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

Apache OpenWhisk vs Serverless

OverviewDecisionsComparisonAlternatives

Overview

Serverless
Serverless
Stacks2.2K
Followers1.2K
Votes28
GitHub Stars46.9K
Forks5.7K
Apache OpenWhisk
Apache OpenWhisk
Stacks58
Followers149
Votes7

Apache OpenWhisk vs Serverless: What are the differences?

Apache OpenWhisk and Serverless framework are popular platforms for building and deploying serverless applications. Below are key differences between Apache OpenWhisk and Serverless:

  1. Architecture: Apache OpenWhisk follows a distributed architecture where each function runs in its container, providing more control and isolation. In contrast, Serverless framework uses a centralized architecture with the entire code base deployed together, simplifying management but potentially leading to resource sharing issues.

  2. Language Support: Apache OpenWhisk supports a wider range of programming languages, including Node.js, Python, Java, and Swift. On the other hand, the Serverless framework primarily focuses on Node.js and Python, with support for other languages through plugins.

  3. Community and Ecosystem: Apache OpenWhisk has a larger community and ecosystem due to its open-source nature and backing by the Apache Software Foundation. Serverless, while also open-source, has a smaller community but offers more integrations with third-party services and providers.

  4. Vendor Lock-in: Using Apache OpenWhisk allows for a more vendor-neutral approach as it can be deployed on various cloud providers or on-premises. Serverless framework, however, may lead to vendor lock-in since it is tightly integrated with specific cloud providers like AWS, Azure, and Google Cloud.

  5. Scalability and Performance: Apache OpenWhisk provides more flexibility in scaling functions individually, optimizing resources, and potentially improving performance. Serverless framework, while offering auto-scaling capabilities, may not provide the same level of fine-tuning for performance optimization.

  6. Workflow Automation: Apache OpenWhisk includes a built-in visual editor called Composer for composing complex workflows, whereas Serverless framework relies more on custom scripts and configurations for workflow automation, making it potentially more complex for developers.

In Summary, Apache OpenWhisk and Serverless differ in architecture, language support, community size, vendor lock-in, scalability, and workflow automation approaches.

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Advice on Serverless, Apache OpenWhisk

Tim
Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceonHerokuHerokuAWS LambdaAWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

  • Developer Experience trumps everything.
  • AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
  • If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

  • Pure, uncut, self hosted Kubernetes — way too much complexity
  • Managed Kubernetes in various flavors — still too much complexity
  • Zeit — Maybe, but no Docker support
  • Elastic Beanstalk — Maybe, bit old but does the job
  • Heroku
  • Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

  • Developer Experience / DX 🤓
  • Ops Experience / OX 🐂 (?)
  • Cost 💵
  • Lock in 🔐

Read the full post linked below for all details

357k views357k
Comments

Detailed Comparison

Serverless
Serverless
Apache OpenWhisk
Apache OpenWhisk

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.

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.

-
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
GitHub Stars
46.9K
GitHub Stars
-
GitHub Forks
5.7K
GitHub Forks
-
Stacks
2.2K
Stacks
58
Followers
1.2K
Followers
149
Votes
28
Votes
7
Pros & Cons
Pros
  • 14
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 3
    Lower cost
  • 1
    3. Simplified Management for developers to focus on cod
  • 1
    Openwhisk
Pros
  • 4
    You are not tied to a provider. IBM available however
  • 3
    Still exploring... its just intresting
Integrations
Azure Functions
Azure Functions
AWS Lambda
AWS Lambda
Amazon API Gateway
Amazon API Gateway
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 Serverless, 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.

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.

Fission

Fission

Write short-lived functions in any language, and map them to HTTP requests (or other event triggers). Deploy functions instantly with one command. There are no containers to build, and no Docker registries to manage.

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