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This repository guides you through deploying a private GKE cluster and provides a base platform for hands-on exploration of several GKE related topics which leverage or integrate with that infrastructure. After completing the exercises in all topic areas, you will have a deeper understanding of several core components of GKE and GCP as configured in an enterprise environment.
Building applications with bazel and deploying them on to GKE. This demo contains a java-spring-boot rest service and an angular front-end. Both containers are deployed on GKE.
This demo aims to show what a fully-featured project running in Kubernetes Engine looks like. It includes Elasticsearch, a very popular open-source project for indexing and searching data, as well as some custom software to interface with it.
This project demonstrates how Istio's mesh expansion feature can be used to link services accross a VPN. The feature allows for a non-Kubernetes service running outside of the Istio infrastructure on Kubernetes Engine, to be integrated into, and managed by the Istio service mesh.
This project describes the steps required to deploy a sample application to Kubernetes Engine that forwards log events to Stackdriver Logging. As a part of the exercise, you will create a Cloud Storage bucket and a BigQuery dataset for exporting log data.
This project walks you through setting up monitoring and visualizing metrics from a Kubernetes Engine cluster. The logs from the Kubernetes Engine cluster will be leveraged to walk through the monitoring capabilities of Stackdriver.
gke-tf was created to streamline the creation of customized Terraform source files that build GKE clusters and supporting resources in GCP.
This project introduces you to Stackdriver's tracing feature, and provides a distributed tracing example that can serve as a basis for your own applications. You will deploy a multi-tier application to a Kubernetes Engine cluster and trace calls between the components.
This demo builds two GKE Clusters and guides you through using secrets in Vault, using Kubernetes authentication from within a pod to login to Vault, and fetching short-lived Google Service Account credentials on-demand from Vault within a pod.
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