Architecting with Google Kubernetes Engine: Workloads
This course is part of Architecting with Google Kubernetes Engine.
This course provides a comprehensive exploration of cloud-native application development with Google Kubernetes Engine. You'll learn to effectively manage Kubernetes deployments, jobs, and CronJobs to deliver applications and automate tasks. The curriculum covers essential networking concepts including pod communication, service creation, load balancers, and ingress configuration for optimal application exposure. You'll also master Kubernetes storage abstractions to ensure persistent data access, efficient pod management using StatefulSets, and secure configuration management with ConfigMaps and Secrets. This practical course includes hands-on labs to reinforce concepts and prepares you for the next course in the specialization series, Architecting with Google Kubernetes Engine: Production.
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What you'll learn
Create and manage Kubernetes Deployments with various update strategies Configure Jobs and CronJobs for automated task execution Implement cluster scaling techniques for optimal resource utilization Control pod placement using labels, affinity rules, taints, and tolerations Configure Kubernetes Services to expose applications to the network Implement load balancing for external access to applications Define and work with Kubernetes storage abstractions for persistent data
Skills you'll gain
This course includes:
1.6 Hours PreRecorded video
3 assignments
Access on Mobile, Tablet, Desktop
Batch access
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There are 5 modules in this course
This course provides a comprehensive exploration of Google Kubernetes Engine (GKE) workload management. Students learn to manage deployments, jobs, and CronJobs to efficiently deliver applications and automate tasks. The curriculum covers pod networking fundamentals, service configuration, load balancing options, and ingress control for optimal application exposure. Students also master Kubernetes storage abstractions to ensure persistent data access across container lifecycles. The course includes hands-on labs for creating deployments, configuring networking, and implementing persistent storage in GKE environments. With a focus on practical application, participants gain the skills to effectively deploy, manage, and scale containerized applications in production cloud environments.
Workloads Course Introduction
Module 1 · 1 Minutes to complete
Workloads: Deployments and Jobs
Module 2 · 1 Hours to complete
Google Kubernetes Engine Networking
Module 3 · 1 Hours to complete
Persistent Data and Storage
Module 4 · 1 Hours to complete
Workloads Course Summary
Module 5 · 10 Minutes to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Architecting with Google Kubernetes Engine
Instructor
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