In "Architecting with Google Kubernetes Engine: Workloads," you'll embark on a comprehensive journey into cloud-native application development. Throughout the learning experience, you'll explore Kubernetes operations, deployment management, GKE networking, and persistent storage.

Architecting with Google Kubernetes Engine: Workloads

Architecting with Google Kubernetes Engine: Workloads
This course is part of Architecting with Google Kubernetes Engine Specialization

Instructor: Google Cloud Training
Access provided by SmartStream
33,844 already enrolled
1,270 reviews
What you'll learn
Create and manage workloads in Google Kubernetes Engine.
Explain how pod networking works in Google Kubernetes Engine.
Define and work with different Kubernetes storage abstractions.
Skills you'll gain
Tools you'll learn
Details to know

Add to your LinkedIn profile
3 assignments
See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate

There are 5 modules in this course
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor

Offered by
Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.
Learner reviews
- 5 stars
79.84%
- 4 stars
15.90%
- 3 stars
2.83%
- 2 stars
0.62%
- 1 star
0.78%
Showing 3 of 1270
Reviewed on Jul 21, 2019
This course gave me hands-on learning experience of Google Kubernetes Engine: Workloads. The classes and lab work were impactful.
Reviewed on Apr 20, 2022
Lots of good fundamentals in here especially regarding networking and config and stateful workloads.
Reviewed on Apr 24, 2020
The course coverage is very good. The lab for config map and secrets needs to be improved in terms of contents description. For the same lab, the duration needs to be increased by 30 min.
Explore more from Computer Science

Google Cloud


