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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. This lab demonstrates how optimization in your cluster's workloads can lead to an overall optimization of your resources and costs. It walks through a few different workload optimization strategies such as container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets.
Register for this course and see more details by visiting:
OpenCourser.com/course/sggj1q/gke
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What's inside
Syllabus
GKE Workload Optimization
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers techniques used to reduce the financial and resource burden of Kubernetes cluster workloads
Suitable for those with some knowledge of GKE cluster management and workload optimization concepts
Provides hands-on experience through self-paced labs in the Google Cloud console
Taught by Google Cloud Training, which is recognized for its expertise in cloud computing
Save this course
Save GKE Workload Optimization to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in GKE Workload Optimization with these
activities:
Prepare for workload optimization
Show steps
Review key workload optimization concepts to better prepare for the course and enhance understanding.
Show steps
-
Read documentation on workload optimization in Kubernetes
-
Set up a Kubernetes cluster for testing
Explore Google Cloud best practices for workload optimization
Show steps
Gain insights from Google Cloud experts by following guided tutorials on workload optimization best practices.
Show steps
-
Access Google Cloud documentation and tutorials
-
Follow step-by-step instructions on optimizing workloads
Practice container-native load balancing
Show steps
Reinforce understanding by practicing container-native load balancing techniques in Kubernetes.
Show steps
-
Set up a cluster with multiple nodes
-
Create a load-balanced service
-
Configure health checks and load balancing policies
Three other activities
Expand to see all activities and additional details
Show all six activities
Connect with experts in workload optimization
Show steps
Gain personalized guidance and insights by connecting with experts who specialize in workload optimization, allowing for deeper exploration and practical advice.
Browse courses on
Mentorship
Show steps
-
Identify potential mentors
-
Reach out to mentors and introduce yourself
-
Set up regular meetings or communication channels
Design and implement workload optimization strategies
Show steps
Apply workload optimization strategies in a real-world project to solidify learning and foster practical implementation skills.
Show steps
-
Identify areas for workload optimization
-
Research and select appropriate optimization techniques
-
Implement and test the optimization strategies
-
Monitor and evaluate the results
Contribute to open-source projects related to workload optimization
Show steps
Advance your knowledge and contribute to the community by participating in open-source initiatives related to workload optimization, gaining valuable hands-on experience and insights from real-world projects.
Browse courses on
Open Source
Show steps
-
Identify open-source projects in the workload optimization domain
-
Contribute to issues or feature requests
-
Collaborate with other contributors
Prepare for workload optimization
Show steps
Review key workload optimization concepts to better prepare for the course and enhance understanding.
Show steps
Show steps
Show steps
- Read documentation on workload optimization in Kubernetes
- Set up a Kubernetes cluster for testing
Explore Google Cloud best practices for workload optimization
Show steps
Gain insights from Google Cloud experts by following guided tutorials on workload optimization best practices.
Show steps
Show steps
Show steps
- Access Google Cloud documentation and tutorials
- Follow step-by-step instructions on optimizing workloads
Practice container-native load balancing
Show steps
Reinforce understanding by practicing container-native load balancing techniques in Kubernetes.
Show steps
Show steps
Show steps
- Set up a cluster with multiple nodes
- Create a load-balanced service
- Configure health checks and load balancing policies
Three other activities
Expand to see all activities and additional details
Show all six activities
Connect with experts in workload optimization
Show steps
Gain personalized guidance and insights by connecting with experts who specialize in workload optimization, allowing for deeper exploration and practical advice.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Identify potential mentors
- Reach out to mentors and introduce yourself
- Set up regular meetings or communication channels
Design and implement workload optimization strategies
Show steps
Apply workload optimization strategies in a real-world project to solidify learning and foster practical implementation skills.
Show steps
Show steps
Show steps
- Identify areas for workload optimization
- Research and select appropriate optimization techniques
- Implement and test the optimization strategies
- Monitor and evaluate the results
Contribute to open-source projects related to workload optimization
Show steps
Advance your knowledge and contribute to the community by participating in open-source initiatives related to workload optimization, gaining valuable hands-on experience and insights from real-world projects.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify open-source projects in the workload optimization domain
- Contribute to issues or feature requests
- Collaborate with other contributors
Career center
Learners who complete GKE Workload Optimization will develop knowledge and skills
that may be useful to these careers:
Kubernetes Administrator
Kubernetes Administrator
Kubernetes Administrators are responsible for managing and maintaining Kubernetes clusters. The topics covered in this course are the foundation for building an effective Kubernetes cluster. Implementing container-native load balancing, using readiness and liveness probes, and setting up disruption budgets are all essential to administrating an effective Kubernetes cluster. This course would be very helpful for someone looking to enter this career, or an experienced administrator looking to work more effectively.
Cloud Architect
Cloud Architect
Cloud Architects design, build, and manage cloud computing systems. This course will help students develop a foundation in optimizing workloads and resource utilization at a cloud scale. By learning to implement container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets, students of this course will be able to create cloud systems that maximize efficiency and minimize operational costs.
