This blog post discusses setting up a chatbot UI using Streamlit alongside a deployed language model inference service in Azure Kubernetes. It details the process of testing the inference service with curl commands, implementing a Streamlit app, and configuring ingress rules for external access, highlighting Streamlit's user-friendly capabilities for chatbot development.
The Kubernetes AI Toolchain Operator (KAITO) automates AI/ML model processes in Kubernetes, enhancing control and security. This setup involves creating an AKS cluster, installing KAITO, and configuring an Nginx ingress for public model access, showcasing actionable AI solutions.
Now that I have fine-tuned a model in Part 2, next is to deploy the fine tuned model into a new Kaito workspace. This blog post is part of a series.Part 1: Intro and overview of the KAITO fine-tuning workspace yamlPart 2: Executing the Training Kubernetes Training JobPart 3: Deploying the Fine-Tuned ModelPart 4: Evaluating …
I will continue from the Part 1 to execute the deployment of the fine-tuning workspace job. This blog post is part of a series.Part 1: Intro and overview of the KAITO fine-tuning workspace yamlPart 2: Executing the Training Kubernetes Training JobPart 3: Deploying the Fine-Tuned ModelPart 4: Evaluating the Fine-Tuned Model Let' start the fine …
Continue reading Deep Dive Into Fine-Tuning An LM Using KAITO on AKS – Part 2: Execution
KAITO simplifies the deployment of large language models (LLMs) in Azure Kubernetes Service (AKS) environments with preset GPU configurations. This tool automates the setup process, including node provisioning and identity management, essential for data experiments while ensuring security compliance. It enhances efficiency, allowing engineers to focus on AI/ML model experimentation. #azure #kubernetes #AI #genAI #mvpbuzz
I did an experiment of running a load test against 4 applications and while executing a Azure Kubernetes Cluster Upgrade to see the affects and any downtime. The applications hosted in my AKS cluster are AKS Helloworld - super simple application Voting App - simple application with Redis backend Bookinfo Istio demo - microservices architecture …
If you ever encounter the following error, I'll show you one way that helped me resolve my AKS cluster. The cluster is in a failed state. If you didn't do an operation, AKS may resolve the provisioning status automatically if your cluster applications continue to run. To further troubleshoot, you can refer to https://github.com/MicrosoftDocs/SupportArticles-docs/blob/main/support/azure/azure-kubernetes/cluster-node-virtual-machine-failed-state.md For …
I like to share in hoping to have helped the small minority that couldn't get kubelogin setup properly with the struggles that I have been having. My desktop environment WSL on Windows 10 Ubuntu 20.04 Here's my error ~/linux-scripts $ kubelogin convert-kubeconfigerror: unknown command "convert-kubeconfig" for "kubelogin" I should have paid attention that the kubelogin …
The process of upgrading an AKS cluster involves careful consideration due to its complexity, especially in production environments. Manual control plane and node pool upgrades are essential, requiring meticulous monitoring and careful planning. Consider the extensive documentation for detailed guidance.
This blog post is a continuation of Deploying Azure Kubernetes Service Demo Store App with Azure Open AI – Part 1. It dives into the Python code that calls the Azure Open AI Service and highlights the use of Semantic Kernel. The AKS Demo Store uses the AI functionality to generate product descriptions. The article emphasizes the benefits of using Azure Kubernetes Service (AKS) to support AI Ops platform.
Roy Kim on Azure and AI 