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

AWS Lambda vs OpenFaaS

OverviewDecisionsComparisonAlternatives

Overview

AWS Lambda
AWS Lambda
Stacks26.0K
Followers18.8K
Votes432
OpenFaaS
OpenFaaS
Stacks54
Followers234
Votes17
GitHub Stars26.0K
Forks2.0K

AWS Lambda vs OpenFaaS: What are the differences?

Key Differences between AWS Lambda and OpenFaaS

AWS Lambda and OpenFaaS are both serverless computing platforms, but they have some key differences that set them apart.

  1. Deployment and Hosting: AWS Lambda is a fully managed service provided by Amazon Web Services, which means that AWS takes care of the underlying infrastructure and hosting. On the other hand, OpenFaaS is an open-source framework that allows you to deploy and host functions on your own infrastructure or on third-party cloud providers.

  2. Programming Languages and Runtimes: AWS Lambda supports a wide range of programming languages, including Node.js, Java, Python, and more. It also allows you to use custom runtimes to run functions in any language. OpenFaaS also supports multiple languages, but it relies on Docker containers, which means you can use any programming language supported by Docker.

  3. Scaling: AWS Lambda automatically scales the number of function instances based on the incoming request volume, allowing you to handle large loads without manual intervention. OpenFaaS also supports scaling, but it requires manual configuration and setup. You need to specify the desired number of replicas to handle the load.

  4. Vendor Lock-in: AWS Lambda is a proprietary service offered by Amazon, which means it ties you to the AWS ecosystem. If you develop functions using Lambda, it may be challenging to migrate them to other cloud providers or hosting platforms. OpenFaaS, being open-source, provides more flexibility in terms of vendor lock-in, as you can deploy functions on different cloud providers or your own infrastructure.

  5. Community and Ecosystem: AWS Lambda has a large and well-established community, along with a comprehensive ecosystem of services and tools provided by AWS. OpenFaaS also has a growing community and ecosystem, but it may not be as extensive as AWS Lambda. Depending on your requirements and preferences, the size and maturity of the community and ecosystem can be an important factor to consider.

  6. Pricing Model: The pricing model for AWS Lambda is based on the number of requests and the compute time consumed by the functions. You only pay for the actual usage of the functions. OpenFaaS, being a self-hosted solution, allows you to choose your infrastructure and hosting providers, which may have different pricing models. It provides more flexibility in terms of cost optimization.

In summary, the key differences between AWS Lambda and OpenFaaS include deployment and hosting, programming languages and runtimes, scaling, vendor lock-in, community and ecosystem, and pricing model.

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Advice on AWS Lambda, OpenFaaS

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

AWS Lambda
AWS Lambda
OpenFaaS
OpenFaaS

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.

Serverless Functions Made Simple for Docker and Kubernetes

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
-
Statistics
GitHub Stars
-
GitHub Stars
26.0K
GitHub Forks
-
GitHub Forks
2.0K
Stacks
26.0K
Stacks
54
Followers
18.8K
Followers
234
Votes
432
Votes
17
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
  • 5
    Open source
  • 4
    Ease
  • 3
    Autoscaling
  • 2
    Documentation
  • 2
    Community
Integrations
No integrations available
Kubernetes
Kubernetes
Docker
Docker

What are some alternatives to AWS Lambda, OpenFaaS?

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

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.

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