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

Apache OpenWhisk vs Azure Functions

OverviewDecisionsComparisonAlternatives

Overview

Azure Functions
Azure Functions
Stacks785
Followers705
Votes62
Apache OpenWhisk
Apache OpenWhisk
Stacks58
Followers149
Votes7

Apache OpenWhisk vs Azure Functions: What are the differences?

Apache OpenWhisk and Azure Functions are both serverless computing platforms that allow developers to build and run event-driven applications without the need to provision or manage the underlying infrastructure. While both platforms have similar goals, there are several key differences between Apache OpenWhisk and Azure Functions that set them apart from each other.
  1. Language Support: One key difference between Apache OpenWhisk and Azure Functions is the language support they offer. OpenWhisk supports a wide range of programming languages including JavaScript, Python, Swift, and PHP. On the other hand, Azure Functions offers support for languages such as C#, Java, JavaScript, PowerShell, and TypeScript. This difference in language support allows developers to choose the language they are most comfortable with for building their serverless applications.

  2. Event Sources: Another difference between OpenWhisk and Azure Functions lies in their event source integrations. OpenWhisk allows developers to trigger functions based on various event sources such as HTTP requests, timers, message queues, and database updates. In contrast, Azure Functions provides a broader range of event source integrations including HTTP requests, timers, message queues, databases, IoT devices, and more. This wider range of event sources in Azure Functions gives developers more flexibility and options when it comes to triggering their serverless functions.

  3. Scaling Model: In terms of scaling, there is a slight difference between OpenWhisk and Azure Functions. OpenWhisk scales the execution environment by creating new instances of the runtime to handle increased load. This means that each individual function is scaled independently based on its usage. On the other hand, Azure Functions uses a more granular scaling model called "Consumption Plan" where functions are automatically scaled based on the number of incoming requests. This scaling model in Azure Functions allows for more efficient resource utilization, as it can dynamically scale the entire function app rather than each individual function.

  4. Development and Deployment: OpenWhisk and Azure Functions also differ in terms of development and deployment options. OpenWhisk provides a command-line interface (CLI) as well as a web-based graphical user interface (GUI) for managing functions and deployments. It also allows developers to deploy functions using a variety of methods including direct code upload, packaging functions into containers, or using a source code repository. Azure Functions, on the other hand, provides a rich development experience through its integrated development environment (IDE) in Azure Portal. It also offers seamless integration with Azure DevOps for continuous integration and deployment of serverless functions.

  5. Pricing Model: OpenWhisk and Azure Functions have different pricing models. OpenWhisk pricing is based on the number of invocations, compute time, and memory usage, with separate pricing for each programming language. On the other hand, Azure Functions offers a consumption-based pricing model where users only pay for the actual number of executions and the associated resources used by the function. This pay-per-use pricing model in Azure Functions can be more cost-effective for applications with variable workloads and intermittent usage patterns.

  6. Community and Ecosystem: The last key difference between OpenWhisk and Azure Functions lies in their respective communities and ecosystems. OpenWhisk is an open-source platform that is supported by a vibrant community of developers and contributors. It has a wide range of community-built integrations and extensions, which can be beneficial for developers looking for additional functionalities and customizations. Azure Functions, being a part of the larger Azure ecosystem, benefits from the extensive set of Azure services and integrations available. It also has a strong community and marketplace, offering pre-built templates and extensions that can expedite the development process.

In Summary, the key differences between Apache OpenWhisk and Azure Functions lie in their language support, event source integrations, scaling models, development and deployment options, pricing models, and community ecosystems.

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Advice on Azure Functions, Apache OpenWhisk

Mark
Mark

Nov 2, 2020

Needs adviceonMicrosoft AzureMicrosoft Azure

Need advice on what platform, systems and tools to use.

Evaluating whether to start a new digital business for which we will need to build a website that handles all traffic. Website only right now. May add smartphone apps later. No desktop app will ever be added. Website to serve various countries and languages. B2B and B2C type customers. Need to handle heavy traffic, be low cost, and scale well.

We are open to either build it on AWS or on Microsoft Azure.

Apologies if I'm leaving out some info. My first post. :) Thanks in advance!

133k views133k
Comments

Detailed Comparison

Azure Functions
Azure Functions
Apache OpenWhisk
Apache OpenWhisk

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.

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.

Easily schedule event-driven tasks across services;Expose Functions as HTTP API endpoints;Scale Functions based on customer demand;Develop how you want, using a browser-based UI or existing tools;Get continuous deployment, remote debugging, and authentication out of the box
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
785
Stacks
58
Followers
705
Followers
149
Votes
62
Votes
7
Pros & Cons
Pros
  • 14
    Pay only when invoked
  • 11
    Great developer experience for C#
  • 9
    Multiple languages supported
  • 7
    Great debugging support
  • 5
    Can be used as lightweight https service
Cons
  • 1
    Poor support for Linux environments
  • 1
    Sporadic server & language runtime issues
  • 1
    Not suited for long-running applications
  • 1
    No persistent (writable) file system available
Pros
  • 4
    You are not tied to a provider. IBM available however
  • 3
    Still exploring... its just intresting
Integrations
Azure DevOps
Azure DevOps
Java
Java
Bitbucket
Bitbucket
Node.js
Node.js
Microsoft Azure
Microsoft Azure
GitHub
GitHub
Visual Studio Code
Visual Studio Code
JavaScript
JavaScript
Azure Cosmos DB
Azure Cosmos DB
C#
C#
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 Azure Functions, 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.

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.

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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