Kubernetes supports deployments that represents a set of multiple Pods to run multiple replicas of an application and replaces the instances when they are unresponsive. In this course you will recognize the key Kubernetes deployment strategies and the elements of the manifest file for the deployment strategies, review the workload resources that are used by Kubernetes to manage deployments and Pods. You'll recognize the different states of deployment lifecycle, the scenarios of using the StatefulSet workload API object, including the components and the limitations associated with StatefulSet in deployments. Next, you'll implement deployments that create and bring three replicated Pods, define the selection rules to help deployments find which Pods to manage, update deployments, view rollout status and deployment update information. Moving on, you'll use Kubectl commands to inspect rollouts, pause and resume rollouts to rollback updates, check the revisions of deployments, rollback deployments, manage Pods, scale out and customize resource definition of deployments. Next, you'll use Kubectl commands to scale specific StatefulSet by increasing replicas, diagnose Pods. And finally, you'll set up Autoscaler for deployment and specify the minimum and maximum number of Pods based on the CPU utilization of the existing Pods. This course is part of a series that aligns with the objectives for the Certified Kubernetes Administrator exam and can be used to prepare for this exam.