Architecting with Google Kubernetes Engine Certification Overview:

Whether you’re a seasoned DevOps pro or a cloud-curious explorer, this course will equip you with: 

  • Deploying and managing containerized applications confidently, understanding pods, containers, deployments, and services, and becoming a GKE master. 
  • Go Beyond the engine by diving into Google Cloud’s rich ecosystem, seamlessly integrating tools like Cloud Storage, Clod-SQL, and Cloud Load Balancing with your GKE deployments. 
  • Immerse yourself in interactive labs, crafting real-world solutions for security, access control, resource management, and comprehensive monitoring. 
  • Be network savvy by architecting secure and flexible networks for your GKE clusters, mastering concepts like VPCs, subnets, and firewalls. 
  • Build robust application services and ensure high availability, scalability, and fault tolerance. 

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

  • Break down the concept of software containers, understanding their benefits and how they revolutionize application development.
  • Explore the internal working mechanism of Kubernetes, the orchestration platform that empowers your containerized dreams.
  • Navigate the Google Cloud Platform ecosystem, understanding how its components like Cloud Storage and Cloud SQL seamlessly integrate with your GKE clusters.
  • Grasp the intricacies of pod networking in GKE, ensuring secure and reliable communication within your containerized world.
  • From the Google Cloud Console to gcloud/kubectl commands, craft and manage your GKE clusters like a pro.
  • Launch, roll back, and expose jobs in Kubernetes with ease, controlling your application lifecycle with precision.
  • Implement robust access control using Kubernetes RBAC and IAM, guarding your clusters against unauthorized access.
  • Design pod security policies and network policies, solidifying your containerized fortress.
  • Keep sensitive credentials and configuration settings under lock and key using Secrets and ConfigMaps.
  • Discover Google Cloud's managed storage services like Cloud Storage and Cloud SQL, finding the perfect match for your application needs.
  • Monitor your applications running in GKE, proactively identifying and resolving issues.

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Key Features of Architecting with Google Compute Engine Course:

  • Our Google Cloud Platform training modules have 50% - 60% hands-on lab sessions to encourage Thinking-Based Learning (TBL).
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL).
  • GCP certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL).
  • Well-structured Case-Studies to simulate challenges encountered in a Real-World environment during Google Cloud Platform training.
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform.
  • Being an official Google Cloud Platform Training Partner, we offer authored curriculum that are at par with industry standards.

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

  • Cloud architects, administrators, and SysOps/DevOps personnel
  • Individuals using Google Cloud to create new solutions or to integrate existing systems, application environments, and infrastructure with Google Cloud.

Prerequisites:

    To get the most out of this course, participants should:
  • Completed “Google Cloud Fundamentals: Core Infrastructure” or have equivalent experience.

    • 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:

    • Confidently deploy and manage containerized applications on GKE, understanding pods, containers, deployments, and services. Design and implement scalable, resilient architectures for your containerized workloads.
    • Seamlessly integrate Google Cloud Platform services like Cloud Storage, Cloud SQL, and Cloud Load Balancing with your GKE deployments. Leverage the robust GCP ecosystem to build comprehensive and efficient solutions.
    • Implement robust security practices for your GKE clusters, including access control using Kubernetes RBAC and IAM, pod security policies, and network policies. Ensure reliable communication within your containerized world through pod networking best practices.
    • Effectively manage resources and monitor your GKE applications. Utilize Google Cloud tools to ensure high availability, scalability, and fault tolerance. Proactively identify and resolve issues in your containerized environment.
    • Master the Google Cloud Console and gcloud/kubectl commands to efficiently manage your GKE clusters. Automate tasks and perform advanced operations to become a proficient GKE architect.

    Course Outline Download Course Outline

    Topics:

    • Use the Google Cloud Console
    • Use Cloud Shell
    • Define Cloud Computing
    • Identify Google Cloud Compute Services
    • Understand Regions and Zones
    • Understand the Cloud Resource Hierarchy
    • Administer your Google Cloud Resources

    Objectives:

    • Identify Google Cloud services and their function.
    • Choose the right Google Cloud services to create your own Cloud solution.

    Activities:

    • 1 lab and 1 quiz.

    Topics:

    • Create a Container Using Cloud Build.
    • Store a Container in Container Registry.
    • Understand the Relationship Between Kubernetes and Google Kubernetes Engine (GKE).
    • Understand how to Choose Among Google Cloud Compute Platforms.

    Objectives:

    • Create a Container using Cloud Build.
    • Store a Container in Container Registry.
    • Compare and Contrast Kubernetes and GKE features

    Activities:

    • 1 lab and 1 quiz

    Topics:

    • Understand the Architecture of Kubernetes: Pods, Namespaces
    • Understand the Control-plane Components of Kubernetes
    • Create Container Images using Cloud Build
    • Store Container Images in Container Registry
    • Create a Kubernetes Engine Cluster

    Objectives:

    • Conceptualize the Kubernetes Architecture.
    • Deploy a Kubernetes Cluster using GKE.
    • Deploy Pods to a GKE Cluster.
    • View and Manage Kubernetes Objects.
    • Conceptualize the Migrate for Anthos process

    Activities:

    • 1 lab and 1 quiz

    Topics:

    • The Kubectl Command

    Objectives:

    • Work with the Kubectl Command.
    • Inspect the Cluster and Pods.
    • View a Pod’s Console Output.
    • Sign in to a Pod Interactively

    Activities:

    • 2 labs and 1 quiz

    Topics:

    • Deployments
    • Ways to Create Deployments
    • Services and Scaling
    • Updating Deployments
    • Rolling Updates
    • Blue/Green Deployments
    • Canary Deployments
    • Managing Deployments
    • Jobs and CronJobs
    • Parallel Jobs
    • CronJobs
    • Cluster Scaling
    • Downscaling
    • Node Pools
    • Controlling Pod Placement
    • Affinity and Anti-Affinity
    • Pod Placement Example
    • Taints and Tolerations
    • Getting Software into your Cluster

    Objectives:

    • Create and Use Deployments.
    • Create and Run Jobs and CronJobs.
    • Scale Clusters Manually and Automatically.
    • Configure Node and Pod Affinity.
    • Get Software into your Cluster with Helm Charts and Kubernetes Marketplace.

