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T-GKEE-AOfficial Google Curriculum

Manage Scalable Workloads in GKE Enterprise

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Overview

Discover how to modernize, manage, and observe applications at scale using Google Kubernetes Engine. This course uses lectures and hands-on labs to help you explore and deploy using Google Kubernetes Engine (GKE), GKE fleets, Cloud Service Mesh, and config controller capabilities that will enable you to work with modern applications, even when they are split among multiple clusters hosted by multiple providers.

What You'll Learn

  • Describe the challenges of designing a multi-cluster infrastructure
  • Describe the components and architecture of GKE fleets
  • Identify and describe the core components of a GKE fleet
  • Create, connect, and manage GKE clusters from multiple deployment environments
  • Describe how fleets discover and communicate with each other in GKE
  • Detail the benefits of using Service Mesh
  • Use Service Mesh to implement advanced routing and traffic management
  • Secure traffic between microservices using Cloud Service Mesh
  • Create multi-cluster networking architectures with Cloud Service Mesh
  • Use authentication to effectively manage identity in GKE at scale
  • Evaluate and apply various security measures to effectively protect and manage GKE deployments
  • Evaluate options and Google Cloud products that allow you to create scalable CI/CD implementations within a multi-cluster GKE environment
  • Explore how GKE facilitates the deployment and optimization of AI models

Who Should Attend

Google Cloud practitioners and individuals using Google Cloud to create, integrate, or modernize solutions using secure, scalable microservices architectures in hybrid environments

Prerequisites

Having completed Google Cloud Platform Fundamentals: Core Infrastructure or having equivalent experience. Having completed Architecting with GKE or having equivalent experience.

Course Modules

1

Introduction to GKE at scale

Topics

  • Multi-cluster overview
  • GKE fleets
  • Sameness and trust
  • GKE fleet management

Learning Outcomes

  • Recognize the challenges of designing and building multi-environment solutions
  • Explain how GKE uses fleets to streamline operations
  • Describe the concepts of sameness and trust and use them to manage fleets
  • Identify the features and components used to manage GKE fleets

Activities

Quiz
2

Multi-cluster GKE architecture

Topics

  • Centralized cluster management
  • Multi-cluster GKE
  • Connect and manage fleet clusters
  • Access GKE fleet clusters

Learning Outcomes

  • Recognize how GKE can be used to centralize cluster management for multicluster environments
  • Examine the architecture of multi-cluster GKE
  • Create, connect, and manage GKE fleet clusters
  • Securely access GKE fleet clusters

Activities

Quiz
3

Fleets and teams

Topics

  • GKE fleets
  • Example fleet solutions
  • Fleet team management
  • Fleet management

Learning Outcomes

  • Define GKE fleets
  • Describe how GKE fleets can solve common cluster management problems
  • Manage fleets and teams in GKE
  • Detail the elements of fleet management

Activities

QuizLab: Manage Workloads at Scale with GKE Fleets and Teams
4

Managing GKE configuration at scale

Topics

  • Configuration management challenges
  • Centralized configuration management at scale
  • Config Sync
  • Policy controller
  • Config Connector
  • Blueprints

Learning Outcomes

  • Recognize the challenges of scaling multi-cluster, multi-tenant configurations
  • Configure a centralized configuration management using a GitOps model
  • Describe the benefits and architecture of Config Sync
  • Use policy controller to enforce security and compliance in GKE
  • Create a standardized, reusable, and policy-driven foundation for Kubernetes deployments

Activities

QuizLab: Automate GKE Configuration with Config Sync
5

Fleet networking

Topics

  • Fleet networking communications
  • Pod discovery in GKE
  • Multi-cluster Services
  • Configuring multi-cluster Services
  • Multi-cluster gateway
  • Configuring multi-cluster gateways

Learning Outcomes

  • Explain how fleet networking works
  • Describe how Pods in a Kubernetes cluster communicate with each other
  • Enable multi-cluster Services
  • Configure multi-cluster Services
  • Detail the elements of fleet management
  • Outline the role of a multi-cluster gateway
  • Configure a multi-cluster gateway

Activities

QuizLab: Deploying a Multi-Cluster Gateway Across GKE Clusters
6

Cloud Service Mesh

Topics

  • Introducing Cloud Service Mesh
  • Provisioning Cloud Service Mesh
  • Handling requests
  • Monitoring and supporting Cloud Service Mesh

Learning Outcomes

  • List and describe the benefits of using Cloud Service Mesh
  • Install and configure Cloud Service Mesh on different clusters
  • Trace the path of a request through the mesh, correctly identifying and explaining the role of key components like Envoy proxies, Mesh CA, and extensions in handling the request
  • Create Service Mesh dashboards from workload telemetry including metrics, traces, and logs

