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. ...

  • NGINX
    NGINX

    nginx [engine x] is an HTTP and reverse proxy server, as well as a mail proxy server, written by Igor Sysoev. According to Netcraft nginx served or proxied 30.46% of the top million busiest sites in Jan 2018. ...

  • Apache HTTP Server
    Apache HTTP Server

    The Apache HTTP Server is a powerful and flexible HTTP/1.1 compliant web server. Originally designed as a replacement for the NCSA HTTP Server, it has grown to be the most popular web server on the Internet. ...

Azure App Service alternatives & related posts

Azure Service Fabric logo

Azure Service Fabric

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282
26
Distributed systems platform that simplifies build, package, deploy, and management of scalable microservices apps
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282
+ 1
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PROS OF AZURE SERVICE FABRIC
  • 5
    Intelligent, fast, reliable
  • 4
    Runs most of Azure core services
  • 3
    Reliability
  • 3
    Superior programming models
  • 3
    More reliable than Kubernetes
  • 3
    Open source
  • 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
    • 4
      Well-documented
    • 3
      Independend app container
    • 2
      Postgres hosting
    • 2
      Ability to be customized
    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 · 3.2M 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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    611
    PROS OF GOOGLE APP ENGINE
    • 145
      Easy to deploy
    • 106
      Auto scaling
    • 80
      Good free plan
    • 62
      Easy management
    • 56
      Scalability
    • 35
      Low cost
    • 32
      Comprehensive set of features
    • 28
      All services in one place
    • 22
      Simple scaling
    • 19
      Quick and reliable cloud servers
    • 6
      Granular Billing
    • 5
      Easy to develop and unit test
    • 5
      Monitoring gives comprehensive set of key indicators
    • 3
      Really easy to quickly bring up a full stack
    • 3
      Create APIs quickly with cloud endpoints
    • 2
      No Ops
    • 2
      Mostly up
    CONS OF GOOGLE APP ENGINE
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      related Google App Engine posts

      Nick Rockwell
      SVP, Engineering at Fastly · | 12 upvotes · 432.4K 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
      • 14
        Pay only when invoked
      • 11
        Great developer experience for C#
      • 9
        Multiple languages supported
      • 7
        Great debugging support
      • 5
        Can be used as lightweight https service
      • 4
        Easy scalability
      • 3
        WebHooks
      • 3
        Costo
      • 2
        Event driven
      • 2
        Azure component events for Storage, services etc
      • 2
        Poor developer experience for C#
      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 · 768.7K 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

      274
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      Reliable cloud messaging as a service (MaaS)
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      PROS OF AZURE SERVICE BUS
      • 4
        Easy Integration with .Net
      • 2
        Cloud Native
      • 1
        Use while high messaging need
      CONS OF AZURE SERVICE BUS
      • 1
        Limited features in Basic tier
      • 1
        Skills can only be used in Azure - vendor lock-in
      • 1
        Lacking in JMS support
      • 1
        Observability of messages in the queue is lacking

      related Azure Service Bus posts

      Shared insights
      on
      Azure Service BusAzure Service BusIBM MQIBM MQ

      Want to get the differences in features and enhancement, pros and cons, and also how to Migrate from IBM MQ to Azure Service Bus.

      See more
      Kubernetes logo

      Kubernetes

      59.8K
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      681
      Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
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      PROS OF KUBERNETES
      • 166
        Leading docker container management solution
      • 129
        Simple and powerful
      • 107
        Open source
      • 76
        Backed by google
      • 58
        The right abstractions
      • 25
        Scale services
      • 20
        Replication controller
      • 11
        Permission managment
      • 9
        Supports autoscaling
      • 8
        Simple
      • 8
        Cheap
      • 6
        Self-healing
      • 5
        Open, powerful, stable
      • 5
        Reliable
      • 5
        No cloud platform lock-in
      • 5
        Promotes modern/good infrascture practice
      • 4
        Scalable
      • 4
        Quick cloud setup
      • 3
        Custom and extensibility
      • 3
        Captain of Container Ship
      • 3
        Cloud Agnostic
      • 3
        Backed by Red Hat
      • 3
        Runs on azure
      • 3
        A self healing environment with rich metadata
      • 2
        Everything of CaaS
      • 2
        Gke
      • 2
        Golang
      • 2
        Easy setup
      • 2
        Expandable
      • 2
        Sfg
      CONS OF KUBERNETES
      • 16
        Steep learning curve
      • 15
        Poor workflow for development
      • 8
        Orchestrates only infrastructure
      • 4
        High resource requirements for on-prem clusters
      • 2
        Too heavy for simple systems
      • 1
        Additional vendor lock-in (Docker)
      • 1
        More moving parts to secure
      • 1
        Additional Technology Overhead

      related Kubernetes posts

      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 12.6M 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
      NGINX logo

