Public Preview: Azure Monitor pipeline transformations
Overview The Azure Monitor pipeline extends the data collection capabilities of Azure Monitor to edge and multi-cloud environments. It enables at-scale data collection (data collection over 100k EPS), and routing of telemetry data before it's sent to the cloud. The pipeline can cache data locally and sync with the cloud when connectivity is restored and route telemetry to Azure Monitor in cases of intermittent connectivity. Learn more about this here - Configure Azure Monitor pipeline - Azure Monitor | Microsoft Learn Why transformations matter Lower Costs: Filter and aggregate before ingestion to reduce ingestion volume and in turn lower ingestion costs Better Analytics: Standardized schemas mean faster queries and cleaner dashboards. Future-Proof: Built-in schema validation prevents surprises during deployment. Azure Monitor pipeline solves the challenges of high ingestion costs and complex analytics by enabling transformations before ingestion, so your data is clean, structured, and optimized before it even hits your Log Analytics Workspace. Check out a quick demo here - If the player doesn’t load, open the video in a new window: Open video Key features in public preview 1. Schema change detection One of the most exciting additions is schema validation for Syslog and CEF : Integrated into the “Check KQL Syntax” button in the Strato UI. Detects if your transformation introduces schema changes that break compatibility with standard tables. Provides actionable guidance: Option 1: Remove schema-changing transformations like aggregations. Option 2: Send data to a custom tables that support custom schemas. This ensures your pipeline remains robust and compliant with analytics requirements. For example, in the picture below, extending to new columns that don't match the schema of the syslog table throws an error during validation and asks the user to send to a custom table or remove the transformations. While in the case of the example below, filtering does not modify the schema of the data at all and so no validation error is thrown, and the user is able to send it to a standard table directly. 2. Pre-built KQL templates Apply ready-to-use templates for common transformations. Save time and minimize errors when writing queries. 3. Automatic schema standardization for syslog and CEF Automatically schematize CEF and syslog data to fit standard tables without any added transformations to convert raw data to syslog/CEF from the user. 4. Advanced filtering Drop unwanted events based on attributes like: Syslog: Facility, ProcessName, SeverityLevel. CEF: DeviceVendor, DestinationPort. Reduce noise and optimize ingestion costs. 5. Aggregation for high-volume logs Group events by key fields (e.g., DestinationIP, DeviceVendor) into 1-minute intervals. Summarize high-frequency logs for actionable insights. 6. Drop unnecessary fields Remove redundant columns to streamline data and reduce storage overhead. Supported KQL sunctions 1. Aggregation summarize (by), sum, max, min, avg, count, bin 2. Filtering where, contains, has, in, and, or, equality (==, !=), comparison (>, >=, <, <=) 3. Schematization extend, project, project-away, project-rename, project-keep, iif, case, coalesce, parse_json 4. Variables for Expressions or Functions let 5. Other Functions String: strlen, replace_string, substring, strcat, strcat_delim, extract Conversion: tostring, toint, tobool, tofloat, tolong, toreal, todouble, todatetime, totimespan Get started today Head to the Azure Portal and explore the new Azure Monitor pipeline transformations UI. Apply templates, validate your KQL, and experience the power of Azure Monitor pipeline transformations. Find more information on the public docs here - Configure Azure Monitor pipeline transformations - Azure Monitor | 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.Announcing Application Insights SDK 3.x for .NET
Microsoft remains committed to making OpenTelemetry the foundation of modern observability on Azure. Today, we’re excited to take the next step on that journey with a major release of the Application Insights SDK 3.x for .NET. Migrate to OpenTelemetry with a Major Version Bump With Application Insights SDK 3.x, developers can migrate to OpenTelemetry-based instrumentation with dramatically less effort. Until now, migrating from classic Application Insights SDK to the Azure Monitor OpenTelemetry Distro required a clean install and code updates. With this release, most customers can adopt OpenTelemetry simply by upgrading their SDK version. The new SDK automatically routes your classic Application Insights