Alternatives to Azure App Service logo

Alternatives to Azure App Service

Azure Service Fabric, AWS Elastic Beanstalk, Google App Engine, Azure Functions, and Azure Service Bus are the most popular alternatives and competitors to Azure App Service.
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What is Azure App Service and what are its top alternatives?

Quickly build, deploy, and scale web apps created with popular frameworks .NET, .NET Core, Node.js, Java, PHP, Ruby, or Python, in containers or running on any operating system. Meet rigorous, enterprise-grade performance, security, and compliance requirements by using the fully managed platform for your operational and monitoring tasks.
Azure App Service is a tool in the Platform as a Service category of a tech stack.

Top Alternatives to Azure App Service

  • Azure Service Fabric

    Azure Service Fabric

    Azure Service Fabric is a distributed systems platform that makes it easy to package, deploy, and manage scalable and reliable microservices. Service Fabric addresses the significant challenges in developing and managing cloud apps. ...

  • AWS Elastic Beanstalk

    AWS Elastic Beanstalk

    Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring. ...

  • Google App Engine

    Google App Engine

    Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow. ...

  • 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. ...

  • Azure Service Bus

    Azure Service Bus

    It is a cloud messaging system for connecting apps and devices across public and private clouds. You can depend on it when you need highly-reliable cloud messaging service between applications and services, even when one or more is offline. ...

  • Kubernetes

    Kubernetes

    Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. ...

  • Heroku

    Heroku

    Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling. ...

  • Apollo

    Apollo

    Build a universal GraphQL API on top of your existing REST APIs, so you can ship new application features fast without waiting on backend changes. ...

Azure App Service alternatives & related posts

Azure Service Fabric logo

Azure Service Fabric

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Distributed systems platform that simplifies build, package, deploy, and management of scalable microservices apps
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PROS OF AZURE SERVICE FABRIC
  • 5
    Intelligent, fast, reliable
  • 3
    Open source
  • 3
    Superior programming models
  • 3
    More reliable than Kubernetes
  • 3
    Runs most of Azure core services
  • 3
    Reliability
  • 2
    Quickest recovery and healing in the world
  • 1
    Deploy anywhere
  • 1
    Is data storage technology
  • 1
    Battle hardened in Azure > 10 Years
CONS OF AZURE SERVICE FABRIC
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    related Azure Service Fabric posts

    AWS Elastic Beanstalk logo

    AWS Elastic Beanstalk

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    Quickly deploy and manage applications in the AWS cloud.
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    PROS OF AWS ELASTIC BEANSTALK
    • 77
      Integrates with other aws services
    • 65
      Simple deployment
    • 44
      Fast
    • 28
      Painless
    • 16
      Free
    • 3
      Independend app container
    • 3
      Well-documented
    • 2
      Ability to be customized
    • 2
      Postgres hosting
    CONS OF AWS ELASTIC BEANSTALK
    • 2
      Charges appear automatically after exceeding free quota
    • 1
      Lots of moving parts and config
    • 0
      Slow deployments

    related AWS Elastic Beanstalk posts

    Julien DeFrance
    Principal Software Engineer at Tophatter · | 16 upvotes · 2.4M views

    Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

    I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

    For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

    Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

    Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

    Future improvements / technology decisions included:

    Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

    As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

    One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

    See more

    We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.

    We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.

    In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.

    Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache

    See more
    Google App Engine logo

    Google App Engine

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    Build web applications on the same scalable systems that power Google applications
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    PROS OF GOOGLE APP ENGINE
    • 144
      Easy to deploy
    • 108
      Auto scaling
    • 80
      Good free plan
    • 64
      Easy management
    • 58
      Scalability
    • 35
      Low cost
    • 33
      Comprehensive set of features
    • 29
      All services in one place
    • 23
      Simple scaling
    • 20
      Quick and reliable cloud servers
    • 5
      Granular Billing
    • 4
      Easy to develop and unit test
    • 3
      Monitoring gives comprehensive set of key indicators
    • 2
      Create APIs quickly with cloud endpoints
    • 2
      Really easy to quickly bring up a full stack
    • 1
      Mostly up
    • 1
      No Ops
    CONS OF GOOGLE APP ENGINE
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      related Google App Engine posts

      Nick Rockwell
      SVP, Engineering at Fastly · | 11 upvotes · 283.8K views

      So, the shift from Amazon EC2 to Google App Engine and generally #AWS to #GCP was a long decision and in the end, it's one that we've taken with eyes open and that we reserve the right to modify at any time. And to be clear, we continue to do a lot of stuff with AWS. But, by default, the content of the decision was, for our consumer-facing products, we're going to use GCP first. And if there's some reason why we don't think that's going to work out great, then we'll happily use AWS. In practice, that hasn't really happened. We've been able to meet almost 100% of our needs in GCP.

