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Learn Kubeless - 10 Code Examples & CST Typing Practice Test

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.

View all 10 Kubeless code examples →
Simple Python HTTP FunctionNode.js HTTP FunctionGo HTTP FunctionRuby HTTP FunctionPython Scheduled FunctionNode.js Kafka FunctionPython RabbitMQ FunctionPython CloudEvent FunctionPython HTTP Function with DependenciesNode.js Cron Function

Learn KUBELESS with Real Code Examples

Updated Nov 25, 2025

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

Basic Concepts Overview

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

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

Building Workflow

Write function code in supported runtime

Create YAML definition or use CLI to deploy function

Define triggers (HTTP, message queues, cron) for the function

Deploy function to Kubernetes cluster

Test function by invoking triggers or HTTP endpoints

Difficulty Use Cases

Beginner: deploy simple HTTP function

Intermediate: event-driven function triggered by Kafka/NATS

Advanced: multiple functions with dependencies and secrets

Expert: CI/CD pipelines with serverless Kubernetes integration

Auditor: monitor and optimize function performance

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

Versioning Timeline

2016 - Kubeless initial release by Bitnami

2017 - Added multiple runtime support

2018 - Improved event triggers and Cron support

2019 - Integration with Prometheus metrics

2020-2023 - Maintenance releases and Kubernetes compatibility updates

Glossary

Function - single-purpose, deployable code unit

Trigger - event source that invokes a function

Runtime - environment in which the function executes

Custom Resource Definition - Kubernetes resource type

Namespace - Kubernetes scope for function deployment

Installation Setup

Install Kubernetes cluster (Minikube, EKS, GKE, AKS, etc.)

Install Kubeless CLI and server components via kubectl

Deploy controller and CRDs using YAML manifests

Verify installation with `kubeless function ls`

Set up permissions and namespaces for function deployment

Environment Setup

Install Kubernetes cluster

Install Kubeless CLI and server components

Configure kubeconfig context

Verify cluster and namespace

Deploy sample function to test setup

Config Files

Function YAML definition

Trigger YAML definition

Kubeless CLI configuration

Kubernetes manifests for controllers

Optional ConfigMaps and Secrets

Cli Commands

kubeless function deploy <name> --runtime <runtime> --from-file <file> --handler <handler>

kubeless function ls

kubeless function call <name>

kubeless trigger create <type> <name> --function-name <function>

kubeless function logs <name>

Internationalization

No built-in i18n support

Message localization handled by function code

Event payloads may be language-agnostic

External services handle multi-language content

Focus on infrastructure, not content

Accessibility

Accessible via kubectl and CLI

HTTP triggers accessible over network

Functions can be invoked programmatically

Namespace isolation supports multi-tenant setups

Runs anywhere Kubernetes is supported

Ui Styling

No UI provided - CLI and YAML based

Integrates with dashboards like Kubernetes Dashboard

Monitor functions via Prometheus/Grafana

Focus on API and event-based workflows

Web interfaces optional via HTTP triggers

State Management

Functions are stateless by design

Persistent state managed externally (DB, storage)

