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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. Apache OpenWhisk vs Kubeless

Apache OpenWhisk vs Kubeless

OverviewComparisonAlternatives

Overview

Kubeless
Kubeless
Stacks39
Followers195
Votes0
Apache OpenWhisk
Apache OpenWhisk
Stacks58
Followers149
Votes7

Apache OpenWhisk vs Kubeless: What are the differences?

Introduction

In this markdown code, we will discuss the key differences between Apache OpenWhisk and Kubeless, two popular serverless platforms.

  1. Execution Model: Apache OpenWhisk follows an event-driven execution model, where functions are triggered by events or time-based intervals. Kubeless, on the other hand, follows a function-driven execution model, where functions are directly invoked by external triggers or APIs.

  2. Language Support: Apache OpenWhisk supports a wide range of programming languages, including JavaScript, Python, Java, Ruby, Swift, and more. Kubeless primarily focuses on providing support for Python and Node.js, although it also allows the execution of custom Docker containers to support other languages.

  3. Infrastructure: Apache OpenWhisk is built on a microservices architecture, leveraging Docker containers and Kubernetes for scalability and resiliency. Kubeless is also based on Kubernetes, making it simpler to deploy and manage functions within a Kubernetes cluster.

  4. Event Sources: Apache OpenWhisk offers a comprehensive set of built-in event sources, such as HTTP, timer, message queue, database, and IoT devices. Kubeless provides a pluggable architecture, allowing users to connect to various event sources and trigger functions based on events generated by those sources.

  5. Ecosystem Integration: Apache OpenWhisk has a strong integration with other cloud services, such as IBM Cloud, Amazon Web Services (AWS), and Azure. It provides seamless integration with these services, enabling developers to leverage their existing cloud infrastructure. Kubeless, being Kubernetes-based, can easily integrate with other Kubernetes-native tools and services.

  6. Community Support: Apache OpenWhisk has a larger and more active community compared to Kubeless. It has a diverse user base and a wide range of contributors, resulting in better support, documentation, and continuous improvement. Kubeless, although relatively newer, also has an active community, but with fewer resources and contributors.

In summary, Apache OpenWhisk and Kubeless differ in their execution models, language support, infrastructure, event sources, ecosystem integration, and community support. Apache OpenWhisk offers a more versatile and feature-rich platform with broader language support and extensive integration options. Kubeless, on the other hand, is simpler to deploy and manage within a Kubernetes environment, with a narrower focus on Python and Node.js. Choose the platform that best fits your requirements and resources.

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Detailed Comparison

Kubeless
Kubeless
Apache OpenWhisk
Apache OpenWhisk

Kubeless is a Kubernetes native serverless Framework. Kubeless supports both HTTP and event based functions triggers. It has a serverless plugin, a graphical user interface and multiple runtimes, including Python and Node.js.

OpenWhisk is an open source serverless platform. It is enterprise grade and accessible to all developers thanks to its superior programming model and tooling. It powers IBM Cloud Functions, Adobe I/O Runtime, Naver, Nimbella among others.

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Serverless functions;FaaS;Fine-grained resource consumption;Use any language;Containers as functions; service;Functions-as-a-Service;Function composition;Step Functions;Docker;Kubernetes;Open source community;Apache
Statistics
Stacks
39
Stacks
58
Followers
195
Followers
149
Votes
0
Votes
7
Pros & Cons
No community feedback yet
Pros
  • 4
    You are not tied to a provider. IBM available however
  • 3
    Still exploring... its just intresting
Integrations
Docker
Docker
Kafka
Kafka
Zookeeper
Zookeeper
Serverless
Serverless
Kubernetes
Kubernetes
Node.js
Node.js
Visual Studio Code
Visual Studio Code
JavaScript
JavaScript
Python
Python
npm
npm
Kubernetes
Kubernetes
Docker
Docker
Swift
Swift
Java
Java
Slack
Slack

What are some alternatives to Kubeless, Apache OpenWhisk?

AWS Lambda

AWS Lambda

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

Azure Functions

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Serverless

Serverless

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

Google Cloud Functions

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

OpenFaaS

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Nuclio

Nuclio

nuclio is portable across IoT devices, laptops, on-premises datacenters and cloud deployments, eliminating cloud lock-ins and enabling hybrid solutions.

Cloud Functions for Firebase

Cloud Functions for Firebase

Cloud Functions for Firebase lets you create functions that are triggered by Firebase products, such as changes to data in the Realtime Database, uploads to Cloud Storage, new user sign ups via Authentication, and conversion events in Analytics.

AWS Batch

AWS Batch

It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.

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