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!Introducing Azure Local: cloud infrastructure for distributed locations enabled by Azure Arc
Today at Microsoft Ignite 2024 we're introducing Azure Local, cloud-connected infrastructure that can be deployed at your physical locations and under your operational control. With Azure Local, you can run the foundational Azure compute, networking, storage, and application services locally on hardware from your preferred vendor, providing flexibility to meet your requirements and budget.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.Speed Innovation with Arc-enabled Kubernetes Applications
As our annual Ignite conference begins in Chicago, I am delighted to share the latest in our effort to empower our customers to rapidly build and scale applications across boundaries: Azure Container Storage, Azure Key Vault Secret Store, Arc Gateway, Azure Monitor Pipeline, Workload Identity Federation, new options for AI workloads with AKS Arc, and the launch of our Azure Arc ISV partner program. In addition, we just published a white paper with more details. In today’s quickly evolving business environment, speed and agility in software innovation are crucial for companies to compete. Organizations of all shapes and sizes need to rapidly build (or buy), deploy, and operate secure, resilient applications to stay competitive. Cloud computing has revolutionized how companies do this with modern, cloud native practices. But many applications don’t just run in the cloud, they run across the vast, distributed landscape that defines customer environments today. Coles, an Australian supermarket retailer, needed to streamline their development and update process for the applications their customers depend on whether they are in-store, online or engaged in a hybrid experience using their mobile app. Emirates Global Aluminium needed to optimize production, support advanced AI and automation solutions, enhance cost savings by applying intelligence at the edge, and optimize processing for massive amounts of real-time readings from sensors, machinery, and production lines. Delivering on the needs of organizations like Coles and Emirates Global Aluminum requires specific technologies that help teams reduce complexity and increase release velocity across the application development lifecycle. I like to think of these in three groups, representing areas of investment for us today and moving forward. As customers invest in applications to fuel their business, many of these solutions come from the broad ecosystem of independent software vendors (ISVs). We are taking an ecosystem approach, helping ISVs to develop and market modern, Arc-enabled applications. This is why I am very excited to announce our Azure Arc ISV partner program and our first set of Arc-enabled applications in the Azure Marketplace. Below is a full list of the announcements we are making for this space at Ignite: Announcements New capabilities for the development of enterprise-class Kubernetes applications Azure Container Storage: At the edge, customers experience multiple challenges with data: sharing, resiliency, storage capacity, space management, and cloud connection, among others. We are proud to announce Azure Container Storage enabled by Azure Arc (ACSA), a first-party Kubernetes native Arc extension designed to solve these customer edge storage needs. ACSA offers high availability and fault tolerance for Kubernetes clusters ReadWriteMany persistent volumes that can be provisioned as Kubernetes native Persistent Volume Claims (PVCs). Available configuration options include keeping data local or transferring it to Azure storage services, such as Blob, ADLSgen2 and OneLake Fabric. ACSA is suitable for production workloads and is available as a standard component of the Azure IoT Operations GA release. Azure Key Vault Secret Store: Customers need the confidence and scalability that comes with unified secrets management in the cloud, while maintaining disconnection-resilience for operational activities at the edge. To help them with this, the Azure Key Vault Secret Store Extension for Arc-enabled Kubernetes automatically synchronizes secrets from an Azure Key Vault to a Kubernetes cluster for offline access. This means customers can use Azure Key Vault to store, maintain, and rotate secrets, even when running a Kubernetes cluster in a semi-disconnected state. Synchronized secrets are stored in the cluster secret store, making them available as Kubernetes secrets to be used in all the usual ways—mounted as data volumes or exposed as environment variables to a container in a Pod. Azure Arc Gateway: Customers face challenges with complex network configurations and multiple endpoints, which can be difficult to manage and secure. The Azure Arc Gateway for Arc-enabled Kubernetes alleviates these issues by reducing the number of required endpoints for using Azure Arc, thereby streamlining the enterprise proxy configuration. This simplification makes it significantly easier for customers to set up their networks and leverage the full capabilities of Azure Arc. By centralizing network traffic through a single, unique endpoint, the Azure Arc Gateway not only enhances security by minimizing the attack surface but also improves operational efficiency by reducing the time and effort needed for network setup and maintenance. This centralized approach ensures that customers can manage their Kubernetes clusters more effectively, providing a seamless and consistent experience across diverse environments. Azure Monitor Pipeline: As enterprises scale their infrastructure and applications, the volume of observability data naturally increases, and it is challenging to collect telemetry from certain