What is Google Compute Engine?
What is Microsoft Azure?
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What are the cons of using Google Compute Engine?
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Windows Azure is more difficult to configure than some other cloud based technologies, however, it makes up for it with the incredible integrations and ease of development on mobile platforms (Android, iOS and of course Windows Phone).
The Azure Web Sites is a PaaS that is very easy to setup and is pretty powerful.
If you want VMs you can have them and even program when they come online.
There are tons of ways to use this service and there are a lot of free things you can get in order to try it out. The only downside is that you have to learn a new, although very powerful, platform.
I use Google Compute Engine instances as flexible, reproducible infrastructure that scale with my data science tasks.
Between Google Cloud and Amazon Web Services, I chose Google Cloud for its intuitive UI. SSH within the browser is very convenient.
Related blog post with example usage: Running an IPython Notebook on Google Compute Engine from Chrome
Rackspace plays nice with Windows Server 2013. It is the most customizable platform I have worked with so far and the closest to running a private server. The dev tools are great and if you want to work in a familiar environment with as much customizability as you want this is the right server for you.
- I use Google Compute Engine instances as flexible, reproducible infrastructure that scales with my data science tasks.
- Between Google Cloud and Amazon Web Services, I chose Google Cloud for its intuitive UI. SSH within the browser is very convenient.
- Related blog post with example usage: Running an IPython Notebook on Google Compute Engine from Chrome
We use Microsoft Azure because many of our clients are already Azure for their private cloud. Additionally, Azure supports App Service Environments (ASE), which isolates the application resources and gives us a static IP for securely accessing external resources
Additionally, MSSQL supports columnstore tables which is critical for running fast analytics over large datasets
For our cloud infrastructure, I cannot recommend Rackspace higher. They have consistently knocked it out of the park for us, especially in terms of direct support and help even beyond the call of duty.
My favourite cloud with all the great tools - web apps, mobile apps, storages, easy tables, blobs, app insights, cosmos DB... I think it is really usable and ergonomic. Plus point for mobile app.
We currently host PRS and EARS on Azure as they are .Net apps, but we are currently porting these services to Scala and will be hosting them on Heroku with the other P2 SRX services.
Serviço utilizado para deploy de toda a infraestrutura do projeto. Colocamos todas as peças do serviço no azure, garantindo uma forma rápida e garantia de escalibilidade.
Blackbaud makes use of Azure and my current job is with Blackbaud. Therefore, due to the free credit and the ability to reuse tools, I rely on Azure quite a bit.
Infrastructure for Google App Engine, Google Cloud Endpoints, Memcached, and Google Cloud SQL components, as well as Git repository and Jenkins CI server.
I used Rackspace virtual machines for all my dynamic web applications until switching to Digital ocean. I still like and recommend Rackspace.
Our hosting partner for four years running. Rackspace continually evolves to meet their customers' needs.
Content is distributed via Rackspace CDN for faster file access