Arc Jumpstart Training Video Series
Enter the Arc Jumpstart Training video series, now available on YouTube! This series has been crafted with care to equip users of Arc Jumpstart with the comprehensive knowledge and practical skills needed to unlock the full potential of various Arc Jumpstart solutions. Whether you're a newcomer starting your journey or an experienced user looking to refine your expertise, this series promises to be your ultimate guide. What Awaits You in the Arc Jumpstart Training Series? Designed to provide a structured and in-depth exploration of Arc Jumpstart's offerings, the series consists of five modules, each focusing on a specific aspect of the Arc Jumpstart ecosystem. These modules delve into everything from foundational concepts to advanced functionalities, ensuring that users have all the tools they need to succeed. Let’s take a closer look at what each module has to offer. Module 1: Introduction to Arc Jumpstart Every great journey begins with a solid introduction, and Module 1 delivers that. In this module, we explore the fundamental question: What is Arc Jumpstart? Azure Arc Jumpstart is a comprehensive, automated, and open-source platform designed to help users quickly set up and explore Azure Arc environments. It provides a variety of scenarios and tools to get started with Azure Arc, including: Jumpstart Scenarios: Automated, zero-to-hero scenarios for Arc-enabled servers, Kubernetes, and more. Jumpstart ArcBox: A virtual, hybrid sandbox that allows you to explore all major capabilities of Azure Arc with just one click. Jumpstart HCIBox: A dedicated Azure Local sandbox for trying out Azure Local services. Jumpstart Drops: Community-contributed artifacts, deployment guides, and code snippets. Jumpstart Gems: Detailed technical diagrams and end-to-end cloud scenarios. Jumpstart Agora: Explore comprehensive cloud-to-edge scenarios designed for specific industry needs. These resources are designed to help users deploy quickly, test easily, and evaluate confidently, leveraging the full power of the adaptive cloud. Module 2: Jumpstart ArcBox Arc Jumpstart ArcBox is a virtual, hybrid sandbox environment that allows users to explore and utilize the major capabilities of Azure Arc with ease. Here are some key features: One-Click Deployment: You can set up a complete Azure Arc environment with just one click, requiring only an Azure subscription. Curated Experiences: ArcBox offers tailored environments for different roles, such as IT professionals, DevOps engineers, and data professionals. Comprehensive Capabilities: It includes all major Azure Arc functionalities, enabling users to test, deploy, and evaluate various scenarios in a controlled setting. ArcBox is designed to simplify the process of getting started with Azure Arc, making it accessible and efficient for users to explore its full potential. Module 3: Jumpstart HCIBox (for Azure Local) Arc Jumpstart HCIBox is a turnkey solution that provides a complete sandbox for exploring Azure Local capabilities and hybrid cloud integration in a virtualized environment. Here are some key features: Dedicated Azure Local Sandbox: You can set up an Azure Local environment with just one click, requiring only an Azure subscription. Hybrid Cloud Integration: HCIBox allows you to explore the integration of Azure Local with hybrid cloud scenarios. Automated Deployment: It simplifies the process of deploying and testing Azure Local capabilities. HCIBox is designed to help users quickly get up and running with Azure Local, making it easier to evaluate and leverage its full potential. Module 4: Jumpstart Drops Arc Jumpstart Drops is a curated collection of scripts, tools, tutorials, and other resources contributed by the community for the community. These "Drops" are designed to make life easier for developers, IT professionals, and operations teams by providing small, self-contained pieces of code and artifacts that can be easily integrated into various projects. Here are some key features: Community Contributions: Anyone can contribute their own scripts, tools, and tutorials to the collection. Curated Content: The Drops are carefully selected to ensure quality and relevance. Diverse Resources: The collection includes a wide range of resources, from automation scripts to detailed tutorials. Arc Jumpstart Drops is a great way to share knowledge and tools, helping others to streamline their workflows and solve common challenges. Module 5: More Jumpstart and Next Steps The journey doesn’t end with the earlier modules. Module 5 explores what lies ahead, including: Next Steps: Guidance on how to continue your learning journey and leverage Jumpstart to its fullest potential. Jumpstart Lightning: A sneak peek into this exciting feature and how it can accelerate your workflows. Jumpstart Badges: Earn recognition for your expertise and showcase your achievements in the Jumpstart ecosystem. This module serves as a bridge to advanced learning opportunities and provides a roadmap for continued success. Get Started Today So, are you ready to enhance your skills and unlock the full potential of Arc Jumpstart? Head over to YouTube and dive into the Arc Jumpstart Training video series. Whether you’re deploying ArcBox for the first time, experimenting with HCIBox, or creating your first Jumpstart Drop, these videos are your ultimate resource. Don’t wait—your journey with Arc Jumpstart begins now!Arc Jumpstart Newsletter: March 2025 Edition
