kubeSmartService 0.1.0

Smart Kubernetes service resolver for Python web apps with health-check and failover

kubeSmartService

Smart Kubernetes service resolver for Python apps (Django, Flask, any WSGI/ASGI). Connects via the official Kubernetes Python client, performs health checks and automatic failover, and exposes simple metrics.

Installation

pip3 install kubeSmartService

Quick API

from kubesmartservice import kube_service, init_resolver

# Initialize once at startup (recommended)
init_resolver(cache_ttl_seconds=8.0, retries=2, backoff_base=0.2)

svc = kube_service("my-backend", namespace="default", failover=True)
print(svc.host, svc.port)
print(svc.available_pods)
print(svc.status())  # {"latency_ms": ..., "pods": N, "failover_count": X, "active_pod": "..."}

Features

• Caching of service/pod discovery (default TTL ~8s) to minimize Kubernetes API calls
• TCP health check with retry and exponential backoff
• Automatic failover across pods; fallback endpoint if Kubernetes is unavailable
• Startup initialization for Django/Flask to avoid per-request setup
• Mock mode for local development without a cluster
• Minimal permissions usage; robust error handling and structured logging

Django example (startup-safe)

# views.py
from django.http import JsonResponse
from kubesmartservice import kube_service, init_resolver

# recommended: in settings.py at startup
# from kubesmartservice import init_resolver
# init_resolver(cache_ttl_seconds=8.0, retries=2, backoff_base=0.2)

# Resolve a backend service and proxy a call (pseudo-code)
def health(request):
    svc = kube_service("my-backend", namespace="default")
    data = {
        "endpoint": f"http://{svc.host}:{svc.port}",
        "metrics": svc.status(),
    }
    return JsonResponse(data)

Flask example (app init)

from flask import Flask, jsonify
from kubesmartservice import kube_service, init_resolver

app = Flask(__name__)

@app.before_first_request
def setup_resolver():
    init_resolver(cache_ttl_seconds=8.0, retries=2, backoff_base=0.2)

@app.get("/health")
def health():
    svc = kube_service("my-backend", namespace="default")
    return jsonify({
        "endpoint": f"http://{svc.host}:{svc.port}",
        "metrics": svc.status(),
    })

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5000)

How it works

• Loads Kubernetes config: in-cluster if available, otherwise local kubeconfig.
• Fetches Service ports and Endpoints, lists pods by label app=<service_name>.
• Health checks candidates via TCP connect with retry/backoff; fails over to the next IP if unreachable.
• Tracks latency and failover count; exposes via status().
• Detects environment (minikube/staging/prod) heuristically. Mock mode via KUBESMARTSERVICE_MOCK=1.

API Reference

init_resolver(...)

Initialize the global resolver once at application startup.

Parameters:

• cache_ttl_seconds: float (default 8.0) – cache duration for discovery results
• health_timeout: float (default 1.5) – TCP connect timeout per attempt
• retries: int (default 2) – number of additional attempts per candidate pod
• backoff_base: float (default 0.2) – exponential backoff base (seconds)
• label_selector: str | None – override default app=<service_name> selector
• mock_mode: bool | None – force mock mode; default from env KUBESMARTSERVICE_MOCK
• fallback_host: str | None – fallback endpoint host if Kubernetes unavailable
• fallback_port: int | None – fallback endpoint port

Environment variables:

• KUBESMARTSERVICE_MOCK=1 – enable mock mode (uses fallback or 127.0.0.1:8000)
• KUBE_FALLBACK_HOST / KUBE_FALLBACK_PORT – default fallback endpoint

kube_service(service_name, namespace="default", failover=True, ...)

Resolve a Service to a healthy pod endpoint using cached discovery.

Returns: SmartService with attributes host, port, active_pod, available_pods and method status().

Optional keyword overrides (when not using init_resolver): cache_ttl_seconds, health_timeout, retries, backoff_base, label_selector, mock_mode, fallback_host, fallback_port.

SmartService.status()

Returns a dict: { "latency_ms": float, "pods": int, "failover_count": int, "active_pod": str|None }.

Logging & Debugging

• Library logger name: kubesmartservice
• Logs selected pod and failover attempts at DEBUG/WARNING

Example:

import logging
logging.basicConfig(level=logging.INFO)
logging.getLogger("kubesmartservice").setLevel(logging.DEBUG)

Error Handling

Possible exceptions:

• KubeAPIUnavailableError – cluster config cannot be loaded
• ServiceNotFoundError – Service not found in the target namespace
• NoHealthyEndpointsError – no reachable pods and no fallback configured

Always wrap calls in try/except in critical paths and use a fallback when appropriate.

Security & Permissions

• Uses read-only access to Services, Endpoints, and optionally Pods (for names). If listing pods is denied, resolution still works; pod names will be empty.
• Prefer binding a minimal Role/ClusterRole to the service account running your app.

Requirements

• Python 3.8+
• Kubernetes Python client (kubernetes)

License

MIT