Expert Steps 8시 55분 72 크레딧
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.
PrerequisitesThis 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.
Dev Ops 권장사항은 여러 배포를 이용하여 애플리케이션 배포 시나리오를 관리합니다. 이 실험실에서는 컨테이너를 조정 및 관리하여 여러 이종 배포가 활용되는 일반적 시나리오를 수행하는 연습을 합니다.
In this lab you will learn how to configure a highly available application by deploying WordPress using regional persistent disks on Kubernetes Engine.
Hands-on lab to deploy the NGINX Ingress Controller on Google Kubernetes Engine.
Lab has instructions to conduct distributed load testing with Kubernetes, which includes a sample web application, Docker image, and Kubernetes controllers/services.
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.
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.
컨테이너는 여러 클라우드 제공업체 간 또는 클라우드와 내부 하드웨어 모두에서 애플리케이션을 실행하고 조정하는 방법으로 인기를 얻고 있습니다. 이 실험실에서는 Kubernetes에서 Docker를 사용해 MongoDB 데이터베이스를 실행하는 과정을 간략하게 소개합니다.
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.
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.