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Azure Functions
Azure Functions

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Effe
Effe

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Azure Functions vs Effe: What are the differences?

What is 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.

What is Effe? A building block for an open source AWS lambda. Effe is an extremely simple building block with which to build a "server-less" architecture. This is a building block, operates on the level of a single lambda function.

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

Effe is an open source tool with 231 GitHub stars and 7 GitHub forks. Here's a link to Effe'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 Effe?

Effe is an extremely simple building block with which to build a "server-less" architecture. This is a building block, operates on the level of a single lambda function.
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Why do developers choose Azure Functions?
Why do developers choose Effe?
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        What tools integrate with Azure Functions?
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          What are some alternatives to Azure Functions and Effe?
          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 Effe
          Kestas Barzdaitis
          Kestas Barzdaitis
          Entrepreneur & Engineer · | 12 upvotes · 46.1K views
          atCodeFactorCodeFactor
          Google Cloud Functions
          Google Cloud Functions
          Azure Functions
          Azure Functions
          AWS Lambda
          AWS Lambda
          Docker
          Docker
          Google Compute Engine
          Google Compute Engine
          Microsoft Azure
          Microsoft Azure
          Amazon EC2
          Amazon EC2
          CodeFactor.io
          CodeFactor.io
          Kubernetes
          Kubernetes
          #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 · 50.8K views
          atEvojamEvojam
          Azure Functions
          Azure Functions
          Firebase
          Firebase
          AWS Lambda
          AWS Lambda
          Serverless
          Serverless

          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 · 14.7K views
          atChecklyHQChecklyHQ
          Node.js
          Node.js
          Google Cloud Functions
          Google Cloud Functions
          Azure Functions
          Azure Functions
          Amazon CloudWatch
          Amazon CloudWatch
          Serverless
          Serverless
          AWS Lambda
          AWS Lambda

          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 Effe
          Review ofAzure FunctionsAzure Functions

          Poor developer experience

          How developers use Azure Functions and Effe
          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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