We’re thrilled to bring you the latest updates from the Arc Jumpstart team in this month’s newsletter. Whether you are new to the community or a regular Jumpstart contributor, this newsletter will keep you informed about new releases, key events, and opportunities to get involved in within the Azure Adaptive Cloud ecosystem. Check back each month for new ways to connect, share your experiences, and learn from others in the Adaptive Cloud community.Upgrade to Azure Local, version 23H2 OS
Azure Stack HCI is now part of Azure Local. Learn more. Today, we’re sharing an update on the upgrade to Azure Local, version 23H2 OS. As described in a previous blog post, moving from Azure Stack HCI, version 22H2 to Azure Local, version 23H2 is a two-step process. The first step is to upgrade the operating system using existing processes and tools. The second step is to apply the upgrade for the mandatory Azure Arc solution enablement, which is a guided experience via the Azure portal. It is urgent that you perform the first step and install the OS upgrade to Azure Local, version 23H2 OS by May 31, 2025. After then, Azure Stack HCI, version 22H2 OS reaches end of support, and your system will stop receiving critical security updates and will not be eligible for support requests. Hear directly from one of our Azure Local customers, Australian supermarket brand Coles, on their experience successfully upgrading the OS for 1000 Azure Local machines in just 8 days! Coles: “Preparing for the Future: Upgrading Azure Local (Stack HCI) from 22h2 to 23h2” As we approach the end of life for Azure Local (Stack HCI) 22h2 in May 2025, it is crucial to prepare for the upcoming changes in management and deployment introduced in 23h2. This transition marks a significant step towards enhancing our cloud deployment and upgrade processes. The first step in this journey is to upgrade the operating system and cluster functional levels. This foundational move sets the stage for a seamless transition to the new version. Our team successfully upgraded 1000 nodes from 22H2 to 23H2 in just 8 days, showcasing our dedication and efficiency. This remarkable achievement was made possible through meticulous planning, including risk assessments, timeline creation, resource allocation, and establishing contingency plans to ensure a smooth transition. Several key technologies and processes played a pivotal role in this upgrade. We leveraged PowerShell scripts for much of the process, finding them to be the most reliable and repeatable method. Through comprehensive testing, we identified improvements that ensured we maintained high standards and minimized risks for the production system rollouts. While the thought of upgrading so many nodes was daunting, utilizing these familiar tools significantly eased the upgrade process. Our team's expertise with these tools enabled us to address challenges promptly and maintain a steady pace. Additionally, cross-departmental collaboration was crucial in streamlining operations and troubleshooting issues effectively. Looking ahead, we are excited about the new features and enhancements in 23H2. We are also planning to further refine our upgrade processes based on the insights gained from this experience. In conclusion, the successful upgrade from 22H2 to 23H2 demonstrates our team's capability to manage complex transitions efficiently. As we continue to innovate and improve our Azure Local deployment strategies, we remain committed to delivering high-quality solutions that meet the evolving needs of our organization. Jason Tayler, Lead Senior Systems Engineer, Coles Conclusion Coles is one of many customer success stories, and we hope this inspires you to upgrade your systems! On behalf of the Azure Local team, we thank you for your continuous trust and feedback. Learn more To learn more about installing the OS upgrade, refer to the upgrade documentation. For known issues and remediation guidance, see the Azure Local Supportability GitHub repository.Announcing Private Preview: ArgoCD through Microsoft GitOps
We're excited to announce the Private Preview for Microsoft GitOps ArgoCD. Delivered as a cluster extension across Azure Kubernetes Service (AKS) and Azure Arc-enabled Kubernetes, Microsoft GitOps delivers a consistent and robust management, security, and deployment experience for ArgoCD across your heterogeneous environments. This capability complements Microsoft GitOps existing support for Flux, which is currently in General Availability. By signing up for the Private Preview, you'll get access to the ArgoCD cluster extension and the opportunity to connect with and provide feedback to the Microsoft GitOps product group. Sign up today at https://aka.ms/MicrosoftGitOpsPreviewSignup. Advantages of the current Microsoft GitOps experience for ArgoCD include: Simplified, templatized deployment as a cluster extension Managed and automated upgrade reducing overhead Official supportability and security for enterprise readiness Integration with Azure identity and authentication We look forward to continuing to deliver on an exceptional Microsoft GitOps experience across ArgoCD and Flux for customers running containerized workloads not only on Azure, but also on on-premises and other public clouds through Azure Arc.Arc Jumpstart Newsletter: February 2025 Edition
