Scale Data Collection Endpoint private connectivity with IP Endpoint Compression - Preview
Scale Azure Monitor Private Link with data collection endpoint IP compression As organizations expand their Azure Monitor deployments, private networking needs to scale with them. For enterprises running large, distributed environments, that can create an increasingly important challenge: how do you grow private monitoring without consuming private IP address space at the same rate? Azure Monitor is introducing private IP endpoint compression for data collection endpoints (DCEs) connected through Azure Monitor Private Link Scope (AMPLS). This capability is designed to reduce the private IP footprint by ~90%-95% associated with DCEs while preserving the Azure Monitor Private Link architecture and the security controls customers already use. The challenge: private monitoring at enterprise scale Organizations often centralize Azure Monitor connectivity through carefully governed hub-and-spoke networks. As these environments grow, they can include monitored resources, data collection rules (DCRs), DCEs, and Log Analytics workspaces distributed across multiple regions. When private connectivity is required, DCEs are connected through AMPLS. The associated private endpoint uses addresses from a customer-managed subnet. As more DCEs are added, this can increase the private IP footprint required for Azure Monitor connectivity and create challenges such as: Increased subnet-capacity planning Additional network-governance reviews Delays when onboarding workloads or regions Provisioning challenges when available subnet capacity becomes constrained More operational complexity in centralized DNS and hub-and-spoke environments As customers onboard more Azure resources to send telemetry over private networks, they need a scalable way to preserve valuable private IP address space without increasing the operational complexity of their network-isolated monitoring environment. Introducing DCE private IP endpoint compression DCE private IP endpoint compression changes how DCE service endpoints are represented behind an AMPLS private endpoint. Instead of having the private IP footprint scale directly with every DCE, the compressed architecture groups compatible DCE service endpoints regionally and allows them to use a smaller, bounded set of private IP configurations. Requests continue to be routed to the intended DCE based on the requested endpoint and the existing Azure Monitor authorization context. The result is a more scalable private-network architecture without introducing a new data collection model. What does this mean for customers? Large enterprises have limited, tightly managed, often fragmented private IPv4 spaces. Private endpoints require IP addresses from customers' private IPv4 subnets. With private IP endpoint compression, all DCEs in a region share 3 regional private IPs. For example, 20 DCEs drop from 60 private IPs to 3, which is 95% fewer. Private IP address use stops growing with every DCE you add. There are no changes to how DCEs, DCRs, AMPLS, Azure Monitor Agent or Log Analytics work. Use private address space more efficiently A smaller, bounded private IP footprint can preserve valuable subnet capacity for additional workloads and Azure services. This can be particularly useful for enterprises operating with constrained private IP address space or centralized network-allocation processes. Make network planning more predictable Instead of treating each additional DCE as a proportional increase in private IP requirements, network teams can plan capacity around the regional architecture. This approach makes the network planning more predictable for enterprise customers. Scale monitoring across more workloads and regions Reducing pressure on private IP address space can make it easier to expand monitoring across applications, subscriptions, and regions without repeatedly redesigning private endpoint subnets. Reduce operational friction A more compact endpoint representation can reduce the networking work associated with subnet capacity reviews, expansion planning, and Private Link onboarding. What stays the same? One of the goals of this design is to improve network scalability while preserving the Azure Monitor model customers already use. DCE private IP endpoint compression doesn't change: The role of AMPLS as the private Azure Monitor network boundary The role of the private endpoint connecting a virtual network to AMPLS AMPLS Open and Private Only access modes DCR collection, transformation, and routing logic Azure Monitor Agent configuration semantics Log Analytics tables, retention, or KQL query behavior The amount of telemetry ingested into Azure Monitor Application Insights data collection, which doesn't use DCEs Azure Monitor ingestion charges Azure Private Link data-processing charges based on data volume Customers should continue following their existing DNS, routing, network security, public network access, and AMPLS configuration requirements. Preparing for the controlled preview DCE private IP endpoint compression is currently intended for subscriptions participating in a controlled preview. For customers participating in the preview, we recommend starting with a nonproduction or limited deployment. Before expanding the deployment: Map your topology. Understand the virtual networks, peering, AMPLS resources, private endpoints, DCEs, DCRs, workspaces, DNS zones, and supporting subnets involved. Review DNS ownership. Pay particular attention to networks sharing Azure Monitor private DNS zones and use a deliberate AMPLS topology. Establish a baseline. Record your existing private endpoint IP configurations and DCE DNS responses. Confirm regional alignment. Review the relationship between monitored resources, DCE configuration access, ingestion endpoints, and destination workspaces. Review access modes. Confirm the appropriate use of AMPLS Open or Private Only