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Kubernetes Manifests

$29

Kubernetes manifest library with deployments, services, ingress, and RBAC configurations.

📁 9 files

JSONMarkdownPythonKubernetes

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📁 File Structure 9 files

kubernetes-manifests/ ├── LICENSE ├── README.md ├── examples/ │ └── app_spec.json ├── free-sample.zip ├── guide/ │ ├── 01_features.md │ ├── 02_configuration-reference.md │ └── 03_generated-files.md ├── index.html └── src/ └── k8s_generator.py

📖 Documentation Preview README excerpt

Kubernetes Manifests

Part of the Deploy Kit by CodeVault

Generate production-ready Kubernetes deployment manifests from a simple JSON application spec. Creates Deployments, Services, Ingress, ConfigMaps, and HorizontalPodAutoscalers — all with security best practices baked in.

Features

Generate complete K8s manifests: Deployment, Service, Ingress, ConfigMap, HPA
Security-hardened defaults: non-root containers, read-only filesystem, resource limits
Readiness and liveness probe configuration
Horizontal Pod Autoscaler with CPU/memory targets
Namespace-aware resource generation
Multi-environment support (dev, staging, production) with different replica counts
Ingress with TLS configuration
ConfigMap and Secret references
Validates your app spec before generating
Python stdlib only — zero dependencies

Quick Start


# Generate all K8s manifests from the example spec
python src/k8s_generator.py --config examples/app_spec.json

# Write to a target directory
python src/k8s_generator.py --config examples/app_spec.json --output-dir ./k8s/

# Generate only specific resources
python src/k8s_generator.py --config examples/app_spec.json --resources deployment,service

# Generate for a specific environment
python src/k8s_generator.py --config examples/app_spec.json --env production

# Validate config without generating
python src/k8s_generator.py --config examples/app_spec.json --validate-only

Configuration Reference

Field	Type	Required	Description
`app_name`	string	Yes	Application name (used in all resource names)
`namespace`	string	No	K8s namespace (default: `default`)
`image`	string	Yes	Container image (e.g., `ghcr.io/acme/app:latest`)
`replicas`	int	No	Replica count (default: `2`)
`port`	int	Yes	Container port
`service_port`	int	No	Service port (default: same as `port`)
`env_vars`	object	No	Environment variables as key-value pairs
`resources`	object	No	CPU/memory requests and limits
`health_check`	object	No	Liveness/readiness probe config
`ingress`	object	No	Ingress host, path, and TLS config
`hpa`	object	No	Autoscaler min/max replicas and CPU target
`environments`	object	No	Per-environment overrides
`labels`	object	No	Additional labels for all resources

CLI Reference

Flag	Description

... continues with setup instructions, usage examples, and more.

📄 Code Sample .py preview

src/k8s_generator.py #!/usr/bin/env python3 """ Kubernetes Manifest Generator — Deploy Kit by DataNest Generate production-ready Kubernetes deployment manifests from a JSON application specification. Creates Deployments, Services, Ingress rules, ConfigMaps, and HorizontalPodAutoscalers with security best practices. Why this exists: Writing Kubernetes YAML by hand is painful — deep nesting, easy-to-miss fields, and security settings you always forget (runAsNonRoot, resource limits, readOnly filesystem). This tool generates correct, security- hardened manifests from a simple app spec so you can deploy confidently. Usage: python k8s_generator.py --config app.json python k8s_generator.py --config app.json --output-dir ./k8s/ python k8s_generator.py --config app.json --resources deployment,service python k8s_generator.py --config app.json --env production License: MIT """ from __future__ import annotations import argparse import json import logging import sys from dataclasses import dataclass, field from pathlib import Path from typing import Any # --------------------------------------------------------------------------- # Constants # --------------------------------------------------------------------------- VALID_RESOURCES = {"namespace", "deployment", "service", "ingress", "configmap", "hpa"} LOG = logging.getLogger("k8s-generator") # --------------------------------------------------------------------------- # Data Models # --------------------------------------------------------------------------- @dataclass class ResourceSpec: """CPU/memory resource requests and limits.""" requests: dict[str, str] = field(default_factory=lambda: {"cpu": "250m", "memory": "256Mi"}) # ... 542 more lines ...

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