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Azure Functions
Azure Functions

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OpenFaaS
OpenFaaS

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Azure Functions vs OpenFaaS: What are the differences?

Azure Functions: Listen and react to events across your stack. 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; OpenFaaS: Serverless Functions Made Simple for Kubernetes and Docker. Serverless Functions Made Simple for Docker and Kubernetes.

Azure Functions and OpenFaaS belong to "Serverless / Task Processing" category of the tech stack.

OpenFaaS is an open source tool with 14.8K GitHub stars and 1.17K GitHub forks. Here's a link to OpenFaaS's open source repository on GitHub.

- No public GitHub repository available -

What is 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.

What is OpenFaaS?

Serverless Functions Made Simple for Docker and Kubernetes
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Why do developers choose Azure Functions?
Why do developers choose OpenFaaS?

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      What are some alternatives to Azure Functions and OpenFaaS?
      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.
      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.
      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.
      Google Cloud Functions
      Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running
      Apex
      Apex is a small tool for deploying and managing AWS Lambda functions. With shims for languages not yet supported by Lambda, you can use Golang out of the box.
      See all alternatives
      Decisions about Azure Functions and OpenFaaS
      Kestas Barzdaitis
      Kestas Barzdaitis
      Entrepreneur & Engineer · | 14 upvotes · 79.6K views
      atCodeFactorCodeFactor
      Kubernetes
      Kubernetes
      CodeFactor.io
      CodeFactor.io
      Amazon EC2
      Amazon EC2
      Microsoft Azure
      Microsoft Azure
      Google Compute Engine
      Google Compute Engine
      Docker
      Docker
      AWS Lambda
      AWS Lambda
      Azure Functions
      Azure Functions
      Google Cloud Functions
      Google Cloud Functions
      #SAAS
      #IAAS
      #Containerization
      #Autoscale
      #Startup
      #Automation
      #Machinelearning
      #AI
      #Devops

      CodeFactor being a #SAAS product, our goal was to run on a cloud-native infrastructure since day one. We wanted to stay product focused, rather than having to work on the infrastructure that supports the application. We needed a cloud-hosting provider that would be reliable, economical and most efficient for our product.

      CodeFactor.io aims to provide an automated and frictionless code review service for software developers. That requires agility, instant provisioning, autoscaling, security, availability and compliance management features. We looked at the top three #IAAS providers that take up the majority of market share: Amazon's Amazon EC2 , Microsoft's Microsoft Azure, and Google Compute Engine.

      AWS has been available since 2006 and has developed the most extensive services ant tools variety at a massive scale. Azure and GCP are about half the AWS age, but also satisfied our technical requirements.

      It is worth noting that even though all three providers support Docker containerization services, GCP has the most robust offering due to their investments in Kubernetes. Also, if you are a Microsoft shop, and develop in .NET - Visual Studio Azure shines at integration there and all your existing .NET code works seamlessly on Azure. All three providers have serverless computing offerings (AWS Lambda, Azure Functions, and Google Cloud Functions). Additionally, all three providers have machine learning tools, but GCP appears to be the most developer-friendly, intuitive and complete when it comes to #Machinelearning and #AI.

      The prices between providers are competitive across the board. For our requirements, AWS would have been the most expensive, GCP the least expensive and Azure was in the middle. Plus, if you #Autoscale frequently with large deltas, note that Azure and GCP have per minute billing, where AWS bills you per hour. We also applied for the #Startup programs with all three providers, and this is where Azure shined. While AWS and GCP for startups would have covered us for about one year of infrastructure costs, Azure Sponsorship would cover about two years of CodeFactor's hosting costs. Moreover, Azure Team was terrific - I felt that they wanted to work with us where for AWS and GCP we were just another startup.

      In summary, we were leaning towards GCP. GCP's advantages in containerization, automation toolset, #Devops mindset, and pricing were the driving factors there. Nevertheless, we could not say no to Azure's financial incentives and a strong sense of partnership and support throughout the process.

