kubernetes
76 TopicsAnnouncing HCIBox support for Azure Stack HCI 23H2
Not a day goes by without the Jumpstart team being asked "When is HCIBox 23H2 coming?" You want to get hands-on with Azure Stack HCI 23H2 and the new cloud deployment, lifecycle management capabilities, and out-of-the-box Arc-enabled services. We have heard the demand loud and clear, and the wait is now over!5KViews6likes2CommentsNew hybrid deployment options for AKS clusters from cloud to edge, enabled by Azure Arc
This Ignite, we're announcing new hybrid deployment options for AKS clusters from cloud to edge, enabled by Azure Arc. Read along to find out how managing AKS on-premises is even more easier and cost-effective!14KViews6likes1CommentAzure Arc enabled Kubernetes is now Generally Available!
We are excited to bring Azure Arc enabled Kubernetes to general availability at our Spring Ignite event. Azure Arc enabled Kubernetes enables you to attach any CNCF-conformant Kubernetes cluster to Azure for management. Your clusters can run anywhere, and if they have connectivity to Azure, onboarding is as easy as deploying the Azure Arc cluster agents using the Azure CLI extension.17KViews6likes0CommentsIgnite 2024: AKS enabled by Azure Arc - New Capabilities and Expanded Workload Support
Microsoft Ignite 2024 has been a showcase of innovation across the Azure ecosystem, bringing forward major advancements in AI, cloud-native applications, and hybrid cloud solutions. This year’s event featured key updates, including enhancements to AKS enabled by Azure Arc, which introduced new capabilities and expanded workload support. These updates reinforce the value and versatility that AKS enabled by Azure Arc brings to organizations looking to scale and optimize their operations. With these advancements, AKS Arc continues to support seamless management, increased scalability, and enhanced workload performance across diverse infrastructures. AKS Enabled by Azure Arc AKS enabled by Azure Arc brings the power of Azure’s managed Kubernetes service to any environment, providing consistent management and security across on-premises, edge, and multi-cloud deployments. It encompasses: AKS on Azure Local: A full-featured Kubernetes platform integrated with Azure Local for comprehensive container orchestration in hybrid setups. Notably, AKS on Azure Local has earned recognition as a leader in the 2024 Gartner Magic Quadrant for Distributed Hybrid Infrastructure, underscoring Microsoft's dedication to delivering comprehensive, enterprise-ready solutions for hybrid cloud deployments. AKS Edge Essentials: A lightweight version designed for edge computing, ensuring operational consistency on constrained hardware. AKS on Azure Local Disconnected Operations: It is now available on Azure Local Disconnected Operations. This latest addition to AKS enabled by Azure Arc portfolio is the support for fully disconnected scenario. It allows AKS enabled by Azure Arc to operate in air-gapped, isolated environments without the need for continuous Azure connectivity. It is crucial for organizations that require secure, self-sufficient Kubernetes operations in highly controlled or remote locations. With this support, businesses can maintain robust Kubernetes functionality while meeting stringent compliance and security standards. Key Features and Expanded Workload Support This year's Ignite announcements unveiled a series of public preview and GA features that enhance the capabilities of AKS enabled by Azure Arc. These advancements reflect our commitment to delivering robust, scalable solutions that meet the evolving needs of our customers. Below are the key highlights that showcase the enhanced capabilities of AKS enabled by Azure Arc: Edge Workload Azure IoT Operations - enabled by Azure Arc: Available on AKS Edge Essentials (AKS-EE) and AKS on Azure Local with public preview support. Azure IoT Operations in the management and scaling of IoT solutions. It provides robust support for deploying and overseeing IoT applications within Kubernetes environments, enhancing operational control and scalability. Organizations can leverage this tool to maintain seamless management of distributed IoT workloads, ensuring consistent performance and simplified scaling across diverse deployment scenarios. Azure Container Storage - enabled by Azure Arc: Available on both AKS Edge Essentials (AKS-EE) and AKS on Azure Local, this support enables seamless integration for persistent storage needs in Kubernetes environments. It provides scalable, reliable, and high-performance storage solutions that enhance data management and support stateful applications running in hybrid and edge deployments. This addition ensures that organizations can efficiently manage their containerized workloads with robust storage capabilities. Azure Key Vault Secret Store extension for Kubernetes: Now available as public preview on AKS Edge Essentials and AKS on Azure Local, this extension automatically synchronizes secrets from an Azure Key Vault to an AKS enabled by Azure Arc cluster for offline access, providing essential tools for proactive monitoring and policy enforcement. It offers advanced security and compliance capabilities tailored for robust governance and regulatory adherence, ensuring that organizations can maintain compliance with industry standards and best practices while safeguarding their infrastructure. Azure Monitor Pipeline: The Azure Monitor pipeline is a data ingestion solution designed to provide consistent, centralized data collection for Azure Monitor. Once deployed for AIO on AKS cluster enabled by Azure Arc, it enables at-scale telemetry data collection and