access modes for your security requirements. Validate end to end. Verify DNS resolution, Azure Monitor Agent configuration access, DCR health, ingestion, transformation, and query behavior before expanding the deployment. Looking ahead Bottom line: DCE private IP endpoint compression is designed to make private Azure Monitor deployments easier to scale by reducing the relationship between DCE growth and private IP consumption, while preserving the Azure Monitor and AMPLS architecture customers use today. Customers interested in participating in the controlled preview can contact the author via email with their subscription need to be allowlisted for the preview. This preview is available only to allowlisted subscriptions. To request access, submit your Azure subscription ID through the DCE IP Endpoint Compression preview onboarding form. Wait for Microsoft to confirm that your subscription is preview-enabled before you create the test DCEs. IP compression applies automatically to newly created DCEs in preview-enabled subscriptions. There's no additional setting to enable when you create a DCE or associate it with AMPLS. We look forward to helping customers scale private Azure Monitor deployments while making more efficient use of their network address space. Resources Learn more about designing and configuring private connectivity for Azure Monitor: Scale Data Collection Endpoint (DCE) private connectivity with IP Endpoint Compression (Preview) - Azure Monitor | Microsoft Learn Use Azure Private Link to connect networks to Azure Monitor Learn how Azure Monitor Private Link Scope (AMPLS), private endpoints, and Azure Monitor resources work together to provide private connectivity. Design your Azure Monitor Private Link configuration Review network topology, DNS, AMPLS limits, hub-and-spoke architectures, and other considerations when planning Azure Monitor Private Link. Configure Azure Monitor Private Link Follow the configuration guidance for creating an AMPLS, connecting Azure Monitor resources such as Data Collection Endpoints (DCEs), and connecting the AMPLS to a private endpoint. Prevent IPv4 Exhaustion in Azure - Azure Architecture Center | Microsoft Learn
Announcing public preview of query-based metric alerts in Azure Monitor
Azure Monitor metric alerts are now more powerful than ever Azure Monitor metric alerts now support all Azure metrics - including platform, Prometheus, and custom metrics - giving you complete coverage for your monitoring needs. In addition, metric alerts now offer powerful query capabilities with PromQL, enabling complex logic across multiple metrics and resources. This makes it easier to detect patterns, correlate signals, and customize alerts for modern workloads like Kubernetes clusters, VMs, and custom applications. Key Benefits Full metrics coverage: metric alerts now support alerting on any Azure metrics including platform metrics, Prometheus metrics and custom metrics. PromQL-Powered Conditions: Use PromQL to select, aggregate, and transform metrics for advanced alerting scenarios. Powerful event detection: Query-based alert rules can now detect intricate patterns across multiple timeseries based on metric change ratio, complex aggregations, or comparison between different metrics and timeseries. You can also analyze metrics across different time windows to identify change in metric behavior over time. Flexible Scoping: For query-based alert rules, choose between resource-centric alerts for granular RBAC or workspace-centric alerts for cross-resource visibility. Alerting at scale: Query-based alert rules allow monitoring metrics from multiple resources within a subscription or a resource group, using a single rule. Managed Identity Support: Securely authorize queries using Azure Managed Identity, ensuring compliance and reducing credential management overhead. Customizable Notifications: Add dynamic custom properties and custom email subjects for faster triage and context-rich alerting. Reuse community alerts: Easily import and re-use PromQL alert queries from the open-source community or from other Prometheus-based monitoring systems. Supported metrics At this time, query-based metric alerts support any metrics ingested into Azure Monitor Workspace (AMW). This currently includes: Metrics collected by Azure Monitor managed service for Prometheus, from Azure Kubernetes Services clusters (AKS) or from other sources. Virtual machine OpenTelemetry (OTel) Guest OS Metrics Other OTel custom metrics collected into Azure Monitor. You can still create threshold-based metric alerts as before on Azure platform metrics. Query-based alerts on platform metrics will be added in future releases. Comparison: Query-based metric alerts vs. Prometheus rule groups alerts Query-based metric alerts serve as an alternative to alerts defined in Prometheus rule groups. Both options remain viable and execute the same PromQL-based alerting logic. However, metric alerts are natively integrated with Azure Monitor, aligning seamlessly with other Azure alert types. They now support all your metric alerting needs within the same rule type. They also offer richer functionality and greater flexibility, making them a strong choice for teams looking for consistency across Azure monitoring solutions. See the table below for detailed comparison of the two alternatives. Stay tuned - additional enhancements to metric alerts are coming in future releases! Feature Azure Prometheus rule groups Query-based metric alerts Alert rule management Part of a rule group resource Independent Azure resource Supported metrics Metrics in AMW (Managed Prometheus) Metrics in AMW (Managed Prometheus, OTel metrics) Condition logic PromQL-based query PromQL-based query Aggregation & transformation Full PromQL support Full PromQL support Scope Workspace-wide Resource-centric or workspace-wide Alerting at scale Not supported Subscription level, Resource-group level Cross-resource conditions Supported Supported RBAC granularity Workspace level Resource or workspace level Managed identity support Not supported Supported Notification customization Supported - Prometheus labels and annotations Advanced - dynamic custom properties, custom email subject Getting Started If you have an Azure Monitor workspace containing Prometheus or OpenTelemetry metrics, you can create query-based metric alert rules today. Rules can be created and managed using the Azure Portal, ARM templates, or Azure REST API. For details, visit Azure Monitor documentation.
