Architecting with Google Kubernetes Engine

PT25142
Training Summary
Learn how to deploy practical solutions including security and access management, resource management, and resource monitoring. This three-day instructor-led class introduces participants to deploying and managing containerized applications on Google Kubernetes Engine (GKE) and the other services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring.
Prerequisites
To get the most out of this course, participants should have: Completed Google Cloud Platform Fundamentals: Core Infrastructure or have equivalent experience and have basic proficiency with command-line tools and Linux operating system environments.
Duration
3 Days/Lecture & Lab
Audience
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 Topics
  • Understand how software containers work Understand the architecture of Kubernetes
  • Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine
  • Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands ::Launch, roll back and expose jobs in Kubernetes
  • Manage access control using Kubernetes RBAC and Google Cloud IAM
  • Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts
  • Understand GCP choices for managed storage services
  • Monitor applications running in Kubernetes Engine

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