We’re thrilled to bring you the latest updates from the Arc Jumpstart team in this month’s newsletter. Whether you are new to the community or a regular Jumpstart contributor, this newsletter will keep you informed about new releases, key events, and opportunities to get involved in within the Azure Adaptive Cloud ecosystem. Check back each month for new ways to connect, share your experiences, and learn from others in the Adaptive Cloud community.Arc Jumpstart Newsletter: January 2025 Edition
We’re thrilled to bring you the latest updates from the Arc Jumpstart team in this month’s newsletter. Whether you are new to the community or a regular Jumpstart contributor, this newsletter will keep you informed about new releases, key events, and opportunities to get involved in within the Azure Adaptive Cloud ecosystem. Check back each month for new ways to connect, share your experiences, and learn from others in the Adaptive Cloud community.Announcing Jumpstart ArcBox 25Q1 general availability
We are thrilled to announce the first major update to ArcBox following our release of ArcBox 3.0 in August 2024. ArcBox has been an invaluable resource for IT professionals, DataOps teams, and DevOps practitioners, providing comprehensive solutions to evaluate how to deploy, manage, and operate Arc-enabled environments. With this release, we have introduced Windows Server 2025 on both the ArcBox-Client as well as in a nested VM, making it possible for you to evaluate a range of new features and enhancements that elevate the functionality, performance, and user experience. WinGet and Windows Terminal Integration One of the standout enhancements in Windows Server 2025 is the inclusion of WinGet and Windows Terminal. These tools are now built-in components of Windows Server 2025 and no longer require bootstrapping in our automation processes. Advanced Management Capabilities for Arc-enabled servers Windows Server 2025 introduces new management capabilities specifically designed for Arc-enabled servers. These capabilities enhance the control and oversight of server environments, providing more robust tools for monitoring, configuration, and maintenance. The enhancements are now available in ArcBox to be evaluated. SSH Included and Enabled Another significant update in Windows Server 2025 is the inclusion of SSH as a native component. This addition is a major step forward, as it eliminates the need for external SSH installations. However, it is important to note that while SSH is included, it needs to be enabled manually. This feature enhances secure access to servers, facilitating more efficient remote management and operations. In ArcBox, SSH is enabled by the automated setup and ready to start evaluating. SSH for Arc-enabled servers enables SSH based connections to Arc-enabled servers without requiring a public IP address or additional open ports. This functionality can be used interactively, automated, or with existing SSH based tooling, allowing existing management tools to have a greater impact on Azure Arc-enabled servers. You can use Azure CLI or Azure PowerShell to connect to one of the Azure Arc-enabled servers using SSH. In addition to SSH, you can also connect to the Azure Arc-enabled servers, Windows Server virtual machines using Remote Desktop tunneled via SSH. Also, Remote PowerShell over SSH is available for Windows and Linux machines. SSH for Arc-enabled servers also enables SSH-based PowerShell Remoting connections to Arc-enabled servers without requiring a public IP address or additional open ports. After setting up the configuration, we can use native PowerShell Remoting commands. Configurable SQL Server Edition to support Performance Dashboards ArcBox now provides the flexibility to deploy SQL Server Standard or Enterprise editions on the ArcBox-SQL guest VM, replacing the previously default Developer edition. This enhancement empowers users to experience advanced Arc-enabled SQL Server monitoring through Performance Dashboard reports. Available in both the ITPro and DataOps configurations, this feature ensures tailored performance monitoring capabilities for diverse use cases. To configure the SQL Server edition during deployment: Portal Deployment: Specify the desired SQL Server edition during setup. Bicep Deployment: Use the sqlServerEdition parameter to define the edition. ARM Template Deployment: Set the edition via the sqlServerEdition parameter. Below is an example Performance