routing at the edge. The pipeline can cache data locally, syncing with the cloud when connectivity is restored, and supports segmented networks where direct data transfer to the cloud isn’t possible. Built on OpenTelemetry Collector, the pipeline’s configuration includes data flows, cache properties, and destination rules defined in the DCR to ensure seamless data processing and transmission to the cloud. Arc Workload Identity Federation: Now available as public preview on AKS Edge Essentials and AKS on Azure Local, providing secure federated identity management to enhance security for customer workloads Arc Gateway: Now available as public preview for AKS Edge Essentials and AKS on Azure Local. Arc Gateway support on AKS enabled by Azure Arc enhances secure connectivity across hybrid environments, reducing required firewall rules and improving security for customer deployments. Azure AI Video Indexer - enabled by Azure Arc: Supported on AKS Edge Essentials and AKS on Azure Local. Arc-enabled Video Indexer enables comprehensive AI-powered video analysis, including transcription, facial recognition, and object detection. It allows organizations to deploy sophisticated video processing solutions within hybrid and edge environments, ensuring efficient local data processing with improved security and minimal latency. MetalLB - Azure Arc Extension: Now supported on AKS Edge Essentials and AKS on Azure Local, MetalLB ensures efficient load balancing capabilities. This addition enhances network resilience and optimizes traffic distribution within Kubernetes environments. Comprehensive AI and Machine Learning Capabilities GPUs for AI Workloads: Now AKS enabled by Azure Arc supports a range of GPUs tailored for AI and machine learning workloads with GPU Partitioning) and GPU Passthrough Virtualization support. These options enable robust performance for resource-intensive AI and machine learning workloads, allowing for efficient use of GPU resources to run complex models and data processing tasks. Arc-enabled Azure Machine Learning: Support on AKS on Azure Local, AML capabilities for running sophisticated AI models. Businesses can leverage Azure’s powerful machine learning tools seamlessly across different environments, enabling them to develop, deploy, and manage machine learning models effectively on-premises and at the edge. Arc-enabled Video Indexer: It extends Azure's advanced video analytics capabilities to AKS enabled by Azure Arc. Organizations can now process and analyze video content in real-time, harnessing Azure's robust video AI tools to enhance video-based insights and operations. This support provides businesses with greater flexibility to conduct video analysis seamlessly in remote or hybrid environments Kubernetes AI Toolchain Orchestrator (Kaito + LoRA + QLoRA): Fully validated and support for fine-tuning and optimizing AI models, Kaito, LoRA and QLoRA are designed for edge deployments such as AKS on Azure Local. This combination enhances the ability to run and refine AI applications effectively in edge environments, ensuring performance and flexibility. Flyte Integration: Now supported on AKS on Azure Local, Flyte offers a scalable orchestration platform for managing machine learning workflows. This capability enables teams to build, execute, and manage complex AI pipelines efficiently, enhancing productivity and simplifying the workflow management process. Enhanced Infrastructure and Operations Management Infrastructure as Code (IaC) with Terraform: Now supported on AKS on Azure Local for both Connected and Air-gapped scenario, providing streamlined deployment capabilities through code. This support enables teams to automate and manage their Kubernetes infrastructure at scale more efficiently with Terraform. Anti-affinity, Pod CIDR, Taints/Labels: Available on AKS on Azure Local, these features provide enhanced infrastructure capabilities by allowing refined workload placement and advanced network configuration. Anti-affinity rules help distribute pods across different nodes to avoid single points of failure, while Pod CIDR simplifies network management by allocating IP ranges to pods. Taints and labels offer greater control over node selection, ensuring that specific workloads run on designated nodes and enhancing the overall efficiency and reliability of Kubernetes operations. Optimized Windows Node Pool Management: AKS enabled by Azure Arc now includes the capability to enable and disable Windows node pools for clusters. This enhancement helps prevent unnecessary binary downloads, benefiting customers with low-speed or limited internet connection. It optimizes resource usage, reduces bandwidth consumption, and enhances overall deployment efficiency, making it ideal for environments with network constraints. Kubernetes Development AKS-WSL: With AKS-WSL, developers can set up a local environment that mimics the experience of working with AKS. This makes it easier for developers to write, debug, and test Kubernetes applications locally before deploying them to a full AKS cluster. AKS-WSL VSCode Extension: The Visual Studio Code extension for AKS-WSL allows developers to write, debug, and deploy Kubernetes applications locally, streamlining development workflows. This setup improves productivity by providing efficient tools and capabilities, making it easier to develop, test, and refine Kubernetes workloads directly from a local machine. Arc Jumpstart: Supported AKS Edge Essentials and AKS on Azure Local. Arc Jumpstart simplifies deployment initiation, providing developers with a streamlined way to set up and start working with Kubernetes environments