Enhancement of Technical Outcomes

[wzshiming]

What would you like to be added?

https://mentorship.lfx.linuxfoundation.org/project/ef8e7637-2eb6-4672-8f6c-c9f9f0677da0

A section of the KWOK website detailing these technical outcomes.

We have identified the following areas of focus:

• Chaos Testing
• Performance
• Simulation
• Scalability

Here are some of the traces I found involving the use of kwok:

Some of the talks that mention kwok are:

• https://sched.co/1R2pf
• https://sched.co/1R2ub
• https://sched.co/1aOpx

Some of the docs that use kwok are:

• https://developer.ibm.com/tutorials/awb-using-kwok-to-simulate-a-large-kubernetes-openshift-cluster/
• https://headlamp.dev/docs/latest/development/testing/
• https://yunikorn.apache.org/docs/performance/evaluate_perf_function_with_kwok
• https://kyverno.io/docs/installation/scaling/#reports-controller
• https://karmada.io/docs/developers/performance-test-setup-for-karmada

Some of the projects that use kwok are:

• https://github.com/kubernetes-sigs/kube-scheduler-simulator (pod, scheduler, simulation)
• https://github.com/kubernetes-sigs/e2e-framework (testing)
• https://github.com/kubernetes-sigs/karpenter (node, scalability, performance)
• https://github.com/kubernetes/autoscaler (node, scalability, performance)
• https://github.com/capi-samples/cluster-api-provider-kwok (node, scalability)
• https://github.com/kyverno/kyverno (apiserver webhook, simulation, performance)
• https://github.com/kubevirt/kubevirt & https://github.com/kwok-ci/kubevirt-demo (stage api, scalability, performance)
• https://github.com/NVIDIA/knavigator (stage api, chaos)
• https://github.com/apache/yunikorn-k8shim (pod, scheduler, performance)
• https://github.com/Azure/azure-container-networking (simulation, performance)
• https://github.com/project-codeflare/multi-cluster-app-dispatcher (pod, scheduler, performance)
• https://github.com/openshift-psap/topsail (pod, scheduler, performance)
• https://github.com/kubescape/kwok-bench (pod, scheduler, performance)
• https://github.com/acrlabs/simkube (pod, node, scheduler, performance, simulation)
• https://github.com/run-ai/fake-gpu-operator (simulation)
• https://github.com/kubeovn/kube-ovn (simulation)
• https://github.com/nuodb/terraform-provider-nuodbaas (simulation)
• https://github.com/vladimirvivien/ktop (ui, simulation)
• https://github.com/headlamp-k8s/headlamp (ui, simulation, performance)
• https://github.com/turbonomic/kubeturbo (multi-cluster, simulation)
• https://github.com/kubewharf/kubeadmiral (multi-cluster, simulation)
• https://github.com/clusterpedia-io/clusterpedia (multi-cluster, simulation)

we shouldn’t mention the description of the specific project. If possible, focus on what kwok can be used for, at most mentioning at the end of the content that the project is a practice of it.

Why is this needed?

On the KWOK homepage (https://kwok.sigs.k8s.io/), we aim to document the technical outcomes of using KWOK. These outcomes represent the aggregation of some of KWOK's features to achieve a high-level technical goal.

ref cncf/mentoring#1227

[Manoramsharma]

Hello @wzshiming,

I am thrilled at the prospect of contributing to the enhancement of KWOK's website, specifically in detailing the technical outcomes as outlined in issue #1063.

I have a recent experience with the Kyverno Chainsaw project, where I substantially improved its documentation to better showcase its advanced features. Initially, the quick start guide did not fully represent the capabilities of Chainsaw. To address this, I immersed myself in understanding the tool's innovative features through extensive research, including a series of insightful blog posts:

• Kyverno Chainsaw 0.1.4 - Awesome New Features
• Exploring the Power of Assertion Trees in Kyverno Chainsaw
• Kyverno Chainsaw: The Ultimate End-to-End Testing Tool

These articles helped me gain a deep understanding of Chainsaw's unique features like assertion trees, resource templating, and resource diff in assertion failures. Leveraging this knowledge, I adopted a narrative approach in the documentation to contextualize these features through real-use case examples. My contributions were compiled into a pull request, which has since been merged. The enhancements are now visible in the latest release of the Kyverno Chainsaw documentation, specifically in the Chainsaw Characteristics section.

For KWOK, I envision a similar approach. I plan to begin with a comprehensive review of KWOK's existing resources and identify key features through further research, including available documentation, blog posts, and community insights. My goal is to outline how these features collectively achieve high-level technical outcomes in areas like Chaos Testing, Performance, Simulation, and Scalability, presenting them in a clear, structured, and engaging manner.

I am keen to bring my documentation skills and enthusiasm for Kubernetes technologies to the KWOK project. Please let me know the best way to start contributing to this effort.

Best regards,
Manoram

[wzshiming]

Thank you, but this program is pending approval, if this is approved, Monday 13th May to start mentee applications.

https://github.com/cncf/mentoring/blob/main/programs/lfx-mentorship/2024/02-Jun-Aug/README.md

[Ayush9026]

@wzshiming sir i am also interested in mentorship #1063

[wzshiming]

The application is already open
https://mentorship.lfx.linuxfoundation.org/project/ef8e7637-2eb6-4672-8f6c-c9f9f0677da0

[lavishpal]

Hi @wzshiming , I am interested in working on this issue, I have been doing some research around the same, I have some questions,
Are there any guides or documents I should read?
What are you expectation on technical outcome pages ?

[pandeyshubham03]

Hi @wzshiming, I'm interested in working on this issue for the LFX summer term.

[wzshiming]

The application is already open, If you want to be a mentee of LFX, apply here
https://mentorship.lfx.linuxfoundation.org/project/ef8e7637-2eb6-4672-8f6c-c9f9f0677da0