A note about Automation and infrastructure capabilities:

Infrastructure capabilities used to be expanded with pre-specified requirements, deterministic allocations based on back-of-the-envelope calculations, and step by step system development. The architecture used to involve service-oriented design and compositions within organizational units such as datacenters. The emerging trend, on the other hand, uses concurrent definitions of requirements and solutions, rapid integration into software-defined components with automation, and heuristics-based evolution. Demand can be managed with services that are redirected to different systems and load-balancing can ensure that all systems are utilized in deployment. With the move to zero-downtime maintenance, capabilities are serviced without any outages or notifications to the customer. Active and stand by servers are rotated so that the incoming traffic is handled appropriately.

Data backup, migration, and replication has brought significant improvements to the practice of system engineering. Content can easily be distributed between sites and near-real-time replication enables customers to find their data when they need it and not some later point.  This has had an impact on the lifecycles of the platform components where newer hardware or upgraded components are much easier to bring in than ever before. With the ease and convenience of updating or upgrading parts or whole systems at lower or intermediary levels, the total cost of ownership of the infrastructure is reduced while the features and capabilities boost productivity. Security of the infrastructure also improves as recent versions of hardware and software bring more robustness and compliances with vulnerability mitigations.

The use of commodity servers and expansion based on a cluster-node design also allows infrastructure to scale out with little or no disruption to existing services. As long as the traffic from higher levels is consolidated towards known entry points, the expansion of the lower level can proceed independently. With an increase in automation of the often-repeated chores to build, deploy and test the system, the overall time to the readiness of the system also reduces bring orders of magnitude scale-out capabilities at the same time that was budgeted.  

Every unit of deployment is also carefully studied to create templates and designs that can be reused across components. Virtual machines and their groups are easily t-shirt sized to meet the varying needs of different workloads and the steps taken to provision entire stacks on those leased resources also get executed automatically. This instantiates most resources customers demand from departments provisioning the infrastructure in a self-service model. Behind the scenes, the resources, their deployments, provisioning, usage calculations, and billing are automated to deliver reports that enable smarter use of those resources. With dry-runs and repeated walkthrough of execution steps, even the datacenters can be re-provisioned. This amount of flexibility resulting from templates and automation has proved critical for cloud-scale.

The container orchestration frameworks provide a good reference for automation and infrastructure design.