      So it's basically mostly Google Kubernetes Engine , we're mostly running stuff on Kubernetes right now.

      #AWStoGCPmigration #cloudmigration #migration

      See more
      Aliadoc Team

      In #Aliadoc, we're exploring the crowdfunding option to get traction before launch. We are building a SaaS platform for website design customization.

      For the Admin UI and website editor we use React and we're currently transitioning from a Create React App setup to a custom one because our needs have become more specific. We use CloudFlare as much as possible, it's a great service.

      For routing dynamic resources and proxy tasks to feed websites to the editor we leverage CloudFlare Workers for improved responsiveness. We use Firebase for our hosting needs and user authentication while also using several Cloud Functions for Firebase to interact with other services along with Google App Engine and Google Cloud Storage, but also the Real Time Database is on the radar for collaborative website editing.

      We generally hate configuration but honestly because of the stage of our project we lack resources for doing heavy sysops work. So we are basically just relying on Serverless technologies as much as we can to do all server side processing.

      Visual Studio Code definitively makes programming a much easier and enjoyable task, we just love it. We combine it with Bitbucket for our source code control needs.

      See more
      Azure Functions logo

      Azure Functions

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      Listen and react to events across your stack
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      PROS OF AZURE FUNCTIONS
      • 12
        Pay only when invoked
      • 8
        Great developer experience for C#
      • 6
        Multiple languages supported
      • 5
        Great debugging support
      • 2
        Poor developer experience for C#
      • 2
        Easy scalability
      • 2
        Can be used as lightweight https service
      • 1
        WebHooks
      • 1
        Event driven
      • 1
        Azure component events for Storage, services etc
      CONS OF AZURE FUNCTIONS
      • 1
        No persistent (writable) file system available
      • 1
        Poor support for Linux environments
      • 1
        Sporadic server & language runtime issues
      • 1
        Not suited for long-running applications

      related Azure Functions posts

      Kestas Barzdaitis
      Entrepreneur & Engineer · | 16 upvotes · 453K views

      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

      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
      Azure Service Bus logo

      Azure Service Bus

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      Reliable cloud messaging as a service (MaaS)
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      PROS OF AZURE SERVICE BUS
      • 2
        Cloud Native
      • 1
        Easy Integration with .Net
      CONS OF AZURE SERVICE BUS
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        related Azure Service Bus posts

        Kubernetes logo

        Kubernetes

        38.9K
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        Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
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        PROS OF KUBERNETES
        • 159
          Leading docker container management solution
        • 124
          Simple and powerful
        • 101
          Open source
        • 75
          Backed by google
        • 56
          The right abstractions
        • 24
          Scale services
        • 18
          Replication controller
        • 9
          Permission managment
        • 7
          Simple
        • 7
          Supports autoscaling
        • 6
          Cheap
        • 4
          Self-healing
        • 4
          Reliable
        • 4
          No cloud platform lock-in
        • 3
          Open, powerful, stable
        • 3
          Scalable
        • 3
          Quick cloud setup
        • 3
          Promotes modern/good infrascture practice
        • 2
          Backed by Red Hat
        • 2
          Runs on azure
        • 2
          Cloud Agnostic
        • 2
          Custom and extensibility
        • 2
          Captain of Container Ship
        • 2
          A self healing environment with rich metadata
        • 1
          Golang
        • 1
          Easy setup
        • 1
          Everything of CaaS
        • 1
          Sfg
        • 1
          Expandable
        • 1
          Gke
        CONS OF KUBERNETES
        • 13
          Poor workflow for development
        • 11
          Steep learning curve
        • 5
          Orchestrates only infrastructure
        • 2
          High resource requirements for on-prem clusters

        related Kubernetes posts

        Conor Myhrvold
        Tech Brand Mgr, Office of CTO at Uber · | 39 upvotes · 4.2M views

