Google App Engine vs Heroku vs Jelastic

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Google App Engine
Google App Engine

3.6K
2.5K
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Heroku
Heroku

9.3K
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+ 1
3.2K
Jelastic
Jelastic

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+ 1
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- No public GitHub repository available -
- No public GitHub repository available -

What is 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.

What is 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.

What is Jelastic?

Jelastic is the next generation of Java hosting platforms which can run and scale ANY Java application with no code changes required
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Why do developers choose Google App Engine?
Why do developers choose Heroku?
Why do developers choose Jelastic?

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      What are some alternatives to Google App Engine, Heroku, and Jelastic?
      Amazon Web Services
      It provides on-demand cloud computing platforms to individuals, companies and governments. It offers reliable, scalable, and inexpensive cloud computing services.
      DigitalOcean
      We take the complexities out of cloud hosting by offering blazing fast, on-demand SSD cloud servers, straightforward pricing, a simple API, and an easy-to-use control panel.
      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.
      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.
      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.
      See all alternatives
      Decisions about Google App Engine, Heroku, and Jelastic
      Jerome Dalbert
      Jerome Dalbert
      Senior Backend Engineer at StackShare · | 7 upvotes · 21.7K views
      atGratify CommerceGratify Commerce
      Rails
      Rails
      Heroku
      Heroku
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk
      #PaaS

      When creating the web infrastructure for our start-up, I wanted to host our app on a PaaS to get started quickly.

      A very popular one for Rails is Heroku, which I love for free hobby side projects, but never used professionally. On the other hand, I was very familiar with the AWS ecosystem, and since I was going to use some of its services anyways, I thought: why not go all in on it?

      It turns out that Amazon offers a PaaS called AWS Elastic Beanstalk, which is basically like an “AWS Heroku”. It even comes with a similar command-line utility, called "eb”. While edge-case Rails problems are not as well documented as with Heroku, it was very satisfying to manage all our cloud services under the same AWS account. There are auto-scaling options for web and worker instances, which is a nice touch. Overall, it was reliable, and I would recommend it to anyone planning on heavily using AWS.

      See more
      Russel Werner
      Russel Werner
      Lead Engineer at StackShare · | 21 upvotes · 503.6K views
      atStackShareStackShare
      React
      React
      Glamorous
      Glamorous
      Apollo
      Apollo
      Node.js
      Node.js
      Rails
      Rails
      Heroku
      Heroku
      GitHub
      GitHub
      Amazon S3
      Amazon S3
      Amazon CloudFront
      Amazon CloudFront
      Webpack
      Webpack
      CircleCI
      CircleCI
      Redis
      Redis
      #StackDecisionsLaunch
      #SSR
      #Microservices
      #FrontEndRepoSplit

      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
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk
      Heroku
      Heroku
      Ruby
      Ruby
      Rails
      Rails
      Amazon RDS for PostgreSQL
      Amazon RDS for PostgreSQL
      MariaDB
      MariaDB
      Microsoft SQL Server
      Microsoft SQL Server
      Amazon RDS
      Amazon RDS
      AWS Lambda
      AWS Lambda
      Python
      Python
      Redis
      Redis
      Memcached
      Memcached
      AWS Elastic Load Balancing (ELB)
      AWS Elastic Load Balancing (ELB)
      Amazon Elasticsearch Service
      Amazon Elasticsearch Service
      Amazon ElastiCache
      Amazon ElastiCache

      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
      Heroku
      Heroku
      Red Hat OpenShift
      Red Hat OpenShift
      Docker
      Docker

      Heroku vs OpenShift. I've never decided which one is better. Heroku is easier to configure. Openshift provide a better machine for free. Heroku has many addons for free. I've chosen Heroku because of easy initial set-up. I had deployment based on git push. I also tried direct deployment of jar file. Currently Heroku runs my Docker image. Heroku has very good documentation like for beginners. So if you want to start with something, let's follow Heroku. On the other hand OpenShift seems like a PRO tool supported by @RedHat.

      See more
      Gunicorn
      Gunicorn
      uWSGI
      uWSGI
      Heroku
      Heroku
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk

      I use Gunicorn because does one thing - it’s a WSGI HTTP server - and it does it well. Deploy it quickly and easily, and let the rest of your stack do what the rest of your stack does well, wherever that may be.

      uWSGI “aims at developing a full stack for building hosting services” - if that’s a thing you need then ok, but I like the principle of doing one thing well, and I deploy to platforms like Heroku and AWS Elastic Beanstalk where the rest of the “hosting service” is provided and managed for me.

      See more
      Munkhtegsh Munkhbat
      Munkhtegsh Munkhbat
      Software Engineer Consultant at LoanSnap · | 9 upvotes · 46K views
      graphql-yoga
      graphql-yoga
      Prisma
      Prisma
      PostgreSQL
      PostgreSQL
      styled-components
      styled-components
      Heroku
      Heroku
      React
      React
      Apollo
      Apollo
      GraphQL
      GraphQL
      #Backend
      #Frontend

      In my last side project, I built a web posting application that has similar features as Facebook and hosted on Heroku. The user can register an account, create posts, upload images and share with others. I took an advantage of graphql-subscriptions to handle realtime notifications in the comments section. Currently, I'm at the last stage of styling and building layouts.

      For the #Backend I used graphql-yoga, Prisma, GraphQL with PostgreSQL database. For the #FrontEnd: React, styled-components with Apollo. The app is hosted on Heroku.

      See more
      Interest over time
      Reviews of Google App Engine, Heroku, and Jelastic
      Review ofHerokuHeroku

      I use Heroku, for almost any project of mine. Their free plan is awesome for testing, solo developers or your startup and its almost impossible to not cover you somehow. Adding an add on is a simple command away and I find it easy to use it both on my Windows PC or my Linux laptop. Their documentation, covers almost everything. In particular I have used Heroku for Spring, Django and AngularJS. I even find it easier to run my project on my local dev with foreman start, than ./manage.py runserver (for my django projects). There is no place like Heroku for the developer!

