Course Overview of Manage Scalable Workloads in GKE

This advanced course helps learners modernize and manage scalable workloads using Google Kubernetes Engine (GKE). Through instructor-led sessions, classroom activities, quizzes, and hands-on labs, participants will explore multi-cluster architectures, GKE fleets, Cloud Service Mesh, configuration management, networking, identity management, CI/CD pipelines, and AI/ML workloads on GKE.

After completing Manage Scalable Workloads in GKE students will be able to:

  • Design and manage scalable multi-cluster GKE environments.
  • Implement and manage GKE fleets across hybrid infrastructures.
  • Configure and secure Cloud Service Mesh deployments.
  • Build multi-cluster networking architectures.
  • Manage authentication and identity in GKE environments.
  • Manage authentication and identity in GKE environments.
  • Apply security posture management and compliance controls.
  • Implement scalable CI/CD pipelines for Kubernetes workloads.
  • Explore AI/ML model training and serving using GKE.

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Key Features of Manage Scalable Workloads in GKE

  •  Multi-Cluster GKE Architecture

  • GKE Fleets and Configuration Management

  • Advanced Networking with GKE

  • Cloud Service Mesh Deployment and Routing

  • Service Mesh Security

  • Identity and Access Management at Scale

  • CI/CD and Software Supply Chain Security

  •  AI and GKE Integration

Who should Attend Manage Scalable Workloads in GKE Course?

  • • Google Cloud Practitioners
  • • Kubernetes Administrators
  • • Cloud Architects
  • • Platform Engineers
  • • Hybrid Infrastructure Teams

Prerequisites of Manage Scalable Workloads in GKE

  • Completion of Google Cloud Platform Fundamentals: Core Infrastructure or equivalent experience
  • Completion of Architecting with GKE or equivalent experience

    • Learning Objective of Google Kubernetes Engine

    • Understand scalable Kubernetes and GKE architecture concepts
    • Design and manage multi-cluster GKE environments
    • Implement GKE fleets and centralized cluster management
    • Configure GitOps workflows using Config Sync and Policy Controller
    • Deploy and manage Cloud Service Mesh
    • Implement advanced networking and traffic management strategies
    • Secure Kubernetes workloads using mTLS and identity management
    • Apply compliance and security posture best practices
    • Build CI/CD pipelines for Kubernetes applications
    • Deploy and optimize AI and ML workloads on GKE
    • Apply operational best practices for scalable Kubernetes infrastructure

    Why choose CloudThat as your training partner?

    • Specialized Google Cloud and Kubernetes Expertise  -CloudThat specializes in cloud-native technologies, Kubernetes, DevOps, and Google Cloud solutions with a strong focus on enterprise implementation practices. 
    • Industry-Recognized Trainers -Our trainers are certified Google Cloud and Kubernetes experts with practical experience in scalable cloud-native architectures and production-grade Kubernetes deployments. 
    • Hands-On Learning Approach - CloudThat emphasizes practical learning through labs, real-world scenarios, troubleshooting exercises, and implementation-focused demonstrations. 
    • Customized Learning Paths - Training paths are designed for DevOps engineers, cloud architects, Kubernetes administrators, and platform engineering teams with varying experience levels. 
    • Interactive and Enterprise-Focused Sessions - Sessions include architecture discussions, deployment walkthroughs, live demonstrations, and operational best practices.
    • Career and Certification Support - CloudThat supports learners with project guidance, interview preparation, and cloud-native career learning paths. 
    • Updated Industry-Relevant Content - Course materials are continuously updated to align with the latest GKE, Kubernetes, service mesh, CI/CD, and AI infrastructure advancements.
    • Trusted by Global Enterprises - Thousands of professionals and enterprise customers trust CloudThat for advanced cloud-native and Kubernetes training programs. 

    Course Outline for Manage Scalable Workloads in GKE Download Course Outline

    Topics

    • Multi-Cluster Overview
    • GKE Fleets
    • Sameness and Trust
    • Fleet Management

    Learning Outcomes

    • Understand multi-cluster infrastructure challenges.
    • Explain GKE fleet concepts and operations.
    • Manage fleets using sameness and trust principles.

    Activities

    • Fleet Architecture Discussion
    • Multi-Cluster Management Demo
    • Quiz

    Topics

    • Centralized Cluster Management
    • Multi-Cluster GKE
    • Fleet Cluster Connectivity
    • Secure Cluster Access

    Learning Outcomes

    • Design centralized multi-cluster architectures.
    • Connect and manage fleet clusters securely.
    • Access GKE fleet clusters effectively.

    Activities

    • Multi-Cluster Architecture Exercise
    • Fleet Connectivity Demo
    • Quiz

    Topics

    • GKE Fleets
    • Fleet Solutions
    • Fleet Team Management
    • Fleet Operations

    Learning Outcomes

    • Manage workloads and teams at scale.
    • Solve operational challenges using fleets.
    • Implement fleet governance strategies.

    Activities

    • Fleet Management Lab
    • Team Governance Workshop
    • Quiz

    Topics

    • Configuration Management Challenges
    • Config Sync
    • Policy Controller
    • Config Connector
    • Blueprints

    Learning Outcomes

    • Implement centralized GitOps-based configuration management.
    • Enforce security and compliance policies.
    • Build reusable Kubernetes deployment foundations.