Accelerating SCOM to Azure Monitor Migrations with Automated Analysis and ARM Template Generation
Accelerating SCOM to Azure Monitor Migrations with Automated Analysis and ARM Template Generation Azure Monitor has become the foundation for modern, cloud-scale monitoring on Azure. Built to handle massive volumes of telemetry across infrastructure, applications, and services, it provides a unified platform for metrics, logs, alerts, dashboards, and automation. As organizations continue to modernize their environments, Azure Monitor is increasingly the target state for enterprise monitoring strategies. With Azure Monitor increasingly becoming the destination platform, many organizations face a familiar challenge: migrating from System Center Operations Manager (SCOM). While both platforms serve the same fundamental purpose—keeping your infrastructure healthy and alerting you to problems—the migration path isn’t always straightforward. SCOM Management Packs contain years of accumulated monitoring logic: performance thresholds, event correlation rules, service discoveries, and custom scripts. Translating all of this into Azure Monitor’s paradigm of Log Analytics queries, alert rules, and Data Collection Rules can be a significant undertaking. To help with this challenge, members of the community have built and shared a tool that automates much of the analysis and artifact generation. The community-driven SCOM to Azure Monitor Migration Tool accepts Management Pack XML files and produces several outputs designed to accelerate migration planning and execution. The tool parses the Management Pack structure and identifies all monitors, rules, discoveries, and classes. Each component is analyzed for migration complexity: some translate directly to Azure Monitor equivalents, while others require custom implementation or may not have a direct equivalent. Results are organized into two clear categories: Auto-Migrated Components – Covered by the generated templates and ready for deployment Requires Manual Migration – Components that need custom implementation or review Instead of manually authoring Azure Resource Manager templates, the tool generates deployable infrastructure-as-code artifacts, including: Scheduled Query Alert rules mapped from SCOM monitors and rules Data Collection Rules for performance counters and Windows Events Custom Log DCRs for collecting script-generated log files Action Groups for notification routing Log Analytics workspace configuration (for new environments) For streamlined deployment, the tool offers a combined ARM template that deploys all resources in a single operation: Log Analytics workspace (create new or connect to an existing workspace) Action Groups with email notification All alert rules Data Collection Rules Monitoring Workbook One download, one deployment command — with configurable parameters for workspace settings, notification recipients, and custom log paths. The tool generates an Azure Monitor Workbook dashboard tailored to the Management Pack, including: Performance counter trends over time Event monitoring by severity with drill-down tables Service health overview (stopped services) Active alerts summary from Azure Resource Graph This provides immediate operational visibility once the monitoring configuration is deployed. Each migrated component includes the Kusto Query Language (KQL) equivalent of the original SCOM monitoring logic. These queries can be used as-is or refined to match environment-specific requirements. The workflow is designed to reduce the manual effort involved in migration planning: Export your Management Pack XML from SCOM Upload it to the tool Review the analysis — components are separated into auto-migrated and requires manual work Download the All-in-One ARM template (or individual templates) Customize parameters such as workspace name and action group recipients Deploy to your Azure subscription For a typical Management Pack, such as Windows Server Active Directory monitoring, you may see 120+ components that can be migrated directly, with an additional 15–20 components requiring manual review due to complex script logic or SCOM-specific functionality. The tool handles straightforward translations well: Performance threshold monitors become metric alerts or log-based alerts Windows Event collection rules become Data Collection Rule configurations Service monitors become scheduled query alerts against Heartbeat or Event tables Components that typically require manual attention: Complex PowerShell or VBScript probe actions Monitors that depend on SCOM-specific data sources Correlation rules spanning multiple data sources Custom workflows with proprietary logic The tool clearly identifies which category each component falls into, allowing teams to plan their migration effort with confidence. A Note on Validation This is a community tool, not an officially supported Microsoft product. Generated artifacts should always be reviewed and tested in a non-production environment before deployment. Every environment is different, and the tool makes reasonable assumptions that may require adjustment. Even so, starting with structured ARM templates and working KQL queries can significantly reduce time to deployment. Try It Out The tool is available at https://tinyurl.com/Scom2Azure.Upload a Management Pack, review the analysis, and see what your migration path looks like.