Secrets and ConfigMaps provide configuration

Scaling does not affect function state

Pods destroyed/recreated without losing data externally

Data Management

Input and output via triggers

Supports JSON, HTTP, and message payloads

External databases for persistent storage

Environment variables and ConfigMaps for configuration

Logging and metrics stored in Kubernetes-compatible backends

Architecture

Functions defined as Kubernetes Custom Resources

Controllers manage deployment, scaling, and routing

Triggers listen to events and invoke functions

Ingress or service routes HTTP requests to functions

Pods execute functions in containerized environments

Rendering Model

Function code packaged in container image

Function deployed as Kubernetes custom resource

Triggers listen for events

Kubernetes schedules function pods

Output sent to response or downstream services

Architectural Patterns

Serverless functions deployed as pods

Event-driven architecture

Kubernetes custom resource-based management

Ingress routing for HTTP triggers

Integration with Kubernetes services and ConfigMaps

Real World Architectures

Event-driven REST APIs on Kubernetes

Background jobs for data processing

IoT data ingestion pipelines

Serverless microservices architecture

Integration with Kafka/NATS for messaging

Design Principles

Kubernetes-native serverless functions

Event-driven and scalable

Lightweight and simple architecture

Multiple runtime support

Declarative deployment with YAML manifests

Scalability Guide

Leverage Kubernetes HPA for auto-scaling

Split functions into small single-purpose units

Use external storage for state persistence

Monitor metrics for performance bottlenecks

Optimize container images for faster cold starts

Migration Guide

Move functions from cloud provider to Kubeless by containerizing code

Define triggers in YAML for Kubernetes

Adapt runtime dependencies to supported runtimes

Configure secrets and ConfigMaps for environment variables

Test triggers and function execution in cluster

Performance Notes

Auto-scaling reduces resource consumption during idle periods

Execution performance depends on container startup time

Lightweight compared to full microservices

Leverages Kubernetes scheduling for efficiency

Monitor and tune resource requests/limits for optimal performance

Security Notes

Use Kubernetes RBAC to control access

Secure secrets with Kubernetes Secrets

HTTPS for HTTP triggers

Network policies to limit traffic

Update runtimes to patch vulnerabilities

Monitoring Analytics

Prometheus metrics exposed via Kubeless

Grafana dashboards for function monitoring

Pod logs via kubectl

Monitor event trigger latency

Track scaling events and resource usage

Code Quality

Write modular functions with single responsibility

Use unit tests for each function

Ensure proper logging and metrics

Document triggers and environment variables

Follow Kubernetes best practices for resources and scaling

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

Troubleshooting

Check function logs with `kubectl logs`

Ensure triggers are correctly configured

Verify runtime compatibility

Check Kubernetes pod status

Confirm network and permissions settings

Testing Guide

Unit test functions locally

Deploy to Kubernetes dev namespace for integration tests

Invoke HTTP triggers using curl or Postman

Test message queue triggers with sample events

Validate scaling under load

Deployment Options

Kubernetes cluster (any provider)

Minikube for local development

Cloud-managed Kubernetes (EKS, GKE, AKS)

Namespace-based multi-tenant deployment

CI/CD pipeline for automated deployment

Tools Ecosystem

Kubeless CLI

kubectl for Kubernetes interaction

Prometheus and Grafana for monitoring

CI/CD tools for function deployment

YAML manifests for declarative configuration

Integrations

HTTP via Ingress or Kubernetes Service

Message queues like Kafka or NATS

Cron jobs for periodic triggers

Kubernetes Secrets and ConfigMaps

Prometheus metrics for observability

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

Challenges

Managing Kubernetes resource configurations

Debugging functions in distributed environment

Optimizing function cold-start performance

Ensuring secure access to triggers and secrets

Monitoring and scaling multiple functions efficiently

Learning Path

Learn Kubernetes basics

Understand serverless concepts

Install Kubeless on local cluster

Deploy functions with HTTP triggers

Integrate functions with event sources

Skill Improvement 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

Interview Questions

What is Kubeless and why use it?

How does Kubeless integrate with Kubernetes?

Which runtimes does Kubeless support?

Explain triggers in Kubeless

Compare Kubeless with AWS Lambda or OpenFaaS

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

Books

Serverless Kubernetes with Kubeless

Kubernetes Patterns and Serverless Architectures

Event-Driven Microservices on Kubernetes

Kubernetes for Developers

Hands-On Serverless with Kubernetes

Tutorials

Deploy your first function with Kubeless

Integrate Kubeless with HTTP triggers

Use message queues with Kubeless functions

Monitor and scale Kubeless functions

Secure functions with Kubernetes secrets

Official Docs

https://kubeless.io/

https://github.com/kubeless/kubeless

Community Links

Kubeless GitHub

Kubernetes Slack channels

Bitnami community forums

StackOverflow Kubeless tag

Serverless Kubernetes community

Community Support

Kubeless GitHub repository

Kubernetes Slack channels

StackOverflow Kubeless questions

Bitnami community forums

Serverless Kubernetes community discussions

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

Future Roadmap

Improved runtime support

Enhanced event source integrations

Better observability and monitoring tools

Community-driven plugins and triggers

Continuous compatibility with latest Kubernetes versions

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

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.

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.

Code Sample Descriptions

1

Simple Python HTTP Function

# kubeless/demo/python-http.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: hello-python
    namespace: default
spec:
    runtime: python3.8
    handler: handler.main
    source: |
        def main(event, context):
        return "Hello Kubeless!"
    events:
        hello-http:
        type: http
        metadata:
        path: /hello
        method: GET

A simple Kubeless YAML configuration to deploy a Python HTTP function.