    Activities

    • Config Sync Lab
    • Policy Controller Exercise
    • Blueprint Configuration Workshop

    Topics

    • Fleet Networking Communications
    • Pod Discovery
    • Multi-Cluster Services
    • Multi-Cluster Gateway

    Learning Outcomes

    • Configure multi-cluster networking.
    • Enable service discovery across clusters.
    • Implement multi-cluster gateways.

    Activities

    • Multi-Cluster Gateway Lab
    • Networking Configuration Exercise
    • Quiz

    Topics

    • Cloud Service Mesh Overview
    • Provisioning Service Mesh
    • Request Handling
    • Monitoring Service Mesh

    Learning Outcomes

    • Deploy and manage Cloud Service Mesh.
    • Monitor workload telemetry and tracing.
    • Understand mesh communication flows.

    Activities

    • Cloud Service Mesh Installation Lab
    • Telemetry Dashboard Exercise
    • Quiz

    Topics

    • Istio API Resources
    • VirtualService and DestinationRule
    • ServiceEntry
    • Gateway Configuration
    • WorkloadEntry and WorkloadGroup

    Learning Outcomes

    • Configure advanced traffic routing.
    • Manage traffic for external services.
    • Implement resilience testing and fault injection.

    Activities

    • Traffic Flow Management Lab
    • Routing Policy Workshop
    • Resilience Testing Exercise

    Topics

    • Authentication and Encryption
    • Service Authentication
    • End-User Authentication
    • Authorization Policies

    Learning Outcomes

    • Secure traffic between microservices.
    • Configure authentication and authorization.
    • Implement granular access controls.

    Activities

    • mTLS Security Lab
    • Policy Controller Exercise
    • Security Workshop

    Topics

    • East-West Traffic Routing
    • Multi-Network Communication
    • Multi-Cluster Mesh Architectures

    Learning Outcomes

    • Build secure multi-cluster networking architectures.
    • Enable communication across clusters and networks.
    • Configure east-west gateways.

    Activities

    • Distributed Services Lab
    • Multi-Cluster Mesh Exercise
    • Quiz

    Topics

    • GKE Identity Service
    • Connect Gateway
    • Authentication and Authorization
    • Third-Party Identity Providers
    • Fleet Workload Identity

    Learning Outcomes

    • Configure GKE authentication methods.
    • Integrate OpenID Connect and third-party IdPs.
    • Secure access to GKE fleet clusters.

    Activities

    • Authentication at Scale Lab
    • Identity Federation Exercise
    • Quiz

    Topics

    • GKE Security Posture
    • Security Dashboard
    • Node Security
    • Vulnerability Scanning
    • Security Command Center

    Learning Outcomes

    • Assess and improve GKE security posture.
    • Implement node and workload protection.
    • Use vulnerability scanning and security tools.

    Activities

    • Security Posture Assessment
    • Vulnerability Scanning Exercise
    • Quiz

    Topics

    • Cloud Build and GKE
    • Cloud Deploy
    • Knative Serving
    • Private Network CI/CD
    • Software Supply Chain Security

    Learning Outcomes

    • Build scalable CI/CD pipelines.
    • Secure software supply chains.
    • Deploy workloads using Cloud Deploy and Knative.

    Activities

    • CI/CD Pipeline Lab
    • Deployment Strategy Workshop
    • Security Controls Exercise

    Topics

    • AI and GKE Overview
    • AI Model Training
    • AI Model Serving
    • AI Cost Management

    Learning Outcomes

    • Deploy AI workloads on GKE.
    • Design model training and serving architectures.
    • Optimize costs for AI/ML workloads.

    Activities

    • AI Deployment Discussion
    • AI Deployment Discussion
    • Cost Optimization Workshop

    Certification Details of Manage Scalable Workloads in GKE

      CloudThat Course Completion Certificate will be awarded to all learners who complete the training.

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    Course ID: 28315

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    FAQs for Manage Scalable Workloads in GKE Course

    This course is designed for cloud practitioners and engineers managing scalable Kubernetes workloads using GKE.

    Yes. The course includes multiple labs, classroom activities, networking exercises, and CI/CD implementations.

    The course covers GKE, GKE fleets, Cloud Service Mesh, Config Sync, Cloud Deploy, and related Google Cloud services.

    Yes. Multi-cluster services, gateways, and east-west routing are major topics in the course.

    Yes. Learners will work with mTLS, policy enforcement, authentication, compliance, and vulnerability scanning.

    3-day instructor-led training with lectures, labs, quizzes, and classroom activities.

    Yes. Prior GKE and Kubernetes knowledge is strongly recommended.

    Yes. A CloudThat Course Completion Certificate will be awarded after successful completion of the course.

    Yes, the course includes deployment and optimization of AI/ML workloads on GKE.

    The course includes GKE, GKE Fleets, Cloud Service Mesh, Config Sync, Policy Controller, Cloud Build, Cloud Deploy, Security Command Center, and workload identity services.

    Enquire Now