Google Cloud Solutions I: Scaling Your Infrastructure
Expert 8단계 1일 크레딧 60개
In this advanced-level quest, you will learn how you to harness serious GCP power and infrastructure. The hands-on labs will give you use cases, and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your GCP projects to the next level.
기본 요건:This Quest expects solid hands-on proficiency with Google Cloud workflows and processes, especially those involving multiple services working together. It is recommended that the student have at least earned a Badge by completing the hands-on labs in the Kubernetes Solutions and Networking in the Google Cloud Quests before beginning. Additional experience with the labs in the Cloud Architecture Quest will also be useful.
This lab shows you how to set up multiple NAT gateways with Equal Cost Multi-Path (ECMP) routing and autohealing enabled for a resilient and high-bandwidth deployment.
This lab describes how to deploy an autoscaling Compute Engine instance group that is automatically scaled using a custom Cloud monitoring metric
This hands-on lab will show you how to set up Jenkins on Google Kubernetes Engine to help orchestrate your software delivery pipeline.
Kubernetes Engine 클러스터를 만들고, 애플리케이션을 배포하며, Spinnaker를 사용하여 애플리케이션에 변경사항이 생기면 지속적으로 배포합니다.
In this Qwiklab, you set up a redundant pair of Windows Domain Controllers (DC) with AD using a new Virtual Private Cloud (VPC) network and multiple subnets on Google Cloud Platform (GCP).
In this lab you'll learn how to deploy a cluster of distributed Memcached servers on Kubernetes Engine using Kubernetes, Helm, and Mcrouter.
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.
Lab has instructions to conduct distributed load testing with Kubernetes, which includes a sample web application, Docker image, and Kubernetes deployments/services.