Observability for the Age of Generative AI
Every generation of computing brings new challenges in how we monitor and trust our systems. With the rise of Generative AI, applications are no longer static code—they’re living systems that plan, reason, call tools, and make choices dynamically. Traditional observability, built for servers and microservices, simply can’t tell you when an AI agent is correct, safe, or cost-efficient. We’re reimagining observability for this new world. At Ignite, we introduced the next wave of Azure Monitor and AI Foundry integration—purpose-built for GenAI apps and agents. End-to-End GenAI Observability Across the AI Stack Customers can see not just whether their systems are up or fast, but also whether their agent responses are accurate. Azure Monitor, in partnership with Foundry, unifies agent telemetry with infrastructure, application, network, and hardware signals—creating a true end-to-end view that spans AI agents, the services they call, and the compute they run on. New capabilities include: Agent Overview Dashboard in Grafana and Azure – Gain a unified view of one or more GenAI agents, including success rate, grounding quality, safety violations, latency, and cost per outcome. Customize dashboards in Grafana or Azure Monitor Workbooks to detect regressions instantly after a model or prompt change—and understand how those changes affect user experience and spend. AI-Tailored Trace View – Follow every AI decision as a readable story: plan → reasoning → tool calls → guardrail checks. Identify slow or unsafe steps in seconds, without sifting through thousands of spans. AI-Aware Trace Search by Attributes – Search, sort, and filter across millions of runs using GenAI-specific attributes like model ID, grounding score, or cost. Find the “needle” in your GenAI haystack in a single query. Foundry Low-Code Agent Monitoring – Agents created through Foundry’s visual, low-code interface are now automatically observable. Without writing a single line of code, you can track reliability, safety, and cost metrics from day one. Full-Stack Visibility Across the AI Stack – All evaluations, traces, and red-teaming results are now published to Azure Monitor, where agent signals correlate seamlessly with infrastructure KPIs and application telemetry to deliver a unified operational view. Check out our get started documentation. Powered by OpenTelemetry Innovation This work builds directly on the new OpenTelemetry extensions announced in our recent Azure AI Foundry blog post. Microsoft is helping define the OpenTelemetry agent specification, extending it to capture multi-agent orchestration traces, LLM reasoning context, and evaluation signals—enabling interoperability across Azure Monitor, AI Foundry, and partner tools such as Datadog, Arize, and Weights & Biases. By building on open standards, customers gain consistent visibility across multi-cloud and hybrid AI environments—without vendor lock-in. Built for Enterprise Scale and Trust With open standards and deep integration between Azure Monitor and AI Foundry, organizations can now apply the same discipline they use for traditional applications to their GenAI workloads, complete with compliance, cost governance, and quality assurance. GenAI is redefining what it means to operate software. With these innovations, Microsoft is giving customers the visibility, control, and confidence to operate AI responsibly, at enterprise scale.Generally Available - Azure Monitor Private Link Scope (AMPLS) Scale Limits Increased by 10x!
