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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. AWS Lambda vs Azure Functions vs Knative

AWS Lambda vs Azure Functions vs Knative

OverviewDecisionsComparisonAlternatives

Overview

AWS Lambda
AWS Lambda
Stacks26.0K
Followers18.8K
Votes432
Azure Functions
Azure Functions
Stacks785
Followers705
Votes62
Knative
Knative
Stacks86
Followers342
Votes21
GitHub Stars5.9K
Forks1.2K

AWS Lambda vs Azure Functions vs Knative: What are the differences?

<Write Introduction here>
  1. Pricing Structure: AWS Lambda charges based on the number of requests and the duration of computation, while Azure Functions has a similar model but charges for executions and resource consumption. Knative, on the other hand, is an open-source service that can run on any Kubernetes platform with no additional cost other than the underlying infrastructure charges.

  2. Integrated Development Environment (IDE) Support: AWS Lambda has robust support for AWS Toolkit for Visual Studio and AWS Toolkit for JetBrains, making it favorable for developers using these tools. Azure Functions, as part of the Azure ecosystem, seamlessly integrates with Visual Studio and Visual Studio Code, providing a rich development experience. Knative, being Kubernetes-native, can be developed using any IDE supporting Kubernetes, offering flexibility in the choice of development environment.

  3. Programming Languages: AWS Lambda supports more programming languages natively, including Node.js, Python, Java, and Ruby, providing developers with a variety of options. Azure Functions also supports multiple languages like C#, F#, JavaScript, Python, and more, catering to a vast range of developer preferences. Knative supports any language that can run on a Kubernetes container, allowing developers to use their language of choice without constraints.

  4. Deployment Flexibility: AWS Lambda restricts deployment options to AWS infrastructure, limiting deployment flexibility for organizations with a multi-cloud strategy. Azure Functions, although primarily for Azure deployment, has better integration with Azure DevOps, enabling streamlined deployment pipelines. Knative, with its Kubernetes compatibility, offers deployment flexibility on any cloud provider or on-premises, promoting portability and reducing vendor lock-in.

  5. Scalability and Concurrency: AWS Lambda automatically scales based on incoming traffic, with concurrent execution limits configurable to prevent resource exhaustion. Azure Functions also scales dynamically with the option to adjust concurrency settings to optimize performance. Knative provides auto-scaling capabilities based on actual usage, ensuring efficient resource allocation and utilization without manual intervention.

  6. Ecosystem and Integrations: AWS Lambda has a rich ecosystem of AWS services and integrations, facilitating seamless interaction with various cloud resources. Azure Functions benefits from tight integration with Azure services like Azure Storage, Azure Cosmos DB, and more, enabling easy integration with existing Azure solutions. Knative, being Kubernetes-based, leverages the extensive Kubernetes ecosystem, allowing integration with a wide range of tools and services within the Kubernetes environment.

In Summary, AWS Lambda, Azure Functions, and Knative differ in pricing, IDE support, programming language compatibility, deployment flexibility, scalability, and ecosystems, offering varying capabilities to meet diverse development and deployment requirements.

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Advice on AWS Lambda, Azure Functions, Knative

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
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

AWS Lambda
AWS Lambda
Azure Functions
Azure Functions
Knative
Knative

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 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

Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model
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
-
GitHub Stars
5.9K
GitHub Forks
-
GitHub Forks
-
GitHub Forks
1.2K
Stacks
26.0K
Stacks
785
Stacks
86
Followers
18.8K
Followers
705
Followers
342
Votes
432
Votes
62
Votes
21
Pros & Cons
Pros
  • 129
    No infrastructure
  • 83
    Cheap
  • 70
    Quick
  • 59
    Stateless
  • 47
    No deploy, no server, great sleep
Cons
  • 7
    Cant execute ruby or go
  • 3
    Compute time limited
  • 1
    Can't execute PHP w/o significant effort
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
    No persistent (writable) file system available
  • 1
    Sporadic server & language runtime issues
  • 1
    Poor support for Linux environments
  • 1
    Not suited for long-running applications
Pros
  • 5
    Portability
  • 4
    Autoscaling
  • 3
    Open source
  • 3
    Eventing
  • 3
    On top of Kubernetes
Integrations
No integrations available
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#
Google Kubernetes Engine
Google Kubernetes Engine

What are some alternatives to AWS Lambda, Azure Functions, Knative?

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

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.

Apache OpenWhisk

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

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.

Lambada Framework

Lambada Framework

Lambada framework is a REST framework that implements JAX-RS API and lets you deploy your applications to AWS Lambda and API Gateway in a serverless fashion. With Lambada you can migrate the existing JAX-RS applications with a very little effort and build scalable applications without having to deal with servers.

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