Cloud Developer
Cloud Developer
Cloud Developers design, build, and maintain cloud-based applications. This course will help students develop a foundation in workload optimization and resource utilization in cloud-native environments. It will provide a foundation in implementing container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets to monitor the health of scalable distributed systems.
Cloud Security Engineer
Cloud Security Engineer
Cloud Security Engineers design and implement security measures to protect cloud computing systems. This course will help students develop a foundation in securing and optimizing workloads at a cloud scale. By learning to implement container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets using Kubernetes-native tools, students of this course will be able to create cloud systems that are more secure and cost-effective.
DevOps Engineer
DevOps Engineer
DevOps Engineers are responsible for bridging the gap between development and operations by finding and exploiting synergies between development and operational teams. The ability to optimize resources and workloads is key to working as a DevOps Engineer, even across cloud-native environments. This course will help students build a foundation for working as a DevOps Engineer by providing a foundation in concepts like workload balancing, load testing, and optimizing resource utilization.
Cloud Consultant
Cloud Consultant
Cloud Consultants help organizations design and implement cloud computing solutions. This course will help students build a foundation in workload optimization and resource utilization in cloud-native environments. By learning to implement container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets using Kubernetes-native tools, students of this course will be able to design and implement more effective cloud solutions.
Software Engineer
Software Engineer
Software Engineers design, build, and maintain software applications. While the topics covered in this course are not typically the primary focus of a Software Engineer, they are all helpful for developing software that is reliable, scalable, and cost-effective. By understanding how to optimize workload balancing, use readiness and liveness probes, and set up disruption budgets, Software Engineers can build higher quality applications.
Site Reliability Engineer
Site Reliability Engineer
Site Reliability Engineers help companies optimize their websites and applications by leveraging automation and optimizing resource utilization. Optimizing across containers, readiness and liveness probes, disruption budgets, and load balancing would all be an essential part of delivering a scalable and effective application. While this course can help provide a foundation for someone looking to get into SRE, it may also be a useful course for more experienced engineers in the field.
Security Engineer
Security Engineer
Security Engineers design and implement security measures to protect applications from vulnerabilities. While the topics covered in this course are not typically the primary focus of a Security Engineer, understanding how to use readiness and liveness probes and managing disruption budgets is essential for designing highly available and resilient cloud systems.
Data Engineer
Data Engineer
Data Engineers design and build systems for managing and analyzing data. The topics covered in this course are not the primary focus of a Data Engineer, but they are all relevant to managing large datasets in a cloud environment. By understanding how to optimize workload balancing, use readiness and liveness probes, and set up disruption budgets using Kubernetes-native tools, Data Engineers can build more performant and cost-effective data systems.
For more career information including salaries, visit:
OpenCourser.com/course/sggj1q/gke
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
GKE Workload Optimization.
Practical guide that covers best practices for deploying and managing Kubernetes in production environments. It dives deep into cluster architecture, security, networking, monitoring, and troubleshooting. Provides a solid foundation for understanding the concepts of Kubernetes workload optimization.
Save
Focuses on proven design patterns and best practices for building and managing cloud-native applications on Kubernetes. It offers practical guidance on resource management, scalability, reliability, and security. Complements the course's coverage of workload optimization strategies.
Provides a comprehensive overview of DevOps practices specific to cloud-native environments. It covers topics like CI/CD, infrastructure automation, and monitoring, which are essential for optimizing workload performance in Kubernetes.
Save
Comprehensive guide to Kubernetes architecture, concepts, and best practices. It serves as a valuable reference for understanding the underlying principles of workload optimization in Kubernetes.
Provides a hands-on approach to learning Kubernetes. It covers core concepts, cluster management, application deployment, and advanced topics like workload management and autoscaling. Reinforces the practical aspects of workload optimization covered in the course.
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Introduces the concept of Kubernetes Operators and explains how they can be used to automate the management of complex applications and workloads. Provides valuable knowledge for understanding advanced workload optimization techniques.
Foundational guide to Kubernetes concepts and architecture. It provides a comprehensive overview of the platform and serves as a good starting point for understanding workload optimization principles.
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Focuses on practical aspects of running Kubernetes in production environments. It covers topics like cluster management, monitoring, security, and troubleshooting. Complements the course's coverage of workload optimization strategies.
Provides an architectural perspective on building and deploying cloud-native applications. It covers topics like microservices, containers, and Kubernetes. Offers a higher-level view of workload optimization in a cloud-native context.
Save
Classic in the field of DevOps. It provides a comprehensive overview of DevOps principles and practices. Offers valuable insights into the cultural and organizational aspects of workload optimization.
Provides a comprehensive overview of Site Reliability Engineering (SRE) practices at Google. It offers valuable insights into the principles and techniques for ensuring reliability and availability in distributed systems.
Save
Fictional story that illustrates the challenges and benefits of implementing DevOps practices. It provides valuable insights into the cultural and organizational aspects of workload optimization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/sggj1q/gke
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Effort
1 hour 30 minutes
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Covers techniques used to reduce the financial and resource burden of Kubernetes cluster workloads
Suitable for those with some knowledge of GKE cluster management and workload optimization concepts
Provides hands-on experience through self-paced labs in the Google Cloud console
Taught by Google Cloud Training, which is recognized for its expertise in cloud computing
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