      NGINX

      113.3K
      60.9K
      5.5K
      A high performance free open source web server powering busiest sites on the Internet.
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      PROS OF NGINX
      • 1.4K
        High-performance http server
      • 894
        Performance
      • 730
        Easy to configure
      • 607
        Open source
      • 530
        Load balancer
      • 289
        Free
      • 288
        Scalability
      • 226
        Web server
      • 175
        Simplicity
      • 136
        Easy setup
      • 30
        Content caching
      • 21
        Web Accelerator
      • 15
        Capability
      • 14
        Fast
      • 12
        High-latency
      • 12
        Predictability
      • 8
        Reverse Proxy
      • 7
        The best of them
      • 7
        Supports http/2
      • 5
        Great Community
      • 5
        Lots of Modules
      • 5
        Enterprise version
      • 4
        High perfomance proxy server
      • 3
        Embedded Lua scripting
      • 3
        Streaming media delivery
      • 3
        Streaming media
      • 3
        Reversy Proxy
      • 2
        Blash
      • 2
        GRPC-Web
      • 2
        Lightweight
      • 2
        Fast and easy to set up
      • 2
        Slim
      • 2
        saltstack
      • 1
        Virtual hosting
      • 1
        Narrow focus. Easy to configure. Fast
      • 1
        Along with Redis Cache its the Most superior
      • 1
        Ingress controller
      CONS OF NGINX
      • 10
        Advanced features require subscription

      related NGINX posts

      Simon Reymann
      Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11M 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
      John-Daniel Trask
      Co-founder & CEO at Raygun · | 19 upvotes · 283.3K views

      We chose AWS because, at the time, it was really the only cloud provider to choose from.

      We tend to use their basic building blocks (EC2, ELB, Amazon S3, Amazon RDS) rather than vendor specific components like databases and queuing. We deliberately decided to do this to ensure we could provide multi-cloud support or potentially move to another cloud provider if the offering was better for our customers.

      We’ve utilized c3.large nodes for both the Node.js deployment and then for the .NET Core deployment. Both sit as backends behind an nginx instance and are managed using scaling groups in Amazon EC2 sitting behind a standard AWS Elastic Load Balancing (ELB).

      While we’re satisfied with AWS, we do review our decision each year and have looked at Azure and Google Cloud offerings.

      #CloudHosting #WebServers #CloudStorage #LoadBalancerReverseProxy

      See more
      Apache HTTP Server logo

      Apache HTTP Server

      64.4K
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      Open-source HTTP server for modern operating systems including UNIX and Windows
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      PROS OF APACHE HTTP SERVER
      • 479
        Web server
      • 305
        Most widely-used web server
      • 217
        Virtual hosting
      • 148
        Fast
      • 138
        Ssl support
      • 44
        Since 1996
      • 28
        Asynchronous
      • 5
        Robust
      • 4
        Proven over many years
      • 2
        Mature
      • 2
        Perfomance
      • 1
        Perfect Support
      • 0
        Many available modules
      • 0
        Many available modules
      CONS OF APACHE HTTP SERVER
      • 4
        Hard to set up

      related Apache HTTP Server posts

      Nick Rockwell
      SVP, Engineering at Fastly · | 46 upvotes · 4.1M 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
      Tim Abbott
      Shared insights
      on
      NGINXNGINXApache HTTP ServerApache HTTP Server
      at

      We've been happy with nginx as part of our stack. As an open source web application that folks install on-premise, the configuration system for the webserver is pretty important to us. I have a few complaints (e.g. the configuration syntax for conditionals is a pain), but overall we've found it pretty easy to build a configurable set of options (see link) for how to run Zulip on nginx, both directly and with a remote reverse proxy in front of it, with a minimum of code duplication.

      Certainly I've been a lot happier with it than I was working with Apache HTTP Server in past projects.

      See more