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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.
Azure Functions is a tool in the Serverless / Task Processing category of a tech stack.

Who uses Azure Functions?

Companies
46 companies reportedly use Azure Functions in their tech stacks, including Property With Potential, OneWire, and Veris.

Developers
110 developers on StackShare have stated that they use Azure Functions.

Azure Functions Integrations

JavaScript, GitHub, Node.js, Java, and Visual Studio Code are some of the popular tools that integrate with Azure Functions. Here's a list of all 14 tools that integrate with Azure Functions.

Why developers like Azure Functions?

Here’s a list of reasons why companies and developers use Azure Functions
Azure Functions Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Azure Functions in their tech stack.

Kestas Barzdaitis
Kestas Barzdaitis
Entrepreneur & Engineer · | 12 upvotes · 32.1K 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.

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Farzad Jalali
Farzad Jalali
Senior Software Architect at BerryWorld · | 8 upvotes · 9.7K views
Azure Kubernetes Service
Azure Kubernetes Service
Azure Websites
Azure Websites
Azure Functions
Azure Functions
Azure DevOps
Azure DevOps
Visual Studio
Visual Studio
#AzureApps
#AzureAD
#AzureKeyVault
#Azure

Visual Studio Azure DevOps Azure Functions Azure Websites #Azure #AzureKeyVault #AzureAD #AzureApps

#Azure Cloud Since Amazon is potentially our competitor then we need a different cloud vendor, also our programmers are microsoft oriented so the choose were obviously #Azure for us.

Azure DevOps Because we need to be able to develop a neww pipeline into Azure environment ina few minutes.

Azure Kubernetes Service We already in #Azure , also need to use K8s , so let's use AKS as it's a manged Kubernetes in the #Azure

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Michal Nowak
Michal Nowak
Co-founder at Evojam · | 6 upvotes · 38.4K 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.

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Tim Nolet
Tim Nolet
Founder, Engineer & Dishwasher at Checkly · | 5 upvotes · 9K 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/

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Laurence Bargery
Laurence Bargery
CTO at accuRx · | 4 upvotes · 1.8K views
ataccuRxaccuRx
Azure Functions
Azure Functions
#Blob
#Queue
#Table

We've found Azure Storage really useful during the last few years. It's really cheap and pretty versatile too. We've used #table storage to help us out with a migration where we needed to store quite a bit of data, use the #queues for integrating with Azure Functions and helping us load balance our SMS sending and the #blob storage helps us host our client installer and keep up our weekly release train!

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Kubernetes
Kubernetes
Azure Functions
Azure Functions
.NET
.NET

I first found .NET in 2003 when I first began learning to create software. Every year since then, I've watched as .NET matured into something great, and now we have .NET Core! At Contessa Health, we use .NET Core for a mixture of things including fine-grained and coarse-grained web services, worker processes for long running tasks, and for our Azure Functions that serve as a replacement for distributing our base class libraries. As a startup, we are constantly evaluating technologies to make sure we stay fresh, and we keep coming back to .NET Core because of its ecosystem, maturity of the tooling, and for its ability to help us iterate and move quickly. Take all of that and combine it with the Kubernetes ecosystem, and we have an easy way to orchestrate and compose power service offerings that meet the needs of our customers. It cannot be said enough that Microsoft’s commitment to open source has yielded incredible benefits for small companies such as ourselves. Our voices are heard, and we get to help make .NET Core better, which in turn helps everyone else.

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Azure Functions's Features

  • 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

Azure Functions Alternatives & Comparisons

What are some alternatives to Azure Functions?
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

Azure Functions's Followers
131 developers follow Azure Functions to keep up with related blogs and decisions.
Bharat Kumar Bellamkonda
Dave Longman
Alessandro Pio Ardizio
Deepak Patil
malek farhi
S H
Clifford Crerar
Alistair Doulin
Ganeshbabu Kaliaperumal
davzoku