k8sGPT : Kubernetes diagnosis with ChatGPT and Azure OpenAI

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🌐 Dive into the complexities of diagnosing Kubernetes cluster workloads and discover the game-changing solutions that have emerged in the tech landscape! In this video, we explore the challenges faced by Developers, DevOps and SRE teams when troubleshooting issues within Kubernetes environments.

🤯 Kubernetes, with its vast ecosystem, often presents hurdles in diagnosing and resolving cluster workloads efficiently. The emergence of ChatGPT and GenAI has added a powerful ally to the arsenal of developers and system administrators, offering intelligent insights and solutions to the intricate problems faced in managing containerized applications.

🚀 Introducing K8sGPT – a groundbreaking tool designed to leverage the capabilities of ChatGPT for streamlining and automating the resolution of Kubernetes issues. This video delves into the features and functionalities of K8sGPT, showcasing how it harnesses the intelligence of ChatGPT, powered by the robust Azure OpenAI backend, to provide real-time assistance in diagnosing and resolving Kubernetes challenges.

🔍 Join us on this exploration of cutting-edge technologies, as we unravel the difficulties in Kubernetes cluster workloads and witness the transformative potential of K8sGPT in action. Stay ahead in the world of DevOps and Kubernetes management – watch now!

#K8sGPT #AzureOpenAI #kubernetes #DevOps #ChatGPT #TechInnovation #SRE #DevRel #Azure #azurekubernetesservice #kubernetes 🚀

▬▬▬▬▬▬ ⏱ Chapters⏱ ▬▬▬▬▬▬
00:00 – Introduction to Kubernetes
01:00 – Introduction to k8sGPT
02:45 – k8sGPT overview
05:35 – Prerequisites for k8sGPT
07:10 – install k8sGPT
08:40 – k8sGPT supported commands
09:25 – k8sGPT Authentication provider
10:30 – Setup Azure OpenAI access
12:40 – Create Azure OpenAI service
17:30 – Deploy LLM model using Azure AI Studio
18:40 – Azure OpenAI models and quotas
19:25 – Create a Deployment using Azure Open AI studio
21:55 – Add Azure OpenAI as backend for k8sGPT
26:40 – Set default provider
27:05 – Analyze Kubernetes cluster using k8sGPT
28:15 – Analyze application specific issues using filters
31:00 – Fix typo and rerun the k8sGPT analysis
33:50 – Anonymize flag for masking sensitive data
34:20 – k8sGPT Filters
35:15 – Filter results for pods using k8sGPT filter
36:15 – k8sGPT filter namespace
37:40 – Multiple language support
39:30 – Fix the deployment and rerun k8sGPT analysis
41:30 – Summary

▬▬▬▬▬▬ 🔗 Additional Info 🔗 ▬▬▬▬▬▬
– 🔗 k8sgpt homepage – https://k8sgpt.ai/
– 🔗 k8sgpt docs – https://docs.k8sgpt.ai/
– 🔗 Microsoft docs for the process to request Azure OpenAI service – https://learn.microsoft.com/en-us/legal/cognitive-services/openai/limited-access
– 🔗 Azure OpenAI service request form – https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUNTZBNzRKNlVQSFhZMU9aV09EVzYxWFdORCQlQCN0PWcu
– 🔗 Azure AI studio – https://oai.azure.com/portal/

▬▬▬▬▬▬ 👋 Contact me 👋 ▬▬▬▬▬▬
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