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Kustomize

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BagelHole
kustomize

Customize Kubernetes manifests without templating using Kustomize. Create base configurations with environment overlays, manage configuration variants, and patch resources declaratively. Use when managing Kubernetes configurations across multiple environments without Helm.

Overview

PublisherBagelHole
RepositoryDevOps-Security-Agent-Skills
Skill namekustomize
Stars
1.1K
Forks
161
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by BagelHole on GitHub. Read the source before you install it.

Installation

Install the Kustomize AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/devops/orchestration/kustomize
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/BagelHole/DevOps-Security-Agent-Skills.git /tmp/DevOps-Security-Agent-Skills
mkdir -p .claude/skills
cp -r /tmp/DevOps-Security-Agent-Skills/devops/orchestration/kustomize .claude/skills/kustomize
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kustomize in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Kustomize on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Kustomize is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Kustomize

Customize Kubernetes resources declaratively without templating.

When to Use This Skill

Use this skill when:

  • Managing Kubernetes configs across environments
  • Patching existing manifests without modification
  • Creating configuration variants from bases
  • Customizing third-party manifests
  • Preferring declarative over templating approach

Prerequisites

  • kubectl 1.14+ (includes kustomize)
  • Or standalone kustomize CLI
  • Basic Kubernetes manifest knowledge

Directory Structure

myapp/
├── base/
│   ├── kustomization.yaml
│   ├── deployment.yaml
│   ├── service.yaml
│   └── configmap.yaml
└── overlays/
    ├── development/
    │   ├── kustomization.yaml
    │   └── replica-patch.yaml
    ├── staging/
    │   ├── kustomization.yaml
    │   └── namespace.yaml
    └── production/
        ├── kustomization.yaml
        ├── replica-patch.yaml
        └── resource-patch.yaml

Base Configuration

kustomization.yaml

yaml
# base/kustomization.yaml
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization

resources:
  - deployment.yaml
  - service.yaml
  - configmap.yaml

commonLabels:
  app: myapp
  
commonAnnotations:
  managed-by: kustomize

Base Resources

yaml
# base/deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  replicas: 1
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: myapp
        image: myapp:latest
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "64Mi"
            cpu: "100m"
          limits:
            memory: "128Mi"
            cpu: "200m"

Overlays

Development Overlay

yaml
# overlays/development/kustomization.yaml
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization

resources:
  - ../../base

namespace: myapp-dev

namePrefix: dev-

commonLabels:
  environment: development

images:
  - name: myapp
    newTag: dev-latest

Production Overlay

yaml
# overlays/production/kustomization.yaml
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization

resources:
  - ../../base

namespace: myapp-prod

namePrefix: prod-

commonLabels:
  environment: production

replicas:
  - name: myapp
    count: 5

images:
  - name: myapp
    newName: registry.example.com/myapp
    newTag: v2.0.0

patches:
  - path: resource-patch.yaml

Patching

Strategic Merge Patch

yaml
# overlays/production/resource-patch.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  template:
    spec:
      containers:
      - name: myapp
        resources:
          requests:
            memory: "256Mi"
            cpu: "500m"
          limits:
            memory: "512Mi"
            cpu: "1000m"

JSON Patch

yaml
# kustomization.yaml
patches:
  - target:
      kind: Deployment
      name: myapp
    patch: |-
      - op: replace
        path: /spec/replicas
        value: 5
      - op: add
        path: /spec/template/spec/containers/0/env
        value:
          - name: LOG_LEVEL
            value: info

Inline Patches

yaml
# kustomization.yaml
patches:
  - patch: |-
      apiVersion: apps/v1
      kind: Deployment
      metadata:
        name: myapp
      spec:
        replicas: 3
    target:
      kind: Deployment
      name: myapp

Configuration Generation

ConfigMap Generator

yaml
# kustomization.yaml
configMapGenerator:
  - name: myapp-config
    literals:
      - APP_ENV=production
      - LOG_LEVEL=info
    files:
      - config.yaml
    envs:
      - config.env
    options:
      disableNameSuffixHash: false

Secret Generator

yaml
# kustomization.yaml
secretGenerator:
  - name: myapp-secrets
    literals:
      - api-key=secret123
    files:
      - tls.crt
      - tls.key
    type: kubernetes.io/tls

