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Python HTTP Function with Dependencies - Kubeless Typing CST Test
Python HTTP Function with Dependencies — Kubeless Code
Python HTTP function that uses additional dependencies.
# kubeless/demo/python-http-deps.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
name: http-deps-python
namespace: default
spec:
runtime: python3.8
handler: handler.main
source: |
import requests
def main(event, context):
r = requests.get('https://httpbin.org/get')
return r.text
events:
hello-http:
type: http
metadata:
path: /requests
method: GETKubeless Language Guide
Kubeless is a Kubernetes-native serverless framework that allows developers to deploy small, single-purpose functions without managing infrastructure. It leverages Kubernetes resources to handle scaling, routing, and monitoring.
Primary Use Cases
- ▸Event-driven microservices
- ▸Serverless REST APIs
- ▸Background tasks and cron jobs
- ▸Data processing pipelines
- ▸Integrating Kubernetes-native functions into CI/CD workflows
Notable Features
- ▸Function deployment using Kubernetes Custom Resources
- ▸Supports multiple programming runtimes
- ▸Kubernetes-native scaling and routing
- ▸Triggers from HTTP, Kafka, NATS, and Cron
- ▸CLI and YAML-based management for DevOps workflows
Origin & Creator
Kubeless was created by Bitnami in 2016 as an open-source serverless framework for Kubernetes.
Industrial Note
Kubeless is ideal for teams already using Kubernetes who want to adopt serverless patterns without introducing new infrastructure or cloud dependencies.
Quick Explain
- ▸Kubeless is built on Kubernetes and uses custom resources to define functions as first-class objects.
- ▸Supports multiple runtimes including Python, Node.js, Go, and Ruby.
- ▸Integrates with Kubernetes services like Ingress, Secrets, and ConfigMaps.
- ▸Enables auto-scaling based on resource usage and events.
- ▸Designed to simplify function deployment while taking full advantage of Kubernetes features.
Core Features
- ▸Serverless function deployment on Kubernetes
- ▸Auto-scaling functions based on demand
- ▸Event triggers for HTTP, message queues, and timers
- ▸Native Kubernetes integration (Secrets, ConfigMaps, Services)
- ▸Monitoring via Prometheus and Kubernetes metrics
Learning Path
- ▸Learn Kubernetes basics
- ▸Understand serverless concepts
- ▸Install Kubeless on local cluster
- ▸Deploy functions with HTTP triggers
- ▸Integrate functions with event sources
Practical Examples
- ▸Serverless REST API backend
- ▸Image processing triggered by object storage events
- ▸Periodic data cleanup with cron triggers
- ▸Kafka message processing pipeline
- ▸Email notification service using Kubernetes secrets
Comparisons
- ▸Kubeless vs AWS Lambda: Lambda is managed; Kubeless requires Kubernetes
- ▸Kubeless vs OpenFaaS: Kubeless is Kubernetes-native; OpenFaaS adds UI and auto-scaling features
- ▸Kubeless vs Knative: Knative has more features, Kubeless is lightweight
- ▸Kubeless vs Fission: Both Kubernetes-native; Fission provides faster cold-start optimization
- ▸Kubeless vs Cloud Functions: Kubeless is self-hosted and flexible, Cloud Functions are managed
Strengths
- ▸No need for separate serverless infrastructure
- ▸Leverages Kubernetes features for deployment and scaling
- ▸Supports multiple runtimes and event sources
- ▸Lightweight and open-source
- ▸Enables DevOps teams to manage functions with familiar tools
Limitations
- ▸Requires Kubernetes knowledge
- ▸Less feature-rich than cloud-managed serverless (AWS Lambda, Azure Functions)
- ▸Manual scaling and monitoring setup may be needed
- ▸Community smaller than major serverless frameworks
- ▸Not ideal for non-Kubernetes environments
When NOT to Use
- ▸Projects not using Kubernetes
- ▸Applications needing managed serverless features
- ▸High-latency sensitive workloads
- ▸Teams unfamiliar with Kubernetes
- ▸Small-scale scripts better suited to traditional functions or cron jobs
Cheat Sheet
- ▸kubeless function deploy - deploy a function
- ▸kubeless function ls - list functions
- ▸kubeless function call - invoke function
- ▸kubeless trigger create - create event trigger
- ▸kubeless function logs - view function logs
FAQ
- ▸Is Kubeless free?
- ▸Yes - open-source under Apache 2.0 license.
- ▸Can Kubeless run outside Kubernetes?
- ▸No - it requires a Kubernetes cluster.
- ▸Does Kubeless support multiple languages?
- ▸Yes - Python, Node.js, Go, Ruby, and more.
- ▸How does Kubeless handle scaling?
- ▸Uses Kubernetes HPA and pod management.
- ▸Can Kubeless be used in production?
- ▸Yes - suitable for Kubernetes-based serverless applications.
30-Day Skill Plan
- ▸Week 1: Kubernetes fundamentals
- ▸Week 2: Basic function deployment
- ▸Week 3: Event-driven triggers
- ▸Week 4: Advanced scaling and secrets management
- ▸Week 5: CI/CD integration and monitoring
Final Summary
- ▸Kubeless is a lightweight, Kubernetes-native serverless framework.
- ▸Supports multiple runtimes and event triggers.
- ▸Integrates fully with Kubernetes features and tooling.
- ▸Enables event-driven microservices and background tasks.
- ▸Ideal for teams already leveraging Kubernetes infrastructure.
Project Structure
- ▸functions/ - contains source code for each function
- ▸triggers/ - YAML definitions for event triggers
- ▸deploy/ - manifests for Kubeless controllers and CRDs
- ▸scripts/ - CLI or automation scripts
- ▸README.md - documentation and usage instructions
Monetization
- ▸Backend for SaaS or microservices
- ▸Event-driven workflows in enterprise apps
- ▸Serverless APIs for commercial platforms
- ▸Data processing pipelines as a service
- ▸Integrating serverless functions in Kubernetes-native apps
Productivity Tips
- ▸Use CLI for quick deployments
- ▸Define functions and triggers declaratively via YAML
- ▸Leverage Kubernetes namespaces for isolation
- ▸Monitor metrics to optimize scaling
- ▸Automate deployments with CI/CD pipelines
Basic Concepts
- ▸Function - smallest deployable unit, triggered by events
- ▸Trigger - defines when a function should run
- ▸Runtime - language environment for the function (Python, Node.js, etc.)
- ▸Namespace - Kubernetes scope for functions and resources
- ▸Custom Resource Definitions - define functions as Kubernetes objects