Cloud

This post links to all ten parts of my Google Cloud PCA exam study guide.

This is the final post in the series, covering “everything else” on the exam. If you’ve made it this far in your studying journey and feel confident in the content throughout all 10 blog posts, you’re ready. Good luck!

This post covers all things databases and data tooling. Choosing the right tool from Google Cloud’s extensive repository of managed services can be tricky. Look out for naming conventions of services, such as DataFLOW and DataSTREAM.

This post covers all things Anthos, see Part VII for Kubernetes. Anthos is usually reserved for complex enterprise deployments and won’t come up in the real world that often, but it is on the exam.

This post covers all things GKE, Anthos is covered in Part VIII. Be ready to run kubectl commands to perform most of the tasks in this post, especially rolling our or rolling back a deployment.

This post covers all managed compute options that are not VMs or Kubernetes (GKE). That basically means App Engine, Functions, and Cloud Run. Trust me, the future is Cloud Run!

This post is all about virtual machines (VMs) in Google Cloud. You’ll learn about MIGs, snapshotting disks, PDs, and everything else you can attach to a VM.

This post is all about storage and data encryption. Remember, ingress is always free – cloud providers make money on egress!

This post covers security including Cloud Identity, IAM, encryption, and other security management products.

This posts covers networking including VPC constructs and load balancing. If you have a chance to do a lab, spend time setting up a global load balancer.