      Review ofHerokuHeroku

      Can't beat the simplicity of deploying and managing apps, the pricing is a bit high, but you are paying for those streamlined tools. However, after several experiences of tracing issues back to Heroku's stack, not having visibility into what they are doing has prompted moving two applications off of it and on to other more transparent cloud solutions. Heroku is amazing for what it is, hosting for early stage products.

      Review ofGoogle App EngineGoogle App Engine

      With Cloud Endpoints you can create and deploy mobile backend in one hour or less. And it is free (until you need extra scale). I would not recommend to use Java - python is faster and has all new appengine features.

      Pros: everything is in one place: task queue, cron, backend instances for data processing, datastore, mapreduce. Cons: you cannot easily move your code from GAE. Even with special 3rd party services.

      Review ofHerokuHeroku

      I've been using Heroku for 3 years now, they have grown super fast and each time they're improving their services. What I really like the most is how easily you can show to your client the advances on you project, it would take you maximum 15 minutes to configure two environments (Staging/Production). It is simply essential and fantastic!

      Review ofHerokuHeroku

      I liked how easy this was to use and that I could create some proof of concepts without have to pay. The downside for NodeJS is remote debugging. Pretty much have to depend on logging where Azure allows remote debugging with Node Inspector.

      Review ofHerokuHeroku

      Using Heroku takes away all the pains associated with managing compute and backing services. It may require a little extra optimisation and tweaks, but these constraints often make your app better anyway.

      Review ofGoogle App EngineGoogle App Engine

      With Cloud Endpoints you can create and deploy mobile backend in one hour or less.

      How developers use Google App Engine, Heroku, and Jelastic
      Avatar of StackShare
      StackShare uses HerokuHeroku

      Not having to deal with servers is a huge win for us. There are certainly trade-offs (having to wait if the platform is down as opposed to being able to fix the issue), but we’re happy being on Heroku right now. Being able to focus 100% of our technical efforts on application code is immensely helpful.

      Two dynos seems to be the sweet spot for our application. We can handle traffic spikes and get pretty consistent performance otherwise.

      We have a total of four apps on Heroku: Legacy Leanstack, StackShare Prod, StackShare Staging, StackShare Dev. Protip: if you’re setting up multiple environments based on your prod environment, just run heroku fork app name. Super useful, it copies over your db, add-ons, and settings.

      We have a develop branch on GitHub that we push to dev to test out, then if everything is cool we push it to staging and eventually prod. Hotfixes of course go straight to staging and then prod usually.

      Avatar of Casey Smith
      Casey Smith uses Google App EngineGoogle App Engine

      PaaS for back-end components, including external data ingestion APIs, front-end web service APIs, hosting of static front-end application assets, back-end data processing pipeline microservices, APIs to storage infrastructure (Cloud SQL and Memcached), and data processing pipeline task queues and cron jobs. Task queue fan-out and auto-scaling of back-end microservice instances provide parallelism for high velocity data processing.

      Avatar of StackShare
      StackShare uses HerokuHeroku

      We keep the Metrics tab open while we load test, and hit refresh to see what’s going on: heroku metric

      I would expect the graphs to expand with some sort of detail, but that’s not the case. So these metrics aren’t very useful. The logs are far more useful, so we just keep the tail open while we test.

      Avatar of Lawrence Cheuk
      Lawrence Cheuk uses Google App EngineGoogle App Engine

      checking a swap require a lot of cpu resource, roster normally come out same day of month, every month, at a particular time. Which make very high spike, our flag ship product, iSwap, with the capability looking swap possibility with 10000 other rosters base on user critieria, you need a cloud computing give you this magnitude of computing power. gae did it nicely, user friendly, easy to you, low cost.

      Avatar of Tim Lucas
      Tim Lucas uses HerokuHeroku

      Heroku runs the web and background worker processes. Auto-deployments are triggered via GitHub commits and wait for the Buildkite test build to pass. Heroku pipelines with beta release phase execution (for automatically running database migrations) allowed for easy manual testing of big new releases. Web and worker logs are sent to Papertrail.

      Avatar of Jeff Flynn
      Jeff Flynn uses HerokuHeroku

      As much as I love AWS EC, I prefer Heroku for apps like this. Heroku has grown up around Rails and Ruby, massive set of add-ons that are usually one-click setup, and I once had to perform an emergency app scale-up a that I completed in seconds from my mobile phone whilst riding the Bangkok subway. Doesn't get much easier than that.

      Avatar of danlangford
      danlangford uses HerokuHeroku

      With its complimentary SSL (on *.herokuapp.com) we can test everything. Our dev branch is built and deployed out to Heroku. Testing happens out here. not production cause $20/mo is TOO much to pay for the ability to use my own SSL purchased elsewhere.

      Avatar of CommentBox.io
      CommentBox.io uses Google App EngineGoogle App Engine

      App engine fills in the gaps in the increasingly smaller case where it's necessary for us to run our own APIs.

      Avatar of Abhijeet Gokar
      Abhijeet Gokar uses Google App EngineGoogle App Engine

      Very easy to make cloud computing of ML models , and use containers like Kubernetes.

      Avatar of BrightMachine
      BrightMachine uses JelasticJelastic

      Host the majority of our websites. Great pricing, and a great tech model.

      Avatar of Vamsi Krishna
      Vamsi Krishna uses Google App EngineGoogle App Engine

      Cloud instances to run our app, Cloud MySQL , Network Load Balancer

      How much does Google App Engine cost?
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