The problem Kubernetes is trying to solve is to eliminate the burden and potential mistakes in the workflow you mentioned by automating your container deploymen

The problem Kubernetes is trying to solve is to eliminate the burden and potential mistakes in the workflow you mentioned by automating your container deployments and actively monitoring their state. This allows the cluster to balance workloads, heal failing components, (re-)distribute work to nodes with the appropriate resources, and migrate between different versions of container images without downtime or manual intervention. It does all of this by allowing you to specify a service architecture in configuration files and then actively ensures that this configuration is maintained even as the underlying state of containers change. You can specify things such as the minimum number of backend containers needed to provide a service, scaling parameters to add more backend containers as load increases, and you can tag nodes with different attributes so that containers are distributed and maintained with the appropriate amount of resources. Kubernetes also provides automating various aspects of networking such as provisioning and configuring load balancers for service ingress as needed. It provides an internal DNS service which automatically registers names for deployments so that linked services can just refer to each other by name without any additional configuration. It can also manage things like SSL certificates which can be shared across multiple services. Lastly, it provides you with a single place where you can store secrets and configuration values that these services require and again, you wire all of this up with configuration files which can be stored in a git (or other VCS).