Introduction We are excited to announce the General Availability (GA) of Azure Monitor Private Link Scope (AMPLS) scale limit increase, delivering 10x scalability improvements compared to previous limits. This enhancement empowers customers to securely connect more Azure Monitor resources via Private Link, ensuring network isolation, compliance, and Zero Trust alignment for large-scale environments. What is Azure Monitor Private Link Scope (AMPLS)? Azure Monitor Private Link Scope (AMPLS) is a feature that allows you to securely connect Azure Monitor resources to your virtual network using private endpoints. This ensures that your monitoring data is accessed only through authorized private networks, preventing data exfiltration and keeping all traffic inside the Azure backbone network. AMPLS – Scale Limits Increased by 10x in Public Cloud & Sovereign Cloud (Fairfax/Mooncake) - Regions In a groundbreaking development, we are excited to share that the scale limits for Azure Monitor Private Link Scope (AMPLS) have been significantly increased by tenfold (10x) in Public & Sovereign Cloud regions as part of the General Availability! This substantial enhancement empowers our customers to manage their resources more efficiently and securely with private links using AMPLS, ensuring that workload logs are routed via the Microsoft backbone network. What’s New? 10x Scale Increase Connect up to 3,000 Log Analytics workspaces per AMPLS (previously 300) Connect up to 10,000 Application Insights components per AMPLS (previously 1,000) 20x Resource Connectivity Each Azure Monitor resource can now connect to 100 AMPLS resources (previously 5) Enhanced UX/UI Redesigned AMPLS interface supports loading 13,000+ resources with pagination for smooth navigation Private Endpoint Support Each AMPLS object can connect to 10 private endpoints, ensuring secure telemetry flows Why It Matters Top Azure Strategic 500 customers, including major Telecom service providers and Banking & Financial Services organizations, have noted that previous AMPLS limits did not adequately support their increasing requirements. The demand for private links has grown 3–5 times over existing capacity, affecting both network isolation and integration of essential workloads. This General Availability release resolves these issues, providing centralized monitoring at scale while maintaining robust security and performance. Customer Stories Our solution now enables customers to scale their Azure Monitor resources significantly, ensuring seamless network configurations and enhanced performance. Customer B - Case Study: Leading Banking & Financial Services Customer Challenge: The Banking Customer faced complexity in delivering personalized insights due to intricate workflows and content systems. They needed a solution that could scale securely while maintaining compliance and performance for business-critical applications. Solution: The Banking Customer has implemented Microsoft Private Links Services (AMPLS) to enhance the security and performance of financial models for smart finance assistants, leading to greater efficiency and improved client engagement. To ensure secure telemetry flow and compliance, the banking customer implemented Azure Monitor with Private Link Scope (AMPLS) and leveraged the AMPLS Scale Limit Increase feature. Business Impact: Strengthened security posture aligned with Zero Trust principles Improved operational efficiency for monitoring and reporting Delivered a future-ready architecture that scales with evolving compliance and performance demands Customer B - Case Study: Leading Telecom Service Provider - Scaling Secure Monitoring with AMPLS Architecture: A Leading Telecom Service Provider employs a highly micro-segmented design where each DevOps team operates in its own workspace to maximize security and isolation. Challenge: While this design strengthens security, it introduces complexity for large-scale monitoring and reporting due to physical and logical limitations on Azure Monitor Private Link Scope (AMPLS). Previous scale limits made it difficult to centralize telemetry without compromising isolation. Solution: The AMPLS Scale Limit Increase feature enabled the Telecom Service Provider to expand Azure Monitor resources significantly. Monitoring traffic now routes through Microsoft’s backbone network, reducing data exfiltration risks and supporting Zero Trust principles. Impact & Benefits Scalability: Supports up to 3,000 Log Analytics workspaces and 10,000 Application Insights components per AMPLS (10× increase). Efficiency: Each Azure Monitor resource can now connect to 100 AMPLS resources (20× increase). Security: Private connectivity via Microsoft backbone mitigates data exfiltration risks. Operational Excellence: Simplifies configuration for 13K+ Azure Monitor resources, reducing overhead for DevOps teams. Customer Benefits & Results Our solution significantly enhances