quickly. It makes it easier for teams to evaluate and experiment with AKS enabled by Azure Arc, offering pre-configured scenarios and comprehensive guidance. By reducing complexity and setup time, Arc Jumpstart enhances the developer experience, facilitating faster prototyping and smoother onboarding for new projects in hybrid and edge settings. Conclusion Microsoft Ignite 2024 has underscored the continued evolution of AKS enabled by Azure Arc, bringing more comprehensive, scalable, and secure solutions to diverse environments. These advancements support organizations in running cloud-native applications anywhere, enhancing operational efficiency and innovation. We welcome your feedback (aksarcfeedback@microsoft.com) and look forward to ongoing collaboration as we continue to evolve AKS enabled by Azure Arc.4.1KViews5likes0CommentsTechnology & Services partners are jumping on the bandwagon of Azure Arc
The Azure Arc partner ecosystem offers customers validated, enterprise grade solutions to run Azure on-premises and at the edge. Launched at Microsoft Ignite 2021 with support from industry-leading OEMs, hardware providers, platform providers, and ISVs, we are happy to announce the expansion of the Azure Arc network of trusted partners and validated platforms to data services.92KViews5likes3CommentsPublic Preview: Deploy OSS Large Language Models with KAITO on AKS on Azure Local
Announcement Along with Kubernetes AI Toolchain Operator (KAITO) on AKS GA release, we are thrilled to announce Public Preview refresh for KAITO on AKS on Azure Local. Customers can now enable KAITO as a cluster extension on AKS enabled by Azure Arc as part of cluster creation or day 2 using Az CLI. The seamless enablement experience makes it easy to get started with LLM deployment and fully consistent with AKS in the cloud. We also invest heavily to reduce frictions in LLM deployment such as recommending the right GPU SKU, validating preset models with GPUs and avoiding Out of Memory errors, etc. KAITO Use Cases Many of our lighthouse customers are exploring exciting opportunities to build, deploy and run AI Apps at the edge. We’ve seen many interesting scenarios like Pipeline Leak detection, Shrinkage detection, Factory line optimization or GenAI Assistant across many industry verticals. All these scenarios need a local AI model with edge data to satisfy low latency or regulatory requirements. With one simple command, customers can quickly get started with LLM in the edge-located Kubernetes cluster, and ready to deploy OSS models with OpenAI-compatible endpoints. Deploy & fine-tune LLM declaratively With KAITO extension, customers can author a simple YAML for inference workspace in Visual Studio Code or any text editor and deploy a variety of preset models ranging from Phi-4, Mistral, to Qwen with kubectl on any supported GPUs. In addition, customers can deploy any vLLM compatible text generation model from Hugging Face or even private weights models by following custom integration instructions. You can also customize base LLMs in the edge Kubernetes with Parameter Efficient Fine Tuning (PEFT) using qLoRA or LoRA method, just like the inference workspace deployment with YAML file. For more details, please visit the product documentation and KAITO Jumpstart Drops for more details. Compare and evaluate LLMs in AI Toolkit Customers can now use AI Toolkit, a popular extension in Visual Studio Code, to compare and evaluate LLMs whether it’s local or remote endpoint. With AI Toolkit playground and Bulk Run features, you can test and compare LLMs side by side and find out which model fits the best for your edge scenario. In addition, there are many built-in LLM Evaluators such as Coherence, Fluency, or Relevance that can be used to analyze model performance and generate numeric scores. For more details, please visit AI Toolkit Overview document. Monitor inference metrics in Managed Grafana The KAITO extension defaults to vLLM inference runtime. With vLLM runtime, customers can now monitor and visualize inference metrics with Azure Managed Prometheus and Azure Managed Grafana. Within a few configuration steps, e.g., enabling the extensions, labeling inference workspace, creating Service Monitor, the vLLM metrics will show up in Azure Monitor Workspace. To visualize them, customers can link the Grafana dashboard to Azure Monitor Workspace and view the metrics using the community dashboard. Please view product document and vLLM metric reference for more details. Get started today The landscape of LLM deployment and application is evolving at lightning speed - especially in the world of Kubernetes. With the KAITO extension, we're aiming to supercharge innovation around LLMs and streamline the journey from ideation to model endpoints to real-world impact. Dive into this blog as well as KAITO Jumpstart Drops to explore how KAITO can help you get up and running quickly on your own edge Kubernetes cluster. We’d love to hear your thoughts - drop your feedback or suggestions in the KAITO OSS Repo!1.1KViews4likes2CommentsAnnouncing Preview of Azure AI Video Indexer Cloud-to-Edge Version
Introducing the Public Preview of Azure Video Indexer enabled by Arc: Harness the full capabilities of Video and Audio Content Anywhere. We are excited to unveil that Azure Video Indexer cloud offering is expanding, as part of Microsoft’s adaptive cloud approach. The newly released Video Indexer extension can run within Azure Arc-enabled Kubernetes cluster. This tool allows you to harness the full capabilities of video and audio content from any location. Register for the public preview by submitting this form.4.5KViews4likes0Comments