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GKE Workload Optimization

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.

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What's inside

Syllabus

GKE Workload Optimization

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

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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

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Review key workload optimization concepts to better prepare for the course and enhance understanding.

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Read documentation on workload optimization in Kubernetes
Set up a Kubernetes cluster for testing

Explore Google Cloud best practices for workload optimization

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Gain insights from Google Cloud experts by following guided tutorials on workload optimization best practices.

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Access Google Cloud documentation and tutorials
Follow step-by-step instructions on optimizing workloads

Practice container-native load balancing

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Reinforce understanding by practicing container-native load balancing techniques in Kubernetes.

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Set up a cluster with multiple nodes
Create a load-balanced service
Configure health checks and load balancing policies

Three other activities

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Connect with experts in workload optimization

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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

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Identify potential mentors
Reach out to mentors and introduce yourself
Set up regular meetings or communication channels

Design and implement workload optimization strategies

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Apply workload optimization strategies in a real-world project to solidify learning and foster practical implementation skills.

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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

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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

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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 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.

See salaries and explore the career path for Kubernetes Administrator

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.

See salaries and explore the career path for Cloud Architect

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.

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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.

See salaries and explore the career path for Cloud Security 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.

See salaries and explore the career path for DevOps Engineer

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.

See salaries and explore the career path for Cloud Consultant

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.

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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.

See salaries and explore the career path for Site Reliability 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.

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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.

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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.

The DevOps 2. 6 Toolkit: Jenkins X

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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.

GKE Workload Optimization

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What's inside

Syllabus

Good to know

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Activities

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