    Activities:

    • 3 labs and 1 quiz

    Topics:

    • Introduction
    • Pod Networking
    • Services
    • Finding Services
    • Service Types and Load Balancers
    • How Load Balancers Work
    • Ingress Resource
    • Container-Native Load Balancing
    • Network Security

    Objectives:

    • Create Services to expose applications that are running within Pods.
    • Use load balancers to expose Services to external clients.
    • Create Ingress resources for HTTP(S) load balancing.
    • Leverage container-native load balancing to improve Pod load balancing.
    • Define Kubernetes network policies to allow and block traffic to Pods.

    Activities:

    • 2 labs and 1 quiz

    Topics:

    • Volumes
    • Volume Types
    • The PersistentVolume Abstraction
    • More on PersistentVolumes
    • StatefulSets
    • ConfigMaps
    • Secrets

    Objectives:

    • Use Secrets to isolate security credentials.
    • Use ConfigMaps to isolate configuration artifacts.
    • Push out and roll back updates to Secrets and ConfigMaps.
    • Configure Persistent Storage Volumes for Kubernetes Pods.
    • Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts.

    Activities:

    • 2 labs and 1 quiz

    Topics:

    • Understand Kubernetes Authentication and Authorization
    • Define Kubernetes RBAC Roles and Role Bindings for Accessing Resources in Namespaces
    • Define Kubernetes RBAC Cluster Roles and ClusterRole Bindings for
    • Accessing Cluster-scoped Resources
    • Define Kubernetes Pod Security Policies
    • Understand the Structure of IAM
    • Define IAM roles and Policies for Kubernetes Engine Cluster Administration

    Objectives:

    • Define IAM roles and policies for GKE.
    • Define Kubernetes RBAC roles and role bindings.
    • Define Kubernetes pod security policies.

    Activities:

    • 2 labs and 1 quiz

    Topics:

    • Understand Kubernetes Authentication and Authorization
    • Define Kubernetes RBAC Roles and Role Bindings for Accessing Resources in Namespaces
    • Define Kubernetes RBAC Cluster Roles and ClusterRole Bindings for
    • Accessing Cluster-scoped Resources

    Objectives:

    • Use Cloud Monitoring to monitor and manage availability and performance.
    • Locate and inspect Kubernetes logs.
    • Create probes for wellness checks on live applications.

    Activities:

    • 2 labs and 1 quiz

    Topics:

    • Understand Pros and Cons for Using a Managed Storage Service Versus Self-managed Containerized Storage.
    • Enable Applications Running in GKE to Access Google Cloud Storage Services.
    • Understand Use Cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and BigQuery from within a Kubernetes Application.

    Objectives:

    • Understand use cases for Cloud Storage within a Kubernetes application.
    • Understand use cases for Cloud SQL and Cloud Spanner within a Kubernetes application.
    • Understand use cases for Datastore within a Kubernetes application.
    • Understand use cases for Cloud Bigtable within a Kubernetes application.

    Activities:

    • 1 lab and 1 quiz

    Topics:

    • CI/CD overview
    • CI/CD for Google Kubernetes Engine
    • CI/CD Examples
    • Manage application code in a source repository that can trigger code changes to a continuous delivery pipeline.

    Objectives:

    • Create a continuous delivery pipeline using Cloud Build and start it manually or automatically with a code change.
    • Implement a canary deployment that hosts two versions of your application in production for release testing.

    Activities:

    • 1 lab

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    Course ID: 19195

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    Frequently Asked Questions

    This course is designed for intermediate learners with some understanding of cloud computing concepts. We delve deeper than basic Kubernetes deployment, focusing on architecture, security, and integration with various Google Cloud services.

    You'll gain a thorough understanding of container technology, including its benefits, limitations, and how it revolutionizes application development. We'll explore different container formats and management tools.

    While familiarity with GCP is helpful, it's not mandatory. We'll provide a good understanding of the relevant GCP services used in conjunction with GKE, like Cloud Storage and Cloud SQL.

    The course features interactive labs throughout, letting you practice with GKE cluster creation, pod networking, security policies, and application deployments. You'll gain practical experience applying the concepts learned.

    DevOps engineers, cloud architects, software developers, and anyone interested in containerized applications will find this course valuable. It builds expertise in managing and designing GKE-based solutions.

    The course content aligns with Google Cloud Certifications related to Kubernetes and GKE. While it's not a guaranteed exam pass, it provides a strong foundation for further study and certification preparation.

    GKE is a leading container orchestration platform in high demand. Mastering its architecture and management skills can significantly enhance your career prospects and marketability in the cloud-native space. Configure load balancers to distribute traffic across your VM instances. Set up autoscaling rules to adjust the number of VMs automatically based on demand. Ensure high availability and responsiveness even during sudden traffic spikes.

    Absolutely! You'll learn to deploy and manage Google Cloud resources using infrastructure as code tools like Terraform, automating repetitive tasks and streamlining your workflow.

    Enquire Now