customers’ ability to manage Azure Monitor resources securely and at scale using Azure Monitor Private Link Scope (AMPLS). Key Benefits Massive Scale Increase 3,000 Log Analytics workspaces (previously 300) 10,000 Application Insights components (previously 1,000) Each AMPLS object can now connect to: Azure Monitor resources can now connect with up to 100 AMPLS resources (20× increase). Broader Resource Support - Supported resource types include: Data Collection Endpoints (DCE) Log Analytics Workspaces (LA WS) Application Insights components (AI) Improved UX/UI Redesigned AMPLS interface supports loading 13,000+ Azure Monitor resources with pagination for smooth navigation. Private Endpoint Connectivity Each AMPLS object can connect to 10 private endpoints, ensuring secure telemetry flows. Resources: Explore the new capabilities of Azure Monitor Private Link Scope (AMPLS) and see how it can transform your network isolation and resource management. Visit our Azure Monitor Private Link Scope (AMPLS) documentation page for more details and start leveraging these enhancements today! For detailed information on configuring Azure Monitor private link scope and azure monitor resources, please refer to the following link: Use Azure Private Link to connect networks to Azure Monitor - Azure Monitor | Microsoft Learn Design your Azure Private Link setup - Azure Monitor | Microsoft Learn Configure your private link - Azure Monitor | Microsoft LearnAdvancing Full-Stack Observability with Azure Monitor at Ignite 2025
New AI-powered innovations in the observability space First, we’re excited to usher in the era of agentic cloud operations with Azure Copilot agents. At Ignite 2025, we are announcing the preview of the Azure Copilot observability agent to help you enhance full-stack troubleshooting. Formerly “Azure Monitor investigate”, the observability agent streamlines troubleshooting across application services and resources such as AKS and VMs with advanced root cause analysis in alerts, the portal, and Azure Copilot (gated preview). By automatically correlating telemetry across resources and surfacing actionable findings, it empowers teams to resolve issues faster, gain deeper visibility, and collaborate effectively. Learn more here about the observability agent and learn about additional agents in Azure Copilot here. Additionally, with the new Azure Copilot, we are streamlining agentic experiences across Azure. From operations center in the Azure portal, you can get a single view to navigate, operate and optimize your environments and invoke agents in your workflows. You also get suggested top actions within the observability blade of operations center to prioritize, diagnose and resolve issues with support from the observability agent. Learn more here. In the era of AI, more and more apps are now AI apps. That’s why we’re enhancing our observability capabilities for GenAI and agents: Azure Monitor brings agent-level visibility and control into a single experience in partnership with Observability in Foundry Control Plane through a new agent details view (public preview) showcasing success metrics, quality indicators, safety checks, and cost insights in one place. Simplified tracing also transforms every agent run into a reasonable, plan-and-act narrative for faster understanding. On top of these features, the new smart trace search enables faster detection of anomalies—such as policy violations, unexpected cost spikes, or model regressions—so teams can troubleshoot and optimize with confidence. These new agentic experiences build upon a solid observability foundation provided by Azure Monitor. Learn more here. We’re making several additional improvements in Azure Monitor: Simplified Onboarding & More Centralized Visibility Streamlined onboarding: Azure Monitor now offers streamlined onboarding for VMs, containers, and applications with sensible defaults and abstraction layers. This means ITOps teams can enable monitoring across environments in minutes, not hours. Previously, configuring DCRs and linking Log Analytics workspaces was a multi-step process; now, you can apply predefined templates and scale monitoring across hundreds of VMs faster than before. Centralized dashboards: A new monitor overview page in operations center consolidates top suggested actions and Azure Copilot-driven workflows for rapid investigation. Paired with the new monitoring coverage page (public preview) in Azure Monitor, ITOps can quickly identify gaps based on Azure Advisor recommendations, enable VM Insights and Container Insights at scale, and act on monitoring recommendations—all from a single pane of glass. Learn more here. Richer visualizations: Azure Monitor dashboards with Grafana are now in GA, delivering rich visualizations and data transformation capabilities on Prometheus metrics, Azure resource metrics, and more. Learn more here. Cloud to edge visibility: With