Not the person you replied to, but we do this. The main reason being on premise deployments. Our workload is primarily machine learning models, as such they ar

Not the person you replied to, but we do this. The main reason being on premise deployments. Our workload is primarily machine learning models, as such they are well suited to docker containers due to good support and being able to quickly build images, deploy and tear down. Additionally, whilst the task would be well suited to a Kubernetes deployment which is ideal in the cloud, on prem we're likely running on a single box running multiple VM's. Hence we use containers within the VM. It isn't the perfect solution and definitely has it's downsides, but it is good enough and better than the alternatives when considering everything possible.