Architecting with Google Kubernetes Engine
- Created By raju2006
- Last Updated December 29th, 2023
- Overview
- Prerequisite
- Audience
- Audience
- Curriculum
Description:
Master the deployment and management of containerized applications on Google Kubernetes Engine (GKE) and leverage the full suite of Google Cloud Platform services with this immersive three-day instructor-led course. Engage with dynamic presentations, live demos, and interactive hands-on labs to discover the intricacies of deploying solution components, including pods, containers, deployments, services, networks, and application services. This comprehensive course also extends to deploying practical solutions, encompassing security, access management, resource optimization, and performance monitoring
Course Code/Duration:
BDT109 / 3 Days
Learning Objectives:
- Gain an understanding of software containers and their functioning.
- Explore the architecture of Kubernetes.
- Familiarize with the architecture of Google Cloud Platform.
- Learn how pod networking operates within Kubernetes Engine.
- Create and efficiently manage Kubernetes Engine clusters using GCP Console and gcloud/kubectl commands.
- Deploy, roll back, and expose jobs within Kubernetes.
- Manage access control through Kubernetes RBAC and Google Cloud IAM.
- Implement pod security policies and network policies.
- Leverage Secrets and ConfigMaps for isolating security credentials and configuration artifacts.
- Understand Google Cloud Platform's managed storage services for various data needs.
- Monitor applications running within Kubernetes Engine for performance and reliability.
- To get the most out of this course, participants should have: Completed Google Cloud Platform Fundamentals: Core Infrastructure or have equivalent experience Basic proficiency with command-line tools and Linux operating system environments.
- This class is intended for the following participants: Cloud architects, administrators, and SysOps/DevOps personnel Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform.
- This class is intended for the following participants: Cloud architects, administrators, and SysOps/DevOps personnel Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform.
Course Outline:
The course includes presentations, demonstrations, and hands-on labs.
Module 1: Introduction to Google Cloud Platform
- Use the Google Cloud Platform Console
- Use Cloud Shell
- Define cloud computing
- Identify GCPs compute services
- Understand regions and zones
- Understand the cloud resource hierarchy
- Administer your GCP resources
Module 2: Containers and Kubernetes in GCP
- 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 GCP compute platforms
Module 3: Kubernetes Architecture
- Understand the architecture of Kubernetes: pods, namespaces
- Understand the control-plane components of Kubernetes
- Create container images using Google Cloud Build
- Store container images in Google Container Registry
- Create a Kubernetes Engine cluster
Module 4: Kubernetes Operations
- Work with the kubectl command
- Inspect the cluster and Pods
- View a Pods console output
- Sign in to a Pod interactively
Module 5: Deployments, Jobs, and Scaling
- 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
Module 6: GKE Networking
- 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
Module 7: Persistent Data and Storage
- 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
Module 8: Access Control and Security in Kubernetes and Kubernetes Engine
- Understand Kubernetes authentication and authorization
- Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces
- Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources
- Define Kubernetes pod security policies
- Understand the structure of GCP IAM
- Define IAM roles and policies for Kubernetes Engine cluster administration
Module 9: Logging and Monitoring
- Use Stackdriver to monitor and manage availability and performance
- Locate and inspect Kubernetes logs
- Create probes for wellness checks on live applications
Module 10: Using GCP Managed Storage Services from Kubernetes Applications
- Understand pros and cons for using a managed storage service versus self managed containerized storage
- Enable applications running in GKE to access GCP storage services
- Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and Bigquery from within a Kubernetes application
Training material provided:
Yes (Digital format)
The curriculum is empty
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