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devopscritical PriorityID: karpenter-disruption-and-topology-production-standard

Karpenter Resilient Topology, Interruption Queue, and Consolidation Budget Standard

Enforces deterministic disruption budgets, multi-instance-type diversification, and event-driven SQS interruption queue handling across Karpenter NodePools and EC2NodeClasses. Eliminates cascading eviction loops, instance starvation, and availability downtime during AWS Spot rebalances and underutilized node consolidation.

Prohibited Anti-Pattern: Restricting Spot NodePools to Single Instance Types with Uncapped Consolidation and Missing Interruption Queues

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---
description: Karpenter Resilient Topology, Interruption Queue, and Consolidation Budget Standard - Enforces deterministic disruption budgets, multi-instance-type diversification, and event-driven SQS interruption queue handling across Karpenter NodePools and EC2NodeClasses. Eliminates cascading eviction loops, instance starvation, and availability downtime during AWS Spot rebalances and underutilized node consolidation.
globs: **/karpenter/**/*.yaml, **/*nodepool*.yaml, **/*nodeclass*.yaml, k8s/**/*.yaml, infra/**/*.yaml, terraform/**/*.tf
alwaysApply: true
verified_by: "agentrules.org"
license: "CC-BY-4.0"
source: "https://agentrules.org/rules/karpenter-disruption-and-topology-production-standard"
---

# Karpenter Resilient Topology, Interruption Queue, and Consolidation Budget Standard

> **Severity**: CRITICAL | **Category**: devops
> **Anti-Pattern Warning**: Restricting Spot NodePools to Single Instance Types with Uncapped Consolidation and Missing Interruption Queues

## System Constraints
You are a Principal Cloud Architect specializing in Kubernetes cluster auto-scaling and Karpenter just-in-time provisioning. You enforce production invariants across Karpenter NodePool and EC2NodeClass declarations, ensuring resilient disruption controls, automated spot interruption handling via AWS SQS, and deep instance-type diversification.

## Strict Guidelines
- Engineers MUST ALWAYS configure explicit disruption budgets (`spec.disruption.budgets`) with percentage caps or schedule-based rate limits on every Karpenter NodePool.
- Engineers MUST NOT restrict `karpenter.k8s.aws/instance-family` or `node.kubernetes.io/instance-type` to a single instance family or generation on Spot-backed NodePools; topologies MUST allow at least 15 distinct instance varieties across available zones.
- EC2NodeClass resources MUST configure an AWS SQS queue name in `spec.interruptionQueue` to ingest native 2-minute Spot Interruption and Rebalance events via Amazon EventBridge.
- Services running on Karpenter-provisioned nodes MUST define PodDisruptionBudgets (PDB) and zone-level `topologySpreadConstraints` to prevent correlated availability drops during node drains.
- Engineers MUST NEVER configure `consolidationPolicy: WhenEmptyOrUnderutilized` without an accompanying time-bound consolidation window or rate-limiting disruption budget during peak production traffic periods.

## Bad vs Good Implementations
### Karpenter v1 NodePool and EC2NodeClass Specification

#### Bad Antipattern (AI Common Hallucination)
> **Why it fails**: Configuring a single instance type (`m5.large`) for spot workloads guarantees outage risk during AWS instance pool exhaustion. Omitting `spec.disruption.budgets` allows Karpenter to aggressively terminate multiple nodes at once, and failing to specify an `interruptionQueue` in the EC2NodeClass prevents Karpenter from gracefully evicting pods before hard spot terminations occur.
```yaml
# Anti-Pattern: Single instance type, missing disruption budgets, uncapped consolidation, and missing interruption handling
apiVersion: karpenter.sh/v1
kind: NodePool
metadata:
  name: default
spec:
  template:
    spec:
      nodeClassRef:
        group: karpenter.k8s.aws
        kind: EC2NodeClass
        name: default
      requirements:
        - key: karpenter.sh/capacity-type
          operator: In
          values: ["spot"]
        - key: node.kubernetes.io/instance-type
          operator: In
          values: ["m5.large"] # Fragile: Single instance type leads to Spot capacity starvation
  disruption:
    consolidationPolicy: WhenEmptyOrUnderutilized
    consolidateAfter: 30s # Dangerous: Instantaneous consolidation drains nodes without rate limits
---
apiVersion: karpenter.k8s.aws/v1
kind: EC2NodeClass
metadata:
  name: default
spec:
  amiFamily: AL2023
  role: KarpenterNodeRole-cluster
  subnetSelectorTerms:
    - tags:
        karpenter.sh/discovery: cluster
  securityGroupSelectorTerms:
    - tags:
        karpenter.sh/discovery: cluster
  # Missing interruptionQueue: Cannot react to Spot 2-minute warnings or Rebalance recommendations
```

