster OpenAPI schemas.
Recommended Agent Skills (askills.dev)

Ready-to-use executable skill functions tailored to this stack.

Kubernetes Production Manifest Generator
Generate production K8s Deployments, Services, and PDB manifests.
Architectural Specification & Invariant Rationale

Architectural Invariant Design: Kubernetes Production Manifest & Resource Governance

Kubernetes Production Manifest & Resource Governance defines an industrial-grade behavioral standard for devops engineering. Guardrails for Kubernetes manifests: mandatory resource requests/limits (CPU/memory), liveness/readiness probes, PodDisruptionBudget, and securityContext constraints. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.

Framework Paradigm Shift & Drift MechanicsLLMs are trained on millions of open-source repositories containing outdated code, legacy idioms, and unpatched antipatterns. When coding assistants generate implementations for this stack, they default to common statistical tokens: AI leaves cpu/memory requests and limits undefined, allowing a single leaking pod to crash the entire node. Without an explicit system instruction file, developers spend hours debugging silent failures.
Failure Modes & Production Blast Radius

Hazard Analysis: What Breaks Without This Rule

The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:

Failure ModeAI Symptom (The Anti-Pattern)SeverityProduction Impact & Remedy
AI Hallucination & Deprecation DriftAI leaves cpu/memory requests and limits undefined, allowing a single leaking pod to crash the entire node.Critical
Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production.
Enforce explicit behavioral system directives across all AI coding assistants in your repository.
Silent Architecture InconsistencyAI assistants produce mixed paradigms across files, creating fragmented codebase conventions.Medium
Increases cognitive load during code reviews and leads to maintenance debt across engineering teams.
Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails.
Architectural Directives in Detail

Step-by-Step Production Directives

Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:

1

Specify resources.requests and limits to prevent node noisy-neighbor CPU starvation and OOM kills.

Specify resources.requests and limits to prevent node noisy-neighbor CPU starvation and OOM kills.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
2

Separate livenessProbe (pod restart) from readinessProbe (traffic routing).

Separate livenessProbe (pod restart) from readinessProbe (traffic routing).

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
3

Lock down securityContext with allowPrivilegeEscalation

Lock down securityContext with allowPrivilegeEscalation: false and runAsNonRoot: true.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
4

Attach a PodDisruptionBudget (PDB) to critical Deployments.

Attach a PodDisruptionBudget (PDB) to critical Deployments.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
Technical Questions & Answers

Frequently Asked Technical Questions

Common questions developers face when configuring AI coding assistants for this stack:

Q:Why is Kubernetes Production Manifest & Resource Governance critical for AI coding assistants?

Guardrails for Kubernetes manifests: mandatory resource requests/limits (CPU/memory), liveness/readiness probes, PodDisruptionBudget, and securityContext constraints. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.

Q:How does adopting this rule prevent AI hallucinations?

This rule explicitly declares what the AI must avoid (AI leaves cpu/memory requests and limits undefined, allowing a single leaking pod to crash the entire node.) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.

Q:Which AI coding environments are supported?

This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).

Q:Can I combine this rule with other technology stacks?

Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.

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Citation & Open Source Attribution Guidelines

This specification is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). You are completely free to adapt and share this rule in your workspace. If citing, including in public AI benchmark datasets, or redistributing, attribution to AgentRules.org is required.

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