expanded support for Arc-enabled Kubernetes with OpenShift and Azure Red Hat OpenShift in Container Insights and Managed Prometheus, Azure Monitor offers an even more complete set of services for monitoring the health and performance of different layers of Kubernetes infrastructure and the applications that depend on it. Learn more here. Advanced Logs, Metrics, and Alert Management Logs & metrics innovations: Azure Monitor now supports the log filtering and transformation (GA), as well as the emission of logs to additional destinations (public preview) such as Azure Data Explorer and Fabric—unlocking real-time analytics and more seamless data control. Learn more here. More granular access for managing logs: Granular RBAC for Log Analytics workspaces ensures compliance and least privilege principles across teams, now in general availability. Learn more here. Dynamic thresholds for log search alerts (public preview): Now you can apply the advanced machine learning methods of dynamic threshold calculations to enhance monitoring with log search alerts. Learn more here. Query-based metric alerts (public preview): Get rich and flexible query-based alerting on Prometheus, VM Guest OS, and custom OTel metrics to reduce complexity and unblock advanced alerting scenarios. Learn more here. OpenTelemetry Ecosystem Expansion Azure Monitor doubles down on our commitment to OpenTelemetry with expanded support for monitoring applications deployed to Azure Kubernetes Service (AKS) by using OTLP for instrumentation and data collection. New capabilities include: Auto-instrumentation with the Azure Monitor OpenTelemetry distro for Java and NodeJS apps on AKS (public preview): this reduces friction for teams adopting OTel standards and ensures consistent telemetry across diverse compute environments. Auto-configuration for apps on AKS in any language already instrumented with the open-source OpenTelemetry SDK to emit telemetry to Azure Monitor. Learn more here. Additionally, we are making it easier to gain richer and more consistent visibility across Azure VMs and Arc Servers with OpenTelemetry visualizations, offering standardized system metrics, per-process insights, and extensibility to popular workloads on a more cost-efficient and performant solution. Learn more here. Next Steps These innovations redefine observability from cloud to edge—simplifying onboarding, accelerating troubleshooting, and embracing open standards. For ITOps and DevOps teams, this means fewer blind spots, faster MTTR, and improved operational resilience. Whether you’re joining us at Microsoft Ignite 2025 in-person or online, there are plenty of ways to connect with the Azure Monitor team and learn more: Attend breakout session BRK149 for a deep dive into Azure Monitor’s observability capabilities and best practices for optimizing cloud resources. Attend breakout session BRK145 to learn more about how agentic AI can help you streamline cloud operations and management. Attend breakout session BRK190 to learn about how Azure Monitor and Microsoft Foundry deliver an end-to-end observability experience for your AI apps and agents. Join theater demo THR735 to see a live demo on monitoring AI agents in production. Connect with Microsoft experts at the Azure Copilot, Operations, and Management expert meet-up booth to get your questions answered.General Availability: Granular RBAC in Azure Monitor Logs
We’re excited to announce the general availability of Granular Role-Based Access Control (RBAC) in Azure Monitor Logs! This capability enables you to set fine-grained data access control at the row level, giving you more flexibility and security when managing log data. Back in May 2025, we introduced this feature in public preview. Today, it’s fully available and ready for production use What is Granular RBAC? Organizations often need to segregate and control access to data without trading off the benefits of a centralized logging platform. Granular RBAC builds on existing Azure RBAC capabilities for workspace and table-level access, allowing you to: Apply least privilege access at any level, workspace, table, or row level security. Maintain all your data in a single Log Analytics workspace. Separate data plane and control plane access using Azure Attribute-Based Access Control (ABAC) as part of your RBAC role assignments. With Granular RBAC, you can filter which data each user can view or query based on conditions you define such as organizational roles, geographic regions, or data sensitivity levels. What’s New? Broad Availability: Granular RBAC is now supported in Azure Public Cloud, Azure Government (GCC), and Azure China. New Built-in Role: The Log Analytics Data Reader role now fully supports Granular RBAC for an out-of-the-box experience. Learn more Get Started Learn more about Granular RBAC and how to set it up in Azure Monitor Logs We hope you enjoy this new addition to Azure Monitor Log Analytics.