Dashboard report from an Arc-enabled SQL Server using the Standard or Enterprise editions, highlighting comprehensive insights and monitoring capabilities. Cost Optimizations We optimized the storage costs significantly by changing the ArcBox Client VM data disk from Premium SSD to Premium SSD v2. This change allows for better performance at a lower cost, making ArcBox even more economical for various use cases. With this optimization, users can enjoy faster data access speeds and increased storage efficiency. We also introduced support for enabling Azure VM Spot pricing for the ArcBox Client VM, allowing users to take advantage of cost savings on unused Azure capacity. This feature is ideal for workloads that can tolerate interruptions, providing an economical option for testing and development environments. By leveraging Spot pricing, users can significantly reduce their operational costs while maintaining the flexibility and scalability offered by Azure. You may leverage the advisor on the Azure Spot Virtual Machine pricing page to estimate costs for your selected region. Here is an example for running the ArcBox Client Virtual Machine in the East US region: Visit the ArcBox FAQ to see the updated price estimates for running ArcBox in your environment. The new deployment parameter enableAzureSpotPricing is disabled by default, so users who wants to take advantage of this capability will need to opt-in. Along with the option to opt-in for Azure Spot pricing, we also added new parameters for enabling Auto Shutdown: Auto Shutdown is enabled by default, and will configure the built-on Auto-shutdown feature for Azure VMs: Summary The latest update to ArcBox not only focuses on new features but also on enhancing overall cost and performance. The integration of new operating system versions and management capabilities ensures a smoother, more efficient workflow for IT professionals, DataOps teams, and DevOps practitioners to evaluate Azure Arc services. We invite our community to explore these new features and take full advantage of the enhanced capabilities of ArcBox with Windows Server 2025 support. Your feedback is invaluable to us, and we look forward to hearing about your experiences and insights as you navigate these new enhancements. Watch our release announcement episode of Jumpstart Lightning and get started today by visiting aka.ms/JumpstartArcBox!AKS Arc - Optimized for AI Workloads
Overview Azure is the world’s AI supercomputer providing the most comprehensive AI capabilities ranging from infrastructure, platform services to frontier models. We’ve seen emerging needs among Azure customers to use the same Azure-based solution for AI/ML on the edge with minimized latencies while staying compliant with industry regulation or government requirement. Azure Kubernetes Service enabled by Azure Arc (AKS Arc) is a managed Kubernetes service that empowers customers to deploy and manage containerized workload whether they are in data centers or at edge locations. We want to ensure AKS Arc provides optimal experience for AI/ML workload on the edge, throughout the whole development lifecycle from AI infrastructure, Model deployment, Inference, Fine-tuning, and Application. AI infrastructure AKS Arc supports Nvidia A2, A16, and T4 for compute-intensive workload such as machine learning, deep learning, model training. When GPUs are enabled in Azure Local; AKS Arc customers can provision GPU node pools from Azure and host AI/ML workload in the Kubernetes cluster on the edge. For more details, please visit instructions from GPU Nodepool in AKS Arc. Model deployment and fine tuning Use KAITO for language model deployment, inference and fine tuning Kubernetes AI Toolchain Operator (KAITO) is an open-source operator that automates and simplifies the management of model deployments on a Kubernetes cluster. With KAITO, you can deploy popular open-source language models such as Phi-3 and Falcon, and host them in the cloud or on the edge. Along with the currently supported models from KAITO, you can also onboard and deploy custom language models following this guidance in just a few steps. AKS Arc has been validated with the latest KAITO operator via helm-based installation, and customers can now use KAITO in the edge to: Deploy language models such as Falcon, Phi-3, or their custom models Automate and optimize AI/ML model inferencing for cost-effective deployments, Fine-tune a model directly in a Kubernetes cluster, Perform parameter efficient fine tuning using low-rank adaptation (LoRA) Perform parameter efficient fine tuning using quantized adaptation (QLoRA) You can get started by installing KAITO and deploying a model for inference on your edge GPU nodes with KAITO Quickstart Guidance. You may also refer to KAITO experience in AKS in cloud: Deploy an AI model with the AI toolchain operator (Preview) Use Arc-enabled Machine Learning to train and deploy models in the edge For customers who are already familiar with Azure Machine Learning (AML), Azure Arc-enabled ML extends AML in Azure and enables customers to target