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Leveraging AI for Kubernetes Troubleshooting via K8sGPT
Nowadays, there is a lot of excitement around AI and its new applications. For instance, in April/May 2024, there were at least four AI conventions in Seoul with thousands of attendees. So, what about Kubernetes? Can AI help us manage Kubernetes? The answer is yes. In this article, I will introduce K8sGPT.
What does GPT stand for?
GPT stands for Generative Pre-trained Transformer. It’s a deep learning architecture that relies on a neural network pre-trained on a massive dataset of unlabeled text from various sources such as books, articles, websites, and other digital texts. This enables it to generate coherent and contextually relevant text. The first GPT was introduced in 2018 by OpenAI.
GPT models are based on the transformer architecture, developed by Google, which uses a multi-head attention mechanism. Text is converted into numerical representations called tokens, often how the usage of these models is priced when provided as a service.
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Each token is transformed into a vector via a lookup from a word embedding table based on a pre-trained matrix where each row corresponds to a token…