restricted environments. We are extending our Azure Monitor pipeline at the edge to enable customers to collect telemetry at scale from their edge environment and route to Azure Monitor for observability. With Azure Monitor pipeline at edge, customers can collect telemetry from the resources in segmented networks that do not have a line of sight to cloud. Additionally, the pipeline prevents data loss by caching the telemetry locally during intermittent connectivity periods and backfilling to the cloud, improving reliability and resiliency. Workload Identity Federation: Customers need both simplicity and strong security from their workload identity management, especially when their solutions run in or across distributed environments. Workload Identity Federation delivers this by allowing software workloads running on Kubernetes clusters to access Azure resources without using traditional application credentials like secrets or certificates, which pose security risks. Instead, you can configure a user-assigned managed identity or app registration in Microsoft Entra ID to trust tokens from an external identity provider (IdP) like Kubernetes. This authentication option eliminates the need for manual credential management and reduces the risk of credential leaks or expirations. Creating an ecosystem of Arc-enabled Kubernetes applications Azure Arc ISV partner program: Customers want the ability to utilize third-party (3P) software to build their enterprise applications on Kubernetes. Currently, customers have to run multiple scripts to install any third party application on an Arc-enabled Kubernetes cluster. We are excited to announce the launch of our Azure Arc ISV ecosystem, which enables Azure to be a one-stop-shop. Now customers can install an application that has been validated on Arc and enabled onto their cluster through the Azure portal. With the click of a button in the Azure portal, users can install MongoDB, Redis, CloudCasa, MinIO, and DataStax on their Arc-enabled Kubernetes cluster. This enables customers to develop using enterprise grade tools on top of Azure Arc. This program will enhance the developer ecosystem as we onboard more and more partners. Exciting new ways to engage and get started Join the Adaptive cloud community: Connect with professionals passionate about hybrid, multi-cloud, and edge technologies. This space is designed for those looking to engage with peers and Microsoft experts, explore the latest in Azure Arc, Azure Local, AKS, and IoT, and expand their knowledge through valuable resources and discussions. Whether you are just starting out or an industry professional, this community is the perfect platform to share insights, ask questions, and grow your skills in the evolving Adaptive cloud ecosystem. Learn more about ways to get involved on our Adaptive cloud GitHub. Join the Adaptive cloud Community LinkedIn Group Join the Adaptive cloud Community Teams Channel Visit Arc Jumpstart: Explore the resources available to help you learn what Azure Arc can do for you and your business. Recent additions include Jumpstart Drops, an opportunity to contribute to and use community contributions, and Jumpstart Agora Hypermarket an industry scenario bringing the power of the Adaptive cloud approach for retail to life. I hope you enjoy the week visiting or tuning into Microsoft Ignite. You can find a full listing of opportunities to learn more about our Adaptive cloud approach at Ignite here: aka.ms/AdaptiveCloudIgnite.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.Evolving Stretch Clustering for Azure Local
Stretched clusters in Azure Local, version 22H2 (formerly Azure Stack HCI, version 22H2) entail a specific technical implementation of storage replication that spans a cluster across two sites. Azure Local, version 23H2 has evolved from a cloud-connected operating system to an Arc-enabled solution with Arc Resource Bridge, Arc VM, and AKS enabled by Azure Arc. Azure Local, version 23H2 expands the requirements for multi-site scenarios beyond the OS layer, while Stretched clusters do not encompass the entire solution stack. Based on customer feedback, the new Azure Local release will replace the Stretched clusters defined in version 22H2 with new high availability and disaster recovery options. For Short Distance Rack Aware Cluster is a new cluster option which spans two separate racks or rooms within the same Layer-2 network at a single location, such as a manufacturing plant or a campus. Each rack functions as a local availability zone across layers from OS to Arc management including Arc VMs and AKS enabled by Azure Arc, providing fault isolation and workload placement within the cluster. The solution is configured with one storage pool to reduce additional storage replication and enhance storage efficiency. This solution delivers the same Azure deployment and management experience as a standard cluster. This setup is suitable for edge locations and can scale up to 8 nodes, with 4 nodes in each rack. Rack Aware Cluster is currently in private preview and is slated to public preview and general release in 2025. For Long Distance Azure Site Recovery can be used to replicate on-premises Azure Local virtual machines into Azure and protect business-critical workloads. This allows Azure cloud to serve as a disaster recovery site, enabling critical VMs to be failed over to Azure in case of a local cluster disaster, and then failed back to the on-premises cluster when it becomes operational again. If you cannot fail over certain workloads to cloud and require long distance of disaster recovery, like in two different cities, you can leverage Hyper-V Replica to replicate Arc VMs to the secondary site. Those VMs will become Hyper-V VMs on the secondary site, they