Let’s Try →
2

Node.js HTTP Function

# kubeless/demo/node-http.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: hello-node
    namespace: default
spec:
    runtime: nodejs14
    handler: handler.main
    source: |
        module.exports.main = (event, context) => {
        return 'Hello from Node.js!';
        };
    events:
        hello-http:
        type: http
        metadata:
        path: /node
        method: GET

Kubeless function using Node.js runtime to handle HTTP requests.

Let’s Try →
3

Go HTTP Function

# kubeless/demo/go-http.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: hello-go
    namespace: default
spec:
    runtime: go1.15
    handler: handler.Hello
    source: |
        package handler
        import (
        "fmt"
        "github.com/kubeless/kubeless/pkg/functions"
        )
        func Hello(event functions.Event, context functions.Context) string {
        return fmt.Sprintf("Hello from Go!")
        }
    events:
        hello-http:
        type: http
        metadata:
        path: /go
        method: GET

Kubeless function using Go runtime to handle HTTP requests.

Let’s Try →
4

Ruby HTTP Function

# kubeless/demo/ruby-http.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: hello-ruby
    namespace: default
spec:
    runtime: ruby2.5
    handler: handler.main
    source: |
        def main(event, context)
        "Hello from Ruby!"
        end
    events:
        hello-http:
        type: http
        metadata:
        path: /ruby
        method: GET

Deploy a simple Ruby HTTP function with Kubeless.

Let’s Try →
5

Python Scheduled Function

# kubeless/demo/python-cron.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: scheduled-python
    namespace: default
spec:
    runtime: python3.8
    handler: handler.main
    source: |
        def main(event, context):
        print("Scheduled Hello!")
    events:
        schedule-event:
        type: scheduled
        metadata:
        schedule: "*/5 * * * *"

Python function triggered on a schedule using a CronJob.

Let’s Try →
6

Node.js Kafka Function

# kubeless/demo/node-kafka.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: kafka-node
    namespace: default
spec:
    runtime: nodejs14
    handler: handler.main
    source: |
        module.exports.main = (event, context) => {
        console.log('Received Kafka message:', event.body);
        };
    events:
        kafka-event:
        type: kafka
        metadata:
        topic: test-topic
        broker: localhost:9092

Node.js function triggered by a Kafka message.

Let’s Try →
7

Python RabbitMQ Function

# kubeless/demo/python-rabbitmq.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: rabbit-python
    namespace: default
spec:
    runtime: python3.8
    handler: handler.main
    source: |
        def main(event, context):
        print("Received RabbitMQ message:", event.body)
    events:
        rabbit-event:
        type: rabbitmq
        metadata:
        exchange: test-exchange
        queue: test-queue

Python function triggered by RabbitMQ messages.

Let’s Try →
8

Python CloudEvent Function

# kubeless/demo/python-cloudevent.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: cloudevent-python
    namespace: default
spec:
    runtime: python3.8
    handler: handler.main
    source: |
        def main(event, context):
        print("CloudEvent received:", event)
    events:
        cloudevent:
        type: cloudevent
        metadata:
        source: /source
        type: com.example.event

Python function triggered by CloudEvents.

Let’s Try →
9

Python HTTP Function with 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: GET

Python HTTP function that uses additional dependencies.

Let’s Try →
10

Node.js Cron Function

# kubeless/demo/node-cron.yaml
apiVersion: kubeless.io/v1beta1
kind: Function
metadata:
    name: scheduled-node
    namespace: default
spec:
    runtime: nodejs14
    handler: handler.main
    source: |
        module.exports.main = (event, context) => {
        console.log('Scheduled Node.js function executed!');
        };
    events:
        schedule-event:
        type: scheduled
        metadata:
        schedule: "0 * * * *"

Node.js function triggered on a schedule using Cron.

Let’s Try →

Frequently Asked Questions about Kubeless

What is Kubeless?

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.

What are the primary use cases for Kubeless?

Event-driven microservices. Serverless REST APIs. Background tasks and cron jobs. Data processing pipelines. Integrating Kubernetes-native functions into CI/CD workflows

What are the strengths of Kubeless?

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

What are the limitations of Kubeless?

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

How can I practice Kubeless typing speed?

CodeSpeedTest offers 10+ real Kubeless code examples for typing practice. You can measure your WPM, track accuracy, and improve your coding speed with guided exercises.

Learn Other Programming Languages

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