> Why don't more people just use the native machine imaging built into cloud providers? (I would actually like to know this)

I've done that, and I've done Kubernetes, and Kubernetes is definitely easier once you get past the initial setup. The initial setup is also getting easier over time.

It is also more portable. Kubernetes runs on multiple cloud providers as well as your own hardware and presents the same interface and runs the same containers. Docker containers are more portable than AMIs.

If you plan to write your own system to control deployments, secrets, load balancing, and DNS based on AMIs and other AWS features, you may want to consider that you are reinventing the wheel. You are also locking yourself into AWS to a far greater extent than you would if you used Kubernetes.

Expertise is also a big differentiator. You can hire people who know Kubernetes on day one, but you cannot hire people who already know your custom in-house system.

For us, it's much more economical to binpack multiple apps onto a VM than to run one service per VM. Also it makes it much easier to scale out particular services once they outgrow your chosen VM size.

If your application is 50 microservices, how would you manage that on ec2 instances?

One autoscaling group, AMI, instance (or more than one) per service.

A nontrivial portion of those microservices could probably run on Lambda.

Why does the number of microservices have anything to do with where they might live? Wouldn't that be much more related to CPU load?

Because you generally want to deploy them independently. If you have 50 microservices and have to run an AMI build every time that's going to significantly slow you down. With containers you generally only deploy the service that has changes to a VM that doesn't change as often.

You want them to be independent, atomic. How they are deployed and the choice of technology you choose to couple them with? That should be driven by load -- and dynamic.

The reason everybody's so hot on microservices to begin with is that we kept coupling everything all together and it became a huge mess to manage. You don't want to repeat that mistake, only at cloud scale.