        How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

        Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

        Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

        https://eng.uber.com/distributed-tracing/

        (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

        Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

        See more
        Yshay Yaacobi

        Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

        Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

        After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

        See more
        Heroku logo

        Heroku

        20K
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        Build, deliver, monitor and scale web apps and APIs with a trail blazing developer experience.
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        PROS OF HEROKU
        • 704
          Easy deployment
        • 460
          Free for side projects
        • 374
          Huge time-saver
        • 348
          Simple scaling
        • 261
          Low devops skills required
        • 190
          Easy setup
        • 174
          Add-ons for almost everything
        • 154
          Beginner friendly
        • 150
          Better for startups
        • 133
          Low learning curve
        • 48
          Postgres hosting
        • 41
          Easy to add collaborators
        • 30
          Faster development
        • 24
          Awesome documentation
        • 19
          Focus on product, not deployment
        • 19
          Simple rollback
        • 15
          Natural companion for rails development
        • 15
          Easy integration
        • 12
          Great customer support
        • 8
          GitHub integration
        • 6
          No-ops
        • 6
          Painless & well documented
        • 4
          Free
        • 4
          I love that they make it free to launch a side project
        • 3
          Just works
        • 3
          Great UI
        • 2
          PostgreSQL forking and following
        • 2
          MySQL extension
        • 1
          Able to host stuff good like Discord Bot
        • 0
          Sec
        • 0
          Security
        CONS OF HEROKU
        • 23
          Super expensive
        • 6
          Not a whole lot of flexibility
        • 5
          No usable MySQL option
        • 5
          Storage
        • 4
          Low performance on free tier
        • 1
          24/7 support is $1,000 per month

        related Heroku posts

        Russel Werner
        Lead Engineer at StackShare · | 30 upvotes · 1.5M views

        StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

        Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

        #StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

        See more
        Simon Reymann
        Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 3.3M views

        Our whole DevOps stack consists of the following tools:

        • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
        • Respectively Git as revision control system
        • SourceTree as Git GUI
        • Visual Studio Code as IDE
        • CircleCI for continuous integration (automatize development process)
        • Prettier / TSLint / ESLint as code linter
        • SonarQube as quality gate
        • Docker as container management (incl. Docker Compose for multi-container application management)
        • VirtualBox for operating system simulation tests
        • Kubernetes as cluster management for docker containers
        • Heroku for deploying in test environments
        • nginx as web server (preferably used as facade server in production environment)
        • SSLMate (using OpenSSL) for certificate management
        • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
        • PostgreSQL as preferred database system
        • Redis as preferred in-memory database/store (great for caching)

        The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

        • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
        • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
        • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
        • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
        • Scalability: All-in-one framework for distributed systems.
        • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
        See more
        Apollo logo

        Apollo

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        GraphQL server for Express, Connect, Hapi, Koa and more
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        PROS OF APOLLO
        • 12
          From the creators of Meteor
        • 3
          Great documentation
        • 2
          Real time if use subscription
        • 1
          Open source
        CONS OF APOLLO
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          related Apollo posts

          Nick Rockwell
          SVP, Engineering at Fastly · | 44 upvotes · 1.7M views

          When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

          So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

          React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

          Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

          See more
          Adam Neary

          At Airbnb we use GraphQL Unions for a "Backend-Driven UI." We have built a system where a very dynamic page is constructed based on a query that will return an array of some set of possible “sections.” These sections are responsive and define the UI completely.

          The central file that manages this would be a generated file. Since the list of possible sections is quite large (~50 sections today for Search), it also presumes we have a sane mechanism for lazy-loading components with server rendering, which is a topic for another post. Suffice it to say, we do not need to package all possible sections in a massive bundle to account for everything up front.

          Each section component defines its own query fragment, colocated with the section’s component code. This is the general idea of Backend-Driven UI at Airbnb. It’s used in a number of places, including Search, Trip Planner, Host tools, and various landing pages. We use this as our starting point, and then in the demo show how to (1) make and update to an existing section, and (2) add a new section.

          While building your product, you want to be able to explore your schema, discovering field names and testing out potential queries on live development data. We achieve that today with GraphQL Playground, the work of our friends at #Prisma. The tools come standard with Apollo Server.

          #BackendDrivenUI

          See more