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I started using DigitalOcean back in January to host a Ghost blog. I was a little worried at first because I didn't have too much experience setting up servers. There was always the option of a full service company that does all the work for you, but the point was that I wanted more control for the purpose of learning. And, learning turned out to be really easy thanks to the great community at DigitalOcean. There are tutorials for just about anything. It has been an amazing learning experience, and now I'm looking forward to hosting more complex projects here. I already have a couple in the works for the near future. I highly recommend it.
I can't rate the Support great or bad, as I haven't really had a need to contact them yet. But everything else has been excellent so far.
I am a freelancer and a researcher. I have had tried a lot of hosting services over the years. But DIgitalOcean stands out from the rest for its pricing. Its just five dollar a month for a basic node.
And the other reason for loving Digital Ocean is that they support Docker. It you buy a VPS machine, chances are that docker support wont be available as with PV or hypervisor, docker need some extra config.
So far I am loving DO :-)
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
I use DigitalOcean for testing or hosting my apps. You can set up an Ubuntu server in less than a minute. There are also one-click-install apps, so I don't have to install e.g. the LAMP stack myself. The dashboard has a really easy UI and is easy to use. The costs begin at 5 bucks per month. Also DigitalOcean has a great support and an adorable community. They have a great support page with hundreds of tutorials.
- 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
DigitalOcean offers us everything we need to test out specific scenarios or we expect from small-servers like our monitoring-system. We also use digital-ocean in long-term and are very satisfied with their performance and scalability.
Because I like having more control of my deployment, I am currently hosting this on DigitalOcean. I don't need to worry about arbitrary row limits and I can be sure that the app is always running.
We use DigitalOcean to host our build tools (namely Drone.io) for a cheap CI and CD server.
We'll be using this to host the server application during alpha phase.
Been hosting with them for a while now. Never had an issue, great support, great docs: can't beat 'em. Though I'd probably move to AWS for large scale projects.
Infrastructure for Google App Engine, Google Cloud Endpoints, Memcached, and Google Cloud SQL components, as well as Git repository and Jenkins CI server.
DigitalOcean is the backbone for the whole stack. Without its cheap pricing and easy scalability this whole project wouldn't be possible.
RamNode provides the hosting platform for my personal and production projects.