#### Production Standard (Correct)
> **Standard**: Provides broad instance diversification across compute/memory/general families and architectures (amd64, arm64), precluding spot exhaustion. Defines deterministic disruption budgets to cap node churn during peak operational hours, and connects the EC2NodeClass to an SQS interruption queue for proactive 2-minute drain execution.
```yaml
# Production Invariant: Flexible instance diversification, bounded disruption budgets, and SQS event-driven interruption
apiVersion: karpenter.sh/v1
kind: NodePool
metadata:
  name: general-compute-spot
spec:
  template:
    spec:
      nodeClassRef:
        group: karpenter.k8s.aws
        kind: EC2NodeClass
        name: resilient-linux
      requirements:
        - key: karpenter.sh/capacity-type
          operator: In
          values: ["spot"]
        - key: karpenter.k8s.aws/instance-category
          operator: In
          values: ["c", "m", "r"]
        - key: karpenter.k8s.aws/instance-generation
          operator: Gt
          values: ["4"]
        - key: kubernetes.io/arch
          operator: In
          values: ["amd64", "arm64"]
        - key: kubernetes.io/os
          operator: In
          values: ["linux"]
  disruption:
    consolidationPolicy: WhenEmptyOrUnderutilized
    consolidateAfter: 1m
    budgets:
      # Limit concurrent disruption to 10% of nodes during business hours
      - nodes: "10%"
        schedule: "0 9 * * 1-5"
        duration: 9h
        timezone: "America/New_York"
      # Fallback ceiling for off-hours maintenance
      - nodes: "20%"
---
apiVersion: karpenter.k8s.aws/v1
kind: EC2NodeClass
metadata:
  name: resilient-linux
spec:
  amiFamily: AL2023
  role: KarpenterNodeRole-cluster
  interruptionQueue: KarpenterInterruptionQueue-cluster # Ingests AWS SQS Rebalance & Interruption events
  subnetSelectorTerms:
    - tags:
        karpenter.sh/discovery: cluster
  securityGroupSelectorTerms:
    - tags:
        karpenter.sh/discovery: cluster
```
Recommended MCP Servers (mcp-serverlist.com)

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

Kubernetes Cluster Inspector
Inspects live Karpenter NodePool status, NodeClaims, and PodDisruptionBudgets directly from the Kubernetes API.
AWS Resource Inspector
Verifies EventBridge rule routing and SQS queue health for Karpenter interruption handling.
Recommended Agent Skills (askills.dev)

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

Kubeconform Validation Skill
Validates Karpenter Custom Resource Definitions (NodePool and EC2NodeClass) against standard JSON schemas before deployment.
Architectural Specification & Invariant Rationale

Architectural Invariant Design: Karpenter Resilient Topology, Interruption Queue, and Consolidation Budget Standard

Karpenter Resilient Topology, Interruption Queue, and Consolidation Budget Standard defines an industrial-grade behavioral standard for devops engineering. Enforces deterministic disruption budgets, multi-instance-type diversification, and event-driven SQS interruption queue handling across Karpenter NodePools and EC2NodeClasses. Eliminates cascading eviction loops, instance starvation, and availability downtime during AWS Spot rebalances and underutilized node consolidation. 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: Restricting Spot NodePools to Single Instance Types with Uncapped Consolidation and Missing Interruption Queues 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 DriftRestricting Spot NodePools to Single Instance Types with Uncapped Consolidation and Missing Interruption QueuesCritical
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

Engineers MUST ALWAYS configure explicit disruption budgets (`spec.disruption.budgets`) with percentage caps or schedule-based rate limits on every Karpenter NodePool.

Engineers MUST ALWAYS configure explicit disruption budgets (`spec.disruption.budgets`) with percentage caps or schedule-based rate limits on every Karpenter NodePool.

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

Engineers MUST NOT restrict `karpenter.k8s.aws/instance-family` or `node.kubernetes.io/instance-type` to a single instance family or generation on Spot-backed NodePools

Engineers MUST NOT restrict `karpenter.k8s.aws/instance-family` or `node.kubernetes.io/instance-type` to a single instance family or generation on Spot-backed NodePools; topologies MUST allow at least 15 distinct instance varieties across available zones.

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

EC2NodeClass resources MUST configure an AWS SQS queue name in `spec.interruptionQueue` to ingest native 2-minute Spot Interruption and Rebalance events via Amazon EventBridge.

EC2NodeClass resources MUST configure an AWS SQS queue name in `spec.interruptionQueue` to ingest native 2-minute Spot Interruption and Rebalance events via Amazon EventBridge.

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

Services running on Karpenter-provisioned nodes MUST define PodDisruptionBudgets (PDB) and zone-level `topologySpreadConstraints` to prevent correlated availability drops during node drains.

Services running on Karpenter-provisioned nodes MUST define PodDisruptionBudgets (PDB) and zone-level `topologySpreadConstraints` to prevent correlated availability drops during node drains.

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.
5

Engineers MUST NEVER configure `consolidationPolicy

Engineers MUST NEVER configure `consolidationPolicy: WhenEmptyOrUnderutilized` without an accompanying time-bound consolidation window or rate-limiting disruption budget during peak production traffic periods.

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 Karpenter Resilient Topology, Interruption Queue, and Consolidation Budget Standard critical for AI coding assistants?

Enforces deterministic disruption budgets, multi-instance-type diversification, and event-driven SQS interruption queue handling across Karpenter NodePools and EC2NodeClasses. Eliminates cascading eviction loops, instance starvation, and availability downtime during AWS Spot rebalances and underutilized node consolidation. 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 (Restricting Spot NodePools to Single Instance Types with Uncapped Consolidation and Missing Interruption Queues) 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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