Deploying Containerized Workloads Using Google Cloud Kubernetes Engine

Dev & DevOps colleagues, the Deploying Containerized Workloads Using Google Cloud Kubernetes Engine program teaches you where GKE fits relative to other GCP compute options such as GCE VMs, App Engine, and Cloud Functions. You will understand fundamental building blocks in Kubernetes, such as pods, nodes and node pools, and how these relate to the fundamental building blocks of Docker, namely containers. Pods, ReplicaSets, and Deployments are core Kubernetes concepts, and you will understand each of these in detail. Next, you will discover how to create, manage, and scale clusters using the Horizontal Pod Autoscaler (HPA). You will also learn about StatefulSets and DaemonSets on the GKE. Finally, you will explore how to share states using volume abstractions, and field user requests using service and ingress objects. You will see how custom Docker images are built and placed in the Google Container Registry, and learn a new and advanced feature, binary authorization. When you’re finished with this course, you will have the skills and knowledge of the Google Kubernetes Engine needed to construct scalable clusters running Docker containers on the GCP. Gain high demand, marketable skills including: 1) Introducing Google Kubernetes Engine (GKE) -  Introducing Containers & Kubernetes, Clusters, Nodes, Node Pools, and Node Images, Pods, Kubernetes as an Orchestrator, Replication and Deployment, Services, Volume Abstractions, Load Balancers,  Ingress, StatefulSets and DaemonSets, Horizontal Pod Autoscaler, Pricing; 2) Creating and Administering GKE Clusters - Web Console: Creating a GKE Cluster, Deployments, Exposing a Service, Behind the Scenes Firewall Rules and the Load Balancer, Deleting the Service Deployment and the Cluster, gcloud: Creating a Regional Cluster, Creating and Updating Zonal Clusters, Configuring Custom Node Pools and Resizing Clusters, Using kubectl to Manage Deployments and Expose Services and Update Clusters Delete Services and Deployments, Configure a Horizontal Pod Autoscaler Using kubect, Scaling Clusters Using the Horizontal Pod Autoscaler 3m; 3) Deploying Containerized Workloads to GKE Clusters - Creating a Custom Docker Image, Registering a Custom Image with the Google Container Registry, Deploying a Custom Image and Exposing a Service, Creating and Configuring Ingress Objects, Working with Ingress Objects, Persistent Volume Claims, Deploying and Exposing Multiple Services, Exploring Services Pods Using kubectl, Binary Authorization, Create and Deploy a Custom Test Container, Enable Binary Authorization and Secure Cluster with a Policy,  Create a Note and Associate It with an Attestor, Generate and Associate a Public Key with the Attestor 4m and Deploy Signed Containers; and 4) Monitoring GKE Clusters Using Stackdriver - Monitoring Clusters Using Stackdriver and Prometheus, Enabling Stackdriver Kubernetes Monitoring, Stackdriver Kubernetes Monitoring, Configuring and Viewing Alerts and Prometheus Metrics on Stackdriver.

Enroll today (teams & execs welcome): https://pluralsight.pxf.io/MXLRJn 

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