What is Amazon EC2?
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A VPS gives the full access that I need, because most of what I do has complex integrations and there is plenty of legacy - very stable, highly tuned code developed over two decades - that I carry with me. My use is also limited to during development, so there is no point going for a full server.
Amazon EC2 is a VPS, except it is cheaper.
Additionally, I used to previously take the code developed on my VPS and deploy it to whatever server the client brought.
With Amazon EC2 the deployment is already done. All that remains it to scale up, add other products like dns, mail, storage and so on, and change the billing so that the client gets invoiced. That makes the process that much more predictable and seamless, and the end result much more stable.
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
Just started using EC2 myself, but it was the platform used by my previous employer, as well. They are getting easier to use, dashboard improvements over time were well done. Responded fast to outages. They offer a limited free tier which is perfect for my current project, allowing me time to build it to the point where I will need a paid solution. Overall, I'm liking it so far.
About a year and a half ago (written June 2013) we moved from dedicated servers over to AWS. Thanks to AWS, we no longer have to think on a server level. Instead, we think of everything as a cluster of instances, and an instance is essentially a virtual server where we don’t have to worry about the hardware. It’s a relief to not have to worry about the hardware behind the instances.
The clusters we have are: WWW, API, Upload, HAProxy, HBase, MySQL, Memcached, Redis, and ElasticSearch, for an average total of 80 instances. Each cluster handles the job that its name describes, all working together for the common goal of giving you your daily (hourly?) dose of image entertainment.
Below is a diagram of how they all work together:
- 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 liked a lot of things about Heroku. We loved the build packs, and we still in fact use Heroku build packs, but we were frustrated by lack of control about a lot of things. It’s nice to own the complete stack, or rather as far down as AWS goes. It gave us a lot of flexibility and functionality that we didn’t have before. We use a lot of Amazon technology.
I like containers and all, but for zerotoherojs.com I am a one-man band, who also works full time. I don’t have any (dev)ops budget, and therefore I need the reliability and uptime of an actual virtual machine.
That’s where AWS EC2 comes in handy.
Docker containers will be hosted and run on a single Amazon EC2 instance. This will likely be the t2.small or t2.medium instance type as listed here: https://aws.amazon.com/ec2/instance-types/
Because servers. Lots of them. Lots of configurations. Great for mission-specific functions. Video encoding, data aggregation, dedicated processing, mission-critical data stores. Anything you can't hang off your Heroku environment.
Infrastructure for Google App Engine, Google Cloud Endpoints, Memcached, and Google Cloud SQL components, as well as Git repository and Jenkins CI server.