Overview

Azure Functions

Stacks785

Followers705

Votes62

Knative

Stacks86

Followers342

Votes21

GitHub Stars5.9K

Forks1.2K

Azure Functions vs Knative: What are the differences?

Deployment Options: Azure Functions provides a fully managed, serverless environment for executing functions, which means that developers do not have to worry about infrastructure management. On the other hand, Knative offers a platform for running serverless workloads on Kubernetes. This allows for more control and flexibility in terms of deployment options, as Kubernetes provides a rich set of features for managing containers.
Programming Languages: Azure Functions supports a wide range of programming languages, including C#, JavaScript, Java, Python, PowerShell, and TypeScript. Knative is language-agnostic and can run functions written in any language as long as it can run within a container. This allows developers to use the programming language of their choice when using Knative.
Scalability: Azure Functions automatically scales based on the number of events or requests, ensuring that there are enough resources to handle the workload. Knative also provides auto-scaling capabilities, allowing functions to scale up and down based on demand. However, Knative offers more fine-grained control over the scaling behavior by allowing developers to define custom scaling policies.
Event Triggers: Azure Functions provides a variety of event triggers, such as HTTP requests, timers, message queues, and database changes, that can trigger the execution of a function. Knative also supports event-driven programming, allowing functions to be triggered by various events. However, Knative provides a more extensible framework for defining custom event sources, allowing developers to create their own triggers.
Integration: Azure Functions integrates seamlessly with other Azure services, such as Azure Blob Storage, Azure Cosmos DB, and Azure Event Grid, making it easy to build serverless applications that leverage various Azure services. Knative can be integrated with any service that can send or receive events, allowing functions to interact with a wide range of external systems.
Pricing Model: Azure Functions offers a consumption-based pricing model, where developers only pay for the actual execution time and resources consumed by their functions. Knative, being an open-source project, does not have a built-in pricing model and the costs associated with running Knative workloads depend on the underlying infrastructure.

In summary, Azure Functions and Knative differ in terms of deployment options, programming languages, scalability, event triggers, integration capabilities, and pricing models. While Azure Functions provides a fully managed serverless environment with extensive integration options within the Azure ecosystem, Knative offers more control over deployment and scaling, supports any programming language, and can integrate with any event source.

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Advice on Azure Functions, Knative

Mark

Nov 2, 2020

Needs adviceon

Microsoft 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!

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Detailed Comparison

Azure Functions	Knative
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.	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
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	Serving - Scale to zero, request-driven compute model; Build - Cloud-native source to container orchestration; Events - Universal subscription, delivery and management of events; Serverless add-on on GKE - Enable GCP managed serverless stack on Kubernetes
Statistics
GitHub Stars -	GitHub Stars 5.9K
GitHub Forks -	GitHub Forks 1.2K
Stacks 785	Stacks 86
Followers 705	Followers 342
Votes 62	Votes 21
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 5 Portability 4 Autoscaling 3 On top of Kubernetes 3 Secure Eventing 3 Eventing
Integrations
Azure DevOps Java Bitbucket Node.js Microsoft Azure GitHub Visual Studio Code JavaScript Azure Cosmos DB C#	Google Kubernetes Engine

What are some alternatives to Azure Functions, Knative?

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

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

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

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

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Nuclio

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

Apache OpenWhisk

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.

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

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

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.