will become Arc VMs once they fail back to the original cluster on the first site. Additional Options beyond Azure Local If the above solutions in Azure Local do not cover your needs, you can fully customize your solution with Windows Server 2025 which introduces several advanced hybrid cloud capabilities designed to enhance operational flexibility and connectivity across various environments. Additionally, it offers various replication technologies like Hyper-V Replica, Storage Replica and external SAN replication that enable the development of tailored datacenter disaster recovery solutions. Learn more from the Windows Server 2025 now generally available, with advanced security, improved performance, and cloud agility - Microsoft Windows Server Blog What to do with existing Stretched clusters on version 22H2 Stretched clusters and Storage Replica are not supported in Azure Local, version 23H2 and beyond. However, version 22H2 stretched clusters can stay in supported state in version 23H2 by performing the first step of operating system upgrade as shown in the following diagram to 23H2 OS. The second step of the solution upgrade to Azure Local is not applicable to stretched clusters. This provides extra time to assess the most suitable future solution for your needs. Please refer to the About Azure Local upgrade to version 23H2 - Azure Local | Microsoft Learn for more information on the 23H2 upgrade. Refer the blog on Upgrade from Azure Stack HCI, version 22H2 to Azure Local | Microsoft Community Hub. Conclusion We are excited to be bringing Rack Aware Clusters and Azure Site Recovery to Azure Local. These high availability and disaster recovery options allow customers to address various scenarios with a modern cloud experience and simplified management.Microsoft Ignite 2024: Celebrating the Success of Our First Show Floor Interview Series
🔥 Microsoft Ignite 2024 has wrapped, and what an event it was! This year, we tried something new - the Ignite Show Floor Interview Series - and it is safe to say it was a huge success. Alongside liorkamrat and thomasmaurer, I had the privilege of conducting interviews with some of the most innovative minds in our Adaptive Cloud ecosystem. We spoke with partners, customers, ISVs from the Azure Arc ISV program (Announcing the Azure Arc ISV Partner Program at Ignite), and Microsoft MVPs, diving into their unique stories, their takeaways from Ignite, and how they’re leveraging Microsoft technologies to drive innovation. 17 Interviews, Countless Stories In total, we produced 17 videos during Ignite, each offering a fresh perspective on cloud innovation. Here is a snapshot on everyone we talked to: Why This Matters This was our first year running the Show Floor Interview Series, and it exceeded our expectations. Here’s why we’re excited: Showcasing Innovation: These interviews highlighted the incredible work being done across the Adaptive Cloud ecosystem, from large enterprises to individual experts Building Community: The series wasn’t just about interviews; it was about connecting with people, hearing their challenges, and celebrating their successes Expanding Reach: By sharing these conversations on our Jumpstart YouTube channel and LinkedIn, we helped bring these stories to a wider audience - even for those that were not able to attend Ignite this year What's Next? While Ignite 2024 is over, this is just the beginning. We are already thinking about how to expand and improve this series for future events. Expect more interviews, more insights, and more opportunities to engage with the Microsoft community next year. And we didn’t just stick to business - we even had a little fun with attendees, asking them what their favorite Microsoft Ignite swag was! 🚀 Haven’t seen the interviews yet? Check out our full playlist on the Arc Jumpstart YouTube channel here. Thank You! A huge thank you to everyone who participated and a huge thank you to everyone who tuned in to our series! To our partners, customers, ISVs, and MVPs - thank you for sharing your time and insights. You made this series what it is, and we are excited to continue building on this momentum! Here’s to the power of innovation, collaboration, and community. Let’s keep the conversation going!Ignite 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.Introducing Jumpstart Gems
Today, the Jumpstart team is thrilled to share some exciting news! The "Architecture Posters Diagrams Bundle (APD Bundle)" has officially been rebranded as "Jumpstart Gems". While the name has changed, our commitment to providing high-quality, informative, and pleasing architecture diagrams that you all love remains the same. Jumpstart Gems reflects what the Jumpstart program really represents: curated, indispensable, resources that help you uncover the “gems” of knowledge in the adaptive cloud product ecosystem. What’s New? As we roll out the new branding, you may start noticing website updates reflecting the Jumpstart Gems name. But that is just the beginning - we have enhancements in the works to make the Gems even more valuable and engaging 🤩. Stay tuned for updates! Introducing Jumpstart community badge for Gems! With the recent announcement of Jumpstart Badges, we are excited to recognize the incredible efforts of those who have also contributed to Jumpstart Gems. If you have worked with the Arc Jumpstart team to help create any diagrams or posters, you are eligible for our new Jumpstart Gems Badge - "Treasure Hunter" Thank You for Being Part of the Journey The transformation from Architecture Posters Diagrams Bundle to Jumpstart Gems marks an exciting milestone in our journey together. Whether you are a long-time user of these resources or a new contributor, we are grateful for your support and enthusiasm.
