Architecting with Google Kubernetes Engine Certification Overview:

This course features a combination of lectures, demos, and hands-on labs to help you explore and deploy solution elements—including infrastructure components like pods, containers, deployments, and services—along with networks and application services. You will also learn how to deploy practical solutions involving security, access management, resource management, and monitoring.

After completing this course on Architecting with Google Kubernetes Engine Training, Students will be able to:

  • Create and manage workloads in Google Kubernetes Engine.
  • Explain and configure pod networking within GKE.
  • Define and implement various Kubernetes storage abstractions.
  • Manage security, including authentication and authorization.
  • Monitor applications effectively using Google Cloud tools.
  • Configure CI/CD pipelines to optimize application releases.

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Key Features of Architecting with Google Compute Engine Course:

  • Comprehensive Hands-on Learning: Includes 7 modules, 6 labs, and 14 classroom activities for practical skill development.  

  •  Full Lifecycle Management: Covers everything from initial workload creation to CI/CD pipeline configuration. 

  • Deep Infrastructure Insight: Detailed exploration of pod networking and Kubernetes storage abstractions. 

  •  Managed Service Integration: Learn to contrast and use Google Cloud managed storage and database services with GKE. 

  • Security & Identity Focus: Specific focus on authentication, authorization, and using Cloud SQL Auth Proxy with Workload Iden

Who Should Attend this Course on Architecting with Google Kubernetes Engine Specialization:

  • Cloud architects, administrators, and SysOps/DevOps personnel

Prerequisites:

    Understanding of cloud computing concepts and basic experience with containerization is recommended based on the course level.

Why choose CloudThat as your Architecting with Google Kubernetes Engine Training Partner?

  • Specialized GCP Focus: CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP. 
  • Industry-Recognized Trainers: CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios. 
  • Hands-On Learning Approach: CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set. 
  • Customized Learning Paths: CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills.
  • Interactive Learning Experience: CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course.
  • Placement Assistance and Career Support: CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals.
  • Continuous Learning and Updates: CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge.
  • Positive Reviews and Testimonials: Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training.

Learning objective of the course:

  •  Workload Management: Master the creation and management of GKE workloads.  
  •  Networking & Storage: Understand pod networking and compare managed vs. self-managed storage options. 
  • Security Implementation: Use Cloud SQL Auth Proxy and Workload Identity for secure database connections. 
  •   CI/CD Optimization: Identify best practices for CI/CD pipelines on Google Cloud to optimize app releases. 
  • Monitoring & Resource Management: Learn to monitor GKE applications and manage resources effectively.

Course Outline Download Course Outline

Lecture Content

  • Review of containerization principles and Docker fundamentals
  • Review of containerization principles and Docker fundamentals
  • Pod abstractions and standard Kubernetes lifecycle states
  • GKE infrastructure offerings (Standard vs. Autopilot modes)

Learning Objectives

  • Contrast the structural differences between Standard and Autopilot GKE clusters
  • Explain how pods leverage node resources within a containerized environment

Lab Content

  • NA

Lecture Content

  • Orchestrating container deployments via Deployments and ReplicaSets
  • Managing application elements, scaling workloads, and rolling updates
  • Designing declarative manifests for multi-container configurations
  • Pod lifecycles, liveness, and readiness probe strategies

Learning Objectives

  • Deploy and programmatically manage scalable application workloads on a GKE cluster
  • Implement configuration maps, secrets, and zero-downtime rolling updates

Lab Content

  • Lab: Deploying and Managing Containerized Applications on GKE

Lecture Content

  • Deep dive into intra-cluster pod networking paradigms and IP allocation
  • Exposing container workloads using Kubernetes Service types (ClusterIP, NodePort, LoadBalancer)
  • Advanced route discovery and ingress controller routing patterns
  • Implementing network security guidelines via Kubernetes Network Policies

Learning Objectives

  • Configure highly available internal and external networking paths for GKE workloads
  • Restrict intra-cluster network communication routes using strict policy filters

Lab Content

  • Lab: Configuring GKE Networking and Internal Load Balancing Services

Lecture Content

  • Decoupling ephemeral container lifecycles from persistent application data layers
  • Defining storage abstractions using Volumes, PersistentVolumes (PV), and PersistentVolumeClaims (PVC)
  • Mapping dynamically provisioned storage classes to persistent disk layers
  • Managing configuration states across pods using ConfigMaps and Kubernetes Secrets

Learning Objectives

  • Abstract underlying physical block storage infrastructures using PV and PVC definitions
  • Mount durable persistent storage drives safely inside running Kubernetes pods

Lab Content

  • Lab: Allocating Dynamic Block Storage and Managing Persistent Volumes

Lecture Content

  • Securing cluster administrative entry paths using Role-Based Access Control (RBAC)
  • Authentication and authorization parameters across developers and cluster services
  • Implementing telemetry tracking, alerting rules, and application health logs
  • Implementing telemetry tracking, alerting rules, and application health logs

Learning Objectives

  • Apply fine-grained RBAC policies to manage tenant permissions within specific namespaces
  • Establish automated monitoring dashboards and log sinks to track cluster infrastructure health

Lab Content

  • Lab: Hardening GKE Control Planes and Monitoring Workload Performance

Lecture Content

  • Strategies for pairing stateful database applications with container runtimes
  • Offloading transactional storage states from GKE into Cloud Storage and Cloud SQL
  • Securing service-to-service credential keys by implementing Workload Identity Federation
  • Architectural considerations for latency, multi-region failovers, and backup retention

Learning Objectives

  • Integrate GKE-hosted frontend workloads securely with fully managed external cloud databases
  • Enforce Workload Identity profiles to clear static token dependencies from application code

Lab Content

  • Lab: Using Cloud SQL with GKE and Workload Identity

Lecture Content

  • Building modern continuous integration and continuous deployment pipelines for microservices
  • Leveraging Google Cloud-supported developer tools: Cloud Build, Artifact Registry, and Cloud Deploy
  • Automating container image compilation, vulnerability scanning, and testing
  • Executing canary, blue-green, and progressive rollback rollout deployment patterns

Learning Objectives

  • Construct an automated, secure CI/CD orchestration pipeline targeting GKE test and production environments
  • Deploy updated microservices automatically upon standard code repository commit events

Lab Content

  • Lab: Engineering Automated GitOps Pipelines with GKE and Cloud Deploy

Lecture Content

  • Retrospective technical synthesis of core container orchestration concepts
  • Google-recommended operational checklists for production-grade GKE infrastructures
  • Advanced roadmap patterns: Service meshes, multi-cluster topologies, and continuous optimizations

Learning Objectives

  • Evaluate, synthesize, and plan scalable production infrastructure solutions utilizing best-practice GKE patterns

Lab Content

  • NA

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

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Course ID: 19195

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It is a 2-day intensive course.

You can take it as an Instructor-led Training (ILT) or On-demand.

Yes, the course includes 6 hands-on labs. 

Yes, specifically authentication, authorization, and secure service connections.

Yes, there is a dedicated module on CI/CD pipelines for GKE.

Yes, it includes pod networking and application services.

You will learn to use Cloud SQL Auth Proxy to connect to databases from within GKE.

Yes, you will learn to monitor applications running in GKE.

Yes, it covers Kubernetes storage abstractions and Google Cloud managed storage services.

Cloud architects, admins, and DevOps professionals.

Enquire Now