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Google App Engine
Google App Engine

2.7K
1.7K
+ 1
606
Heroku
Heroku

7.5K
5.2K
+ 1
3.1K
Paz
Paz

0
2
+ 1
0
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- 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 Paz?

A pluggable in-house service platform with a PaaS-like workflow, built on Docker, CoreOS, Etcd and Fleet.
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    What are the cons of using Google App Engine?
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        What companies use Google App Engine?
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          What tools integrate with Google App Engine?
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          What are some alternatives to Google App Engine, Heroku, and Paz?
          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 Paz
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          Interest over time
          Reviews of Google App Engine, Heroku, and Paz
          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 Paz
          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 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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          How much does Paz cost?
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