IT admins have a lot of boxes to check when it comes to VM deployment and provisioning. First, they set up the processor, memory, network and other resources to create the necessary virtual environment, and then they load and configure the desired image file into that virtual environment so the image can run.
While this process isn't difficult, it does require time and attention -- and the same can be said of container deployment, as well. It's certainly possible for an IT administrator to deploy and configure 10 or 20 VMs or containers, but it's impractical for humans to deploy more than 100 error-free instances on demand.
Instead, operations teams can implement automated VM deployment tools, such as Ayehu, vCenter Orchestrator and Ansible, as well as container orchestration tools, such as Kubernetes. These tools stipulate the characteristics of a virtual instance, such as the instance name, number of virtual CPUs, memory and disk space, as well as configuration details such as the desired image, IP address and access credentials. These workflows can include a pause for human approvals, if needed.
The use of automation and orchestration in IT is a fundamental part of advanced software-defined technologies, such as the software-defined data center and infrastructure as code. In addition, automated VM deployment tools increasingly embrace technologies such as AIOps, where machine learning and artificial intelligence make autonomous provisioning and configuration decisions with little, if any, human interaction or approval.