Image Transformations

yaml
# kustomization.yaml
images:
  # Change tag
  - name: myapp
    newTag: v2.0.0
  
  # Change registry
  - name: myapp
    newName: registry.example.com/myapp
    newTag: v2.0.0
  
  # Use digest
  - name: myapp
    digest: sha256:abc123...

Resource Transformations

Name Prefix/Suffix

yaml
# kustomization.yaml
namePrefix: prod-
nameSuffix: -v2

Namespace

yaml
# kustomization.yaml
namespace: production

Labels and Annotations

yaml
# kustomization.yaml
commonLabels:
  app.kubernetes.io/name: myapp
  app.kubernetes.io/environment: production

commonAnnotations:
  example.com/owner: team-a

Replicas

yaml
# kustomization.yaml
replicas:
  - name: myapp
    count: 5
  - name: worker
    count: 3

Components

yaml
# components/monitoring/kustomization.yaml
apiVersion: kustomize.config.k8s.io/v1alpha1
kind: Component

resources:
  - servicemonitor.yaml

patches:
  - patch: |-
      apiVersion: apps/v1
      kind: Deployment
      metadata:
        name: myapp
      spec:
        template:
          metadata:
            annotations:
              prometheus.io/scrape: "true"
              prometheus.io/port: "8080"
yaml
# overlays/production/kustomization.yaml
components:
  - ../../components/monitoring

Remote Resources

yaml
# kustomization.yaml
resources:
  # Remote Git repository
  - https://github.com/org/manifests//base?ref=v1.0.0
  
  # Remote URL
  - https://raw.githubusercontent.com/org/repo/main/deployment.yaml

Commands

bash
# Build and view output
kubectl kustomize overlays/production

# Apply to cluster
kubectl apply -k overlays/production

# Delete resources
kubectl delete -k overlays/production

# View diff
kubectl diff -k overlays/production

# Build with standalone kustomize
kustomize build overlays/production

# Build and apply
kustomize build overlays/production | kubectl apply -f -

Helm Chart Integration

yaml
# kustomization.yaml
helmCharts:
  - name: prometheus
    repo: https://prometheus-community.github.io/helm-charts
    version: 25.0.0
    releaseName: prometheus
    namespace: monitoring
    valuesFile: values.yaml
    includeCRDs: true

Variable Substitution

yaml
# kustomization.yaml
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization

resources:
  - deployment.yaml

replacements:
  - source:
      kind: ConfigMap
      name: myapp-config
      fieldPath: data.APP_VERSION
    targets:
      - select:
          kind: Deployment
          name: myapp
        fieldPaths:
          - spec.template.spec.containers.[name=myapp].image
        options:
          delimiter: ':'
          index: 1

Common Issues

Issue: Name Hash Conflicts

Problem: Resources not updating when ConfigMap changes Solution: Enable name suffix hash (default) or use replacement

Issue: Patch Not Applying

Problem: Strategic merge patch doesn't work Solution: Verify resource names match, use JSON patch for complex changes

Issue: Remote Resource Fails

Problem: Cannot fetch remote resources Solution: Check URL, verify ref/tag exists, ensure network access

Issue: Label Selector Mismatch

Problem: commonLabels breaks selectors Solution: Use includeSelectors: false or exclude specific resources

yaml
commonLabels:
  app: myapp
configurations:
  - labelExclusions.yaml

Best Practices

  • Keep base manifests environment-agnostic
  • Use overlays for environment-specific config
  • Prefer strategic merge patches for simple changes
  • Use components for optional features
  • Pin remote resource versions
  • Enable ConfigMap/Secret hash suffixes
  • Document overlay structure in README
  • Test builds before applying

Related Skills

Frequently asked questions

What does the Kustomize AI skill do?

Customize Kubernetes manifests without templating using Kustomize. Create base configurations with environment overlays, manage configuration variants, and patch resources declaratively. Use when managing Kubernetes configurations across multiple environments without Helm.

Why use Kustomize on TypingMind?

Because you install it once and use it with any model. Kustomize is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Kustomize in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/devops/orchestration/kustomize. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Kustomize?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Kustomize?

As many as you like. As long as a model supports skills, you can use Kustomize with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Kustomize AI skill free?

Yes. It is published on GitHub by BagelHole under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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