Kubernetes Administrator: Managing Kubernetes Deployments

Kubernetes    |    Intermediate
  • 14 videos | 1h 8m 38s
  • Includes Assessment
  • Earns a Badge
Rating 4.4 of 67 users Rating 4.4 of 67 users (67)
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.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Describe the key kubernetes deployment strategies and specify the elements of the manifest file for each deployment strategy
    Recognize the workload resources that are used by kubernetes to manage deployments and sets of pods
    Implement deployments that create and bring three replicated pods and define the selection rules to help deployments find which pods to manage
    Update deployments and use kubectl commands to view deployments, rollout status and deployment update information
    Use kubectl rollout commands to inspect rollouts as they occur, pause and resume rollouts to rollback updates and to view an object's rollout history
    Use kubectl commands to check the revisions of deployments and rollback deployments from current version to previous version
  • Recall the different states of deployment lifecycle along with the characteristics of each state
    Use kubectl commands to manage pods, scale out and customize the resource definition of deployments
    Recognize the scenarios of using the statefulset workload api object, its components and the limitations that need to be considered when utilizing statefulset in deployments
    Use kubectl commands to list statefulset and scale specific statefulset by increasing replicas
    Use kubectl commands to diagnose pods by listing the initcontainer status of the pods including all the running and unhealthy pods
    Set up an autoscaler for deployment and specify the minimum and maximum number of pods based on the cpu utilization of the existing pods
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 29s
  • 5m 33s
  • Locked
    3.  Workload Resource
    6m 25s
  • Locked
    4.  Creating Deployment and Replicaset
    5m 47s
  • Locked
    5.  Updating and Viewing Deployment Status
    4m 43s
  • Locked
    6.  Inspecting Rollout and Rollback Update
    7m 55s
  • Locked
    7.  Implementing Deployment Rollback
    3m 57s
  • Locked
    8.  Deployment Lifecycle and States
    5m 12s
  • Locked
    9.  Managing Pod and Customizing Resource Definition
    7m 33s
  • Locked
    10.  Scenarios of Using StatefulSet Workload
    7m 43s
  • Locked
    11.  Listing StatefulSet and Scaling StatefulSet
    2m 51s
  • Locked
    12.  Diagnosing Pods with Commands
    4m 3s
  • Locked
    13.  Setting up Autoscaler
    3m 46s
  • Locked
    14.  Course Summary
    1m 41s

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