      Bottom line is, IAAS offerings with AWS, Azure, and GCP are evolving fast. At CodeFactor, we aim to be platform agnostic where it is practical and retain the flexibility to cherry-pick the best products across providers.

      See more
      Michal Nowak
      Michal Nowak
      Co-founder at Evojam · | 7 upvotes · 74.5K views
      atEvojamEvojam
      Serverless
      Serverless
      AWS Lambda
      AWS Lambda
      Firebase
      Firebase
      Azure Functions
      Azure Functions

      In a couple of recent projects we had an opportunity to try out the new Serverless approach to building web applications. It wasn't necessarily a question if we should use any particular vendor but rather "if" we can consider serverless a viable option for building apps. Obviously our goal was also to get a feel for this technology and gain some hands-on experience.

      We did consider AWS Lambda, Firebase from Google as well as Azure Functions. Eventually we went with AWS Lambdas.

      PROS
      • No servers to manage (obviously!)
      • Limited fixed costs – you pay only for used time
      • Automated scaling and balancing
      • Automatic failover (or, at this level of abstraction, no failover problem at all)
      • Security easier to provide and audit
      • Low overhead at the start (with the certain level of knowledge)
      • Short time to market
      • Easy handover - deployment coupled with code
      • Perfect choice for lean startups with fast-paced iterations
      • Augmentation for the classic cloud, server(full) approach
      CONS
      • Not much know-how and best practices available about structuring the code and projects on the market
      • Not suitable for complex business logic due to the risk of producing highly coupled code
      • Cost difficult to estimate (helpful tools: serverlesscalc.com)
      • Difficulty in migration to other platforms (Vendor lock⚠️)
      • Little engineers with experience in serverless on the job market
      • Steep learning curve for engineers without any cloud experience

      More details are on our blog: https://evojam.com/blog/2018/12/5/should-you-go-serverless-meet-the-benefits-and-flaws-of-new-wave-of-cloud-solutions I hope it helps 🙌 & I'm curious of your experiences.

      See more
      Tim Nolet
      Tim Nolet
      Founder, Engineer & Dishwasher at Checkly · | 5 upvotes · 26.6K views
      atChecklyHQChecklyHQ
      AWS Lambda
      AWS Lambda
      Serverless
      Serverless
      Amazon CloudWatch
      Amazon CloudWatch
      Azure Functions
      Azure Functions
      Google Cloud Functions
      Google Cloud Functions
      Node.js
      Node.js

      AWS Lambda Serverless Amazon CloudWatch Azure Functions Google Cloud Functions Node.js

      In the last year or so, I moved all Checkly monitoring workloads to AWS Lambda. Here are some stats:

      • We run three core functions in all AWS regions. They handle API checks, browser checks and setup / teardown scripts. Check our docs to find out what that means.
      • All functions are hooked up to SNS topics but can also be triggered directly through AWS SDK calls.
      • The busiest function is a plumbing function that forwards data to our database. It is invoked anywhere between 7000 and 10.000 times per hour with an average duration of about 179 ms.
      • We run separate dev and test versions of each function in each region.

      Moving all this to AWS Lambda took some work and considerations. The blog post linked below goes into the following topics:

      • Why Lambda is an almost perfect match for SaaS. Especially when you're small.
      • Why I don't use a "big" framework around it.
      • Why distributed background jobs triggered by queues are Lambda's raison d'être.
      • Why monitoring & logging is still an issue.

      https://blog.checklyhq.com/how-i-made-aws-lambda-work-for-my-saas/

      See more
      Interest over time
      Reviews of Azure Functions and OpenFaaS
      Review ofAzure FunctionsAzure Functions

      Poor developer experience

      How developers use Azure Functions and OpenFaaS
      Avatar of Yonas B.
      Yonas B. uses Azure FunctionsAzure Functions

      I used Azure functions as part of an integration service when creating a bulk insert module in azure.

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