any Arc enabled Kubernetes cluster for model training, evaluation and inferencing. With Arc ML extension running in AKS Arc, customers can meet data-residency requirements by storing data on premises during model training and deploy models in the cloud for global service access. To get started with Arc ML extension, please view instructions from Azure Machine Learning document . In addition, AML extension can now be used for a fully automated deployment of a curated list of pre-validated language and traditional AI models to AKS clusters, perform CPU and GPU-based inferencing, and subsequently manage them via Azure ML Studio. This experience is currently in gated preview, please view another Ignite blog for more details. Use Azure AI Services with disconnected container in the edge Azure AI services enable customers to rapidly create cutting-edge AI applications with out-of-the-box and customizable APIs and models. It simplified the developer experience to use APIs and embed the ability to see, hear, speak, search, understand and accelerate decision-making into the application. With disconnected Azure AI service containers, customers can now download the container to an offline environment such as AKS Arc and use the same APIs available from Azure. Containers enable you to run Azure AI services APIs in your own environment and are great for your specific security and data governance requirements. Disconnected containers enable you to use several of these APIs disconnected from the internet. Currently, the following containers can be run in this manner: Speech to text Custom Speech to text Neural Text to speech Text Translation (Standard) Azure AI Vision - Read Document Intelligence Azure AI Language Sentiment Analysis Key Phrase Extraction Language Detection Summarization Named Entity Recognition Personally Identifiable Information (PII) detection To get started with disconnected container, please view instructions at Use Docker containers in disconnected environments . Build and deploy data and machine learning pipelines with Flyte Flyte is an open-source orchestrator that facilitates building production-grade data and ML pipelines. It is a Kubernetes native workflow automation tool. Customers can focus on experimentation and providing business value without being an expert in infrastructure and resource management. Data scientists and ML engineers can use Flyte to create data pipelines for processing petabyte-scale data, building analytics workflow for business or finance, or leveraging it as ML pipeline for industry applications. AKS Arc has been validated with the latest Flyte operator via helm-based installation, customers are welcome to use Flyte for building data or ML pipelines. For more information, please view instructions from Introduction to Flyte - Flyte and Build and deploy data and machine learning pipelines with Flyte on Azure Kubernetes Service (AKS). AI-powered edge applications with cloud-connected control plane Azure AI Video Indexer, enabled by Azure Arc Azure AI Video Indexer enabled by Arc enables video and audio analysis, generative AI on edge devices. It runs as Azure Arc extension on AKS Arc and supports many video formats including MP4 and other common formats. It also supports several languages in all basic audio-related models. The Phi 3 language model is included and automatically connected with your Video Indexer extension. With Arc enabled VI, you can bring AI to the content for cases when indexed content can’t move to the cloud due to regulation or data store being too large. Other use cases include using on-premises workflow to lower the indexing duration latency or pre-indexing before uploading to the cloud. You can find more details from What is Azure AI Video Indexer enabled by Arc (Preview) Search on-premises data with a language model via Arc extension Retrieval Augmented Generation (RAG) is emerging to augment language models with private data, and this is especially important for enterprise use cases. Cloud services like Azure AI Search and Azure AI Studio simplify how customers can use RAG to ground language models in their enterprise data in cloud. The same experience is coming to the edge and now customers can deploy an Arc extension and ask questions about on-premises data within a few clicks. Please note this experience is currently in gated preview and please see another Ignite blog for more details. Conclusion Developing and running AI workload at distributed edges brings clear benefits such as using cloud as universal control plane, data residency, reduced network bandwidth, and low latency. We hope the products and features we developed above can benefit and enable new scenarios in Retail, Manufacturing, Logistics, Energy, and more. As Microsoft-managed Kubernetes on the edge, AKS Arc not only can host critical edge applications but also optimized for AI workload from hardware, runtime to application. Please share your valuable feedback with us (aksarcfeedback@microsoft.com) and we would love to hear from you regarding your scenarios and business impact.
