Deploy and fine-tune LLM models on Kubernetes using KAITO
Aug 7, 2024
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Sachi Desai, a Product Manager specializing in AI technologies, and Paul Yu, a Senior Cloud Advocate at Microsoft, dive into the KAITO project for deploying open source LLM models on Kubernetes. They discuss how KAITO simplifies running AI applications alongside LLM models and enables users to bring and fine-tune their own models. The conversation highlights innovative techniques like LoRa and Q-LoRa for efficient model training. Additionally, they emphasize community engagement's role in enhancing AI model deployment and future capabilities.
Kaito simplifies the deployment and management of large language models on Kubernetes, effectively addressing AI workload infrastructure challenges.
The fine-tuning capabilities of Kaito enable organizations to optimize AI model performance with new datasets while ensuring cost efficiency.
Deep dives
Three Year Milestone of the Podcast
The hosts reflect on the journey of the podcast, celebrating its three-year anniversary and over 75 episodes produced. They express gratitude towards listeners for their support and highlight the growth of the audience through word of mouth. The hosts acknowledge the opportunity to engage with industry experts and attend significant events like KubeCon and Red Hat Summit, where they meet listeners in person. Their commitment to continue the podcast remains strong, emphasizing the importance of sharing knowledge on cloud-native technology.
Introduction of Azure Container Storage
Microsoft's Azure Container Storage (ACS) is now generally available, offering a software-defined and cloud-native storage solution derived from OpenEBS. This solution supports underlying devices, including Azure disks and ephemeral disks, allowing for flexible storage options. Notable features of ACS include storage pool expansion, node replication, and customer-managed encryption key support, enhancing storage flexibility and security. The hosts provide resources in the show notes for listeners to understand ACS's journey and its features.
Overview of the Kaito Project
The Kaito project, short for Kubernetes AI toolchain operator, addresses infrastructure provisioning challenges for AI workloads within AKS. It simplifies deploying large language models and managing the underlying infrastructure transparently for users. With Kaito, organizations can efficiently deploy AI models, making it easier to address data privacy and latency concerns associated with using external AI services. The project aims to automate the cumbersome steps involved in onboarding and deploying AI models in Kubernetes clusters.
Fine Tuning and Model Deployment with Kaito
Kaito enables fine-tuning of AI models, enhancing their performance with new datasets without the need for starting from scratch. Users can choose parameter-efficient fine-tuning techniques to optimize resource usage, which is critical for effective cost management. The process includes downloading datasets, training model adaptations, and storing these adaptations as container images for further use in inferencing jobs. This streamlined approach significantly reduces the time needed to prepare models for inference, showcasing Kaito's potential in optimizing AI workflows.
In this episode of the Kubernetes Bytes podcast, Bhavin sits down with Sachi Desai, Product Manager and Paul Yu, Sr. Cloud Advocate at Microsoft to talk about the open source KAITO project. KAITO is the Kubernetes AI Toolchain Operator that enables AKS users to deploy open source LLM models on their Kubernetes clusters. They discuss how KAITO helps with running AI-enabled applications alongside the LLM models, how it helps users bring their own LLM models and run them as containers, and how KAITO helps them fine-tune open source LLMs on their Kubernetes clusters.
Check out our website at https://kubernetesbytes.com/
Jumpstart AI Workflows With Kubernetes AI Toolchain Operator - The New Stack - https://thenewstack.io/jumpstart-ai-workflows-with-kubernetes-ai-toolchain-operator
https://paulyu.dev/article/soaring-with-kaito/
Concepts - Fine-tuning language models for AI and machine learning workflows - Azure Kubernetes Service | Microsoft Learn - https://learn.microsoft.com/en-us/azure/aks/concepts-fine-tune-language-models
Keep up to date on the most recent announcements by following some of the KAITO engineers on LinkedIn: