Architecting with Google Kubernetes Engine GKE

Unlock your potential with our in-depth "Architecting with Google Kubernetes Engine" training course. Learn to deploy, manage, and scale containerized applications on GKE effectively. This comprehensive program covers core Kubernetes concepts, best practices, and real-world scenarios, empowering you with the skills to excel in today's cloud-native world.

What You'll Learn:

• Master Core Kubernetes Concepts: Understand Kubernetes architecture, components, and key concepts like pods, deployments, services, and namespaces.
• Deploy and Manage GKE Clusters: Learn to create, configure, and manage GKE clusters efficiently, including scaling, upgrades, and maintenance.
• Orchestrate Containerized Applications: Deploy, scale, and manage containerized applications with Kubernetes, including rolling updates, rollbacks, and blue/green deployments.
• Secure Your Kubernetes Environments: Implement robust security measures, including IAM, RBAC, network policies, and security best practices.
• Integrate with Google Cloud Services: Leverage the power of Google Cloud services like Cloud Storage, Cloud SQL, and Cloud Spanner within your Kubernetes deployments.
• Troubleshoot and Optimize: Learn to troubleshoot common Kubernetes issues and optimize cluster performance for maximum efficiency.
• Hands-on Labs and Real-World Examples: Gain practical experience through hands-on labs and real-world examples to solidify your understanding and build confidence.

Who Should Attend:

• DevOps Engineers: Enhance your Kubernetes skills and streamline your container orchestration workflows.
• Cloud Engineers: Gain expertise in managing and scaling containerized applications on Google Cloud.
• System Administrators: Learn to effectively manage and maintain Kubernetes clusters in a production environment.
• Software Developers: Understand how to containerize applications and deploy them effectively on Kubernetes.
• Anyone interested in cloud-native technologies and container orchestration.**

Prerequisites:

• Basic understanding of cloud computing concepts
• Familiarity with Linux/Unix operating systems (recommended)

Benefits of Attending:

• Gain in-demand skills in Kubernetes and Google Cloud.
• Enhance your career prospects and increase your earning potential.
• Improve your ability to design, deploy, and manage scalable and reliable cloud-native applications.
• Gain hands-on experience with real-world scenarios.
• Learn from expert instructors with in-depth industry knowledge.
• Receive valuable training materials and resources.

Course Outline:

Module 1: Introduction to Google Cloud Platform

• Introduction to GCP
• Using the Google Cloud Console
• Working with Cloud Shell
• Creating and managing GCP projects
• Understanding GCP compute platforms
• Cloud Resource Manager, Quotas, Billing

Module 2: Launching Workloads in Kubernetes Engine

• Kubernetes Architecture: Pods, Namespaces, Deployments
• Key Kubernetes Components: Control Plane, Nodes, Services
• Building Docker Containers with Google Container Builder
• Storing container images in Google Container Registry (GCR)
• Creating and managing Kubernetes Engine clusters
• Deploying applications using Helm charts

Module 3: Debugging, Monitoring, and Logging

• Introspecting Kubernetes containers
• Viewing pod logs
• Troubleshooting common Kubernetes problems
• Using Stackdriver Kubernetes Monitoring
• Using Prometheus monitoring with Stackdriver

Module 4: Scheduling and Autoscaling Workloads

• Applying labels
• Creating and managing Deployments
• Performing rolling upgrades and rollbacks of Deployments
• Defining Services: NodePort, LoadBalancer, Ingress
• Running cron jobs
• Controlling pod execution with taints and tolerations
• Configuring Kubernetes Engine clusters for autoscaling

Module 5: Kubernetes and Google Cloud VPC Networking

• Kubernetes Networking Model: Pods, Services, and Networking
• Comparing Kubernetes, Docker, and Compute Engine networking
• Working with VPC networks and subnets
• Understanding load balancer types
• Using Kubernetes DNS

Module 6: Persistent Data and Storage

• Using Secrets to store sensitive information
• Using ConfigMaps to store configuration data
• Managing Secrets and ConfigMaps: Updates, Rollbacks
• Configuring Persistent Storage Volumes for Kubernetes Pods
• Using StatefulSets to manage stateful applications

Module 7: Access Control and Security

• Kubernetes Authentication and Authorization
• Defining Kubernetes RBAC: Roles, RoleBindings, ClusterRoles, ClusterRoleBindings
• Defining Kubernetes Pod Security Policies
• Defining Kubernetes Network Policies
• GCP IAM: Roles, Permissions, and Policies
• IAM for Kubernetes Engine cluster administration
• Multi-tenancy considerations: Single vs. Multiple Clusters

Module 8: Integrating with Google Cloud Services

• Using Cloud Storage from within Kubernetes applications
• Using Cloud SQL and Cloud Spanner from within Kubernetes applications
• Using Cloud Datastore from within Kubernetes applications
• Using Cloud Bigtable from within Kubernetes applications