Of course, a virtual machine can still sit under-utilized or even idle when the demand is low. If you've ever worked in a role managing a fleet of servers, you would have noticed the dramatic under-utilization of compute during low demand periods. Ideally, we don't want the overhead of deploying and configuring a full operating system every time we need to run a workload.

To achieve this, we can make use of containerization technologies such as Docker. Docker allows applications running on an operating system to be isolated from each other by running inside a container. Each container holds only the application and associated dependencies (binaries and libraries):

For every operating system running on a physical server, we can run many container workloads in that same OS. Containers are more efficient to run, partly because they share the resources of a single operating system. Because each container doesn't have to run its own full operating system environment, you can achieve a better density of containers over virtual machines. This means we can make better use of the hardware resources that are available. 

It may take minutes to deploy and configure a VM, but it takes seconds to initialize a container. This makes it much more efficient to be able to add capacity during a scale event, which is done by spinning up more containers. It also means you can achieve better granularity of scale, so you're not deploying more capacity than you need at the time. Our unit of scale here is down to the application level. Typically, the life cycle of a container runs for minutes or hours. A request or system may only use part of an application to achieve a result.

The next evolution of compute breaks up the applications into functions so that we can achieve further efficiencies of infrastructure use.