Activities

QuizLab: Installing Cloud Service Mesh on Google Kubernetes Engine
7

Cloud Service Mesh routing

Topics

  • Configuring Cloud Service Mesh with Istio API resources
  • Configuring VirtualService and DestinationRule
  • Configuring ServiceEntry
  • Configuring a Gateway
  • Configuring a WorkloadEntry and WorkloadGroup
  • Network resilience and testing

Learning Outcomes

  • Explain how Cloud Service Mesh learns the network from Kubernetes
  • Configure traffic behavior using VirtualService and DestinationRule
  • Manage traffic for services running outside the mesh using ServiceEntry
  • Configure Gateways to manage inbound and outbound traffic to the mesh
  • Explore how WorkloadEntry and WorkloadGroup onboards and manages non-Kubernetes workloads
  • Evaluate network resilience and test it through fault injection and traffic mirroring

Activities

QuizLab: Managing Traffic Flow with Cloud Service Mesh
8

Service Mesh security

Topics

  • Authentication and encryption
  • Service authentication in the mesh
  • End-user authentication in Cloud Service Mesh
  • Authorization in Cloud Service Mesh

Learning Outcomes

  • Encrypt traffic between microservices to prevent anyone in the network from gaining access to private information
  • Authorize services and requests, ensuring that services only access the information that is allowed access from other services
  • Authenticate and authorize services and requests to verify trust among services in the mesh and among end users
  • Limit service access in the network so that granular controls over the communication can be established

Activities

QuizLab: Secure Cloud Service Mesh with Policy Controller and mTLS
9

Multi-cluster networking with Cloud Service Mesh

Topics

  • Single network east-west routing
  • Multiple network east-west routing

Learning Outcomes

  • Set up a multi-cluster mesh with a single subnet in a single VPC network. Account for variations like multi-region clusters, multiple projects, shared VPC, and private clusters
  • Enable communication between GKE clusters on different networks using an east-west gateway and attached clusters

Activities

QuizLab: Manage and Secure Distributed Services with GKE Managed Service Mesh
10

Manage identity in GKE with authentication

Topics

  • Introduction to GKE Identity Service
  • Connect gateway overview
  • Configuring connect gateway for authentication and authorization
  • Accessing clusters with GKE Identity Service
  • Authenticating third-party identities with GKE Identity Service
  • Fleet Workload Identity

Learning Outcomes

  • Summarize the differences between authentication methods for GKE clusters and explain when to use each
  • Summarize the key features of connect gateway and explain how it simplifies and secures connections to GKE fleet member clusters
  • Configure connect gateway for authentication and authorization
  • Securely access clusters and provide authentication using OpenID Connect (OIDC) and third-party identity providers (IdPs)
  • Given a GKE cluster and a third-party identity provider (IdP), configure GKE Identity Service to enable authentication and authorization for users

Activities

QuizLab: Manage Authentication at Scale with Connect Gateway
11

Security posture, compliance, and preventative controls

Topics

  • GKE security posture overview
  • Security posture dashboard
  • Implementing node security
  • Vulnerability scanning
  • Additional security services

Learning Outcomes

  • Describe GKE security posture
  • Navigate and interpret the GKE security posture dashboard to identify security issues
  • Implement node security measures to protect GKE worker nodes from potential threats
  • Describe the process of vulnerability scanning in GKE
  • Explain the roles and capabilities of Google Cloud's Artifact Analysis and Security Command Center in enhancing GKE security

Activities

Quiz
12

CI/CD at scale in GKE

Topics

  • CI/CD in Google Cloud
  • Cloud Build and GKE
  • Cloud Deploy and GKE
  • Cloud Deploy: Policies, deployments, and security
  • Cloud Run and Knative serving
  • Cloud Deploy and Knative serving
  • CI/CD in a private network
  • Software supply chain security

Learning Outcomes

  • Describe the core components of Google Cloud's CI/CD pipeline and how they address common challenges in application modernization
  • Analyze how Cloud Deploy integrates with GKE to manage Kubernetes manifests and control deployments
  • Compare and contrast the deployment strategies for Knative serving within GKE
  • Explain the steps required to establish a peered VPC connection for secure CI/CD in a private network
  • Evaluate the various security measures and tools available within Google Cloud for securing the software supply chain

Activities

QuizLab: Creating CI/CD Pipelines for GKE Clusters
13

GKE and AI

Topics

  • AI and GKE overview
  • AI model training on GKE
  • AI model serving on GKE
  • AI cost management on GKE

Learning Outcomes

  • Explain how GKE serves as a suitable platform for large language models and the increasing demand for hardware accelerators
  • Describe the high-level architecture of a GKE-based training platform for AI models
  • Outline the architecture for a GKE-based model serving platform
  • Outline different cost management strategies available when using GKE for AI/ML workloads

Activities

Quiz

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Course Details

Course Code
T-GKEE-A
Duration
3 days
Format
ILT
Level
Advanced
Modules
13
Activities
9
Price
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