Simplify Application Monitoring for AKS with Azure Monitor (Public Preview)
As cloud-native workloads scale, customers increasingly expect application and infrastructure observability to be unified, automated, and devops-friendly. Azure Monitor is advancing this vision with Application Monitoring for Azure Kubernetes Service (AKS). With seamless onboarding and troubleshooting experiences in the Azure Portal, now in Public Preview. This new capability brings first-class OpenTelemetry support, seamless onboarding from the AKS cluster blade, and auto-instrumentation and auto-configuration options that make it easier than ever to collect application performance data into Azure Monitor and Application Insights—without modifying application code or maintaining custom agents. Enable application monitoring for your AKS deployed apps directly from the Azure Portal in two steps: 1. Enable application monitoring for the AKS cluster in Monitor Settings 2. Choose the namespaces for application monitoring and configure namespace-wide onboarding to route application signals to an App Insights resource. Optionally, leverage Custom Resource Definitions (CRDs) for more granular enablement and per-deployment onboarding. Feature Highlights Auto-instrumentation Auto-instrument Java and NodeJS applications without code changes. This approach instruments workloads with the AzureMonitor OpenTelemetry distro and routes telemetry to Application Insights. Now available in both CLI and Azure portal for addon enablement and namespace configuration. Unified Monitoring and Troubleshooting Switch seamlessly between infrastructure and application layers with improved navigation between Container Insights and Application Insights, curated OpenTelemetry workbooks, and Azure-curated Grafana dashboards. When looking into your deployment controllers from Container Insights, you can also see the application performance metrics alongside to identify problematic requests or failures. From there, you can seamlessly transition over to your Application Insights to get a more detailed diagnosis. View your application performance next to your infrastructure metrics in Container Insights Full-Stack Dashboards with Grafana This new application monitoring capability becomes even more powerful when paired with Dashboards with Grafana for Azure Monitor. With curated, Azure-hosted Grafana dashboards built specifically for Application Insights and OpenTelemetry data, teams can extend their AKS application monitoring experience with rich, full-stack visualizations tailored for cloud-native workloads. Application monitoring dashboards available through Dashboards with Grafana These dashboards allow you to: Bring application traces, requests, dependencies, and exception data from Application Insights into Grafana dashboards optimized for app-centric troubleshooting. Correlate application performance with AKS infrastructure metrics, including node, pod, and container health, to rapidly identify cross-layer issues. Visualize OpenTelemetry signals flowing through Azure Monitor in a unified, standards-based format without needing to build dashboards from scratch. Customize and extend dashboards with your own OTel metrics or additional Application Insights dimensions for deeper app performance analytics. By combining Application Monitoring for AKS with Dashboards for Grafana, developers and operators gain a complete, end-to-end view of application behavior, making it faster and easier to diagnose issues, validate deployments, and understand the health of microservices running on AKS. Call to Action Start simplifying application observability today with Azure Monitor for AKS. Unify your metrics, logs, and traces in a single monitoring experience powered by OpenTelemetry and Azure Monitor. Explore the documentation and get started: https://learn.microsoft.com/azure/azure-monitor/app/kubernetes-codeless Learn more about our new features for OpenTelemetry in Azure Monitor: https://aka.ms/igniteotelblog
Troubleshoot with OTLP signals in Azure Monitor (Limited Public Preview)
As organizations increasingly rely on distributed cloud-native applications, the need for comprehensive standards-based observability has never been greater. OpenTelemetry (OTel) has emerged as the industry standard for collecting and transmitting telemetry data, enabling unified monitoring across diverse platforms and services. Microsoft is among the top contributors to OpenTelemetry. Azure Monitor is expanding its support for the OTel standard with this preview, empowering developers and operations teams to seamlessly capture, analyze, and act on critical signals from their applications and infrastructure. With this limited preview (sign-up here), regardless of where your applications are running, you can channel the OpenTelemetry Protocol (OTLP) logs, metrics and traces to Azure Monitor directly. On Azure compute platforms, we have simpler collection orchestration that also unifies application and infrastructure telemetry collection with the Azure Monitor collection offerings for VM/VMSS or AKS. On Azure VMs/VMSS (or any Azure Arc supported compute), you can use the Azure Monitor Agent (AMA) that you are already using to collect infrastructure logs. On AKS, the Azure Monitor add-ons that orchestrate Container Insights and managed Prometheus, will also auto configure the collection of OTLP signals from your applications (or auto-instrument with Azure Monitor OTel Distro for supported languages). On these platforms or anywhere else, you can choose to use OpenTelemetry Collector, and channel the OTLP signals from your OTel SDK instrumented application directly to Azure Monitor cloud ingestion endpoints. OTLP metrics will be stored in Azure Monitor Workspace, a Prometheus metrics store. Logs and traces will be stored in Azure Monitor Log Analytics Workspace in an OTel semantic conventions-based schema. Application Insights experiences will light up, enabling all distributed tracing and troubleshooting experiences powered by Azure Monitor, as well as out of the box Dashboards with Grafana from the community. With this preview, we are also extending the support for auto-instrumentation of applications on AKS to .NET and Python applications and introducing OTLP metrics collection from all auto-instrumented applications (Java/Node/.NET/Python). Sign-up for the preview here: https://aka.ms/azuremonitorotelpreview.
