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Kubernetes Solutions

Expert Steps 8H 55M 72 Credits

Containerized applications have changed the game and are here to stay. With Kubernetes, you can orchestrate containers with ease, and integration with the Google Cloud Platform is seamless. In this advanced-level quest, you will be exposed to a wide range of Kubernetes use cases and will get hands-on practice architecting solutions over the course of 9 labs. From building Slackbots with NodeJS, to deploying game servers on clusters, to running the Cloud Vision API, Kubernetes Solutions will show you first-hand how agile and powerful this container orchestration system is.

Infrastructure Application Development

Prerequisites

This Quest builds on an understanding of Kubernetes and the Google Kubernetes Engine, and extends basic GKE operations into integrations with other GCP services. It is recommended that the student has earned the Badge for the Cloud Architecture Quest and the Kubernetes in the Google Cloud Quest before beginning.

Quest Outline

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Managing Deployments Using Kubernetes Engine

Dev Ops best practices make use of multiple deployments to manage application deployment scenarios. This lab provides practice in scaling and managing containers to accomplish common scenarios where multiple heterogeneous deployments are used.

Deutsch English español (Latinoamérica) français 日本語 한국의 português (Brasil)
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Build a Slack Bot with Node.js on Kubernetes

In this lab you'll learn how to build and run a Slack Bot with Google Cloud Platform uses Kubernetes Engine, a hosted version of Kubernetes. Watch the short video Build a Slack Bot with Node.js on Kubernetes

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warning Using Kubernetes Engine to Deploy Apps with Regional Persistent Disks

In this lab you will learn how to configure a highly available application by deploying WordPress using regional persistent disks on Kubernetes Engine.

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NGINX Ingress Controller on Google Kubernetes Engine

Hands-on lab to deploy the NGINX Ingress Controller on Google Kubernetes Engine.

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Distributed Load Testing Using Kubernetes

Lab has instructions to conduct distributed load testing with Kubernetes, which includes a sample web application, Docker image, and Kubernetes controllers/services.

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Running Dedicated Game Servers in Google Kubernetes Engine

This lab will show you how to use an expandable architecture for running a real-time, session-based multiplayer dedicated game server using Kubernetes on Google Container Engine.

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Awwvision: Cloud Vision API from a Kubernetes Cluster

This hands-on lab uses Kubernetes and Cloud Vision API to create an example of how to use the Vision API to classify (label) images from Reddit’s /r/aww subreddit and display the labelled results in a web app.

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Running a MongoDB Database in Kubernetes with StatefulSets

Containers are becoming a popular way to run and scale applications across multiple cloud providers or on both cloud and on-premise hardware. This lab provides a quick introduction to running a MongoDB database on Kubernetes Engine using Docker.

Deutsch English español (Latinoamérica) français 日本語 한국의 português (Brasil)
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Kubeflow End to End

In this hands-on lab, you will install Kubeflow on an empty Kubernetes Engine cluster and use it to train and serve a sequence-to-sequence model using TensorFlow, Keras, and SeldonIO.

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Deploy a Web App on GKE with HTTPS Redirect using Lets Encrypt

This lab shows you how to deploy a web app with a browser-trusted TLS certificate. You also deploy an HTTPS redirect on GKE using Let's Encrypt, NGINX Ingress, and Cloud Endpoints.

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