Track* APIs calls through a new mapping layer that emits OpenTelemetry signals under the hood. Why This Matters By upgrading, you gain: ✔ Vendor‑neutral OpenTelemetry APIs going forward You can immediately begin writing new code using OpenTelemetry APIs, ensuring future portability and alignment with industry standards. ✔ Access to the full OpenTelemetry ecosystem You can now easily plug in community instrumentation libraries and exporters. For example, collecting Redis Cache dependency data—previously not supported with Application Insights 2.x—becomes straightforward. ✔ Multi‑exporter support Export to Azure Monitor and another system (e.g., a SIEM or backend of your choice) simultaneously if your scenario requires it. What Still Requires Attention: Initializers and Processors One area where automatic migration is not possible is telemetry processors and telemetry initializers. These Application Insights extensibility points were extremely flexible, allowing custom property injection, filtering, or deletion logic. OpenTelemetry supports similar behavior, but through more structured concepts such as span processors. See here for a full list of breaking changes. On a positive note, these OpenTelemetry components generally deliver better performance and clearer behavior. Our documentation assists with migration, and we plan to release an MCP with guardrails to assist LLM in accurate coding. Keeping the essence of Azure Monitor Application Insights While OpenTelemetry encourages the use of the OpenTelemetry-Collector, we remain committed to preserving the simplicity that customers love about Azure Monitor Application Insights. The Azure Monitor OpenTelemetry Distro is all that’s required to get started. It’s just a single NuGet package and you configure it with a Connection String. Telemetry flows in minutes. No Collector is required unless you explicitly want one. We are able to achieve this with extensive built‑in sampling to manage cost and a trace‑preservation algorithm, so you see complete traces. This keeps the “just works” spirit of Azure Monitor Application Insights intact, while aligning with OpenTelemetry standards. Feedback If you encounter issues during the upgrade, please open a support ticket—we want the migration to be smooth. If you’d like to share feedback or engage directly with the product team, email us at otel@microsoft.com. This is not an official support channel, but we read every email and appreciate hearing feedback directly from you!
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.Announcing General Availability: Azure Monitor dashboards with Grafana
Continuing our commitment to open-source solutions, we are announcing the general availability of Azure Monitor dashboards with Grafana. This service offers a powerful solution for cloud-native monitoring and visualizing all your Azure data. Dashboards with Grafana enable you to create and edit Grafana dashboards directly in the Azure portal without additional cost and less administrative overhead compared to self-hosting Grafana or using managed Grafana services. Built-in Grafana controls and components allow you to apply a rich set of visualization panels and client-side transformations to Azure monitoring data to create custom dashboards. Start quickly with pre-built and community dashboards Dozens of pre-built Grafana dashboards for Azure Kubernetes Services, Application Insights, Storage Accounts, Cosmos DB, Azure PostgreSQL, OpenTelemetry metrics and dozens of other Azure resources are included and enabled by default. Additionally, you can import dashboards from thousands of publicly available Grafana community and open-source dashboards for the supported data sources: Prometheus, Azure Monitor (metrics, logs, traces, Azure Resource Graph), and Azure Data Explorer. Streamline monitoring with open-source compatibility and Azure enterprise capabilities Azure Monitor dashboards with Grafana are fully compatible with open-source Grafana dashboards and are portable across any Grafana instances regardless of where they are hosted. Furthermore, dashboards are native Azure resources supporting Azure RBAC to assign permissions, and automation via ARM and Bicep templates. Import, edit and create dashboards in 30+ Azure regions Choose from any language in the Azure Portal for your Grafana user interface Manage dashboard content as part of the ARM resource Automatically generate ARM templates to automate deployment and manage dashboards Take advantage of Grafana Explore and New Dashboards Leverage Grafana Explore to quickly create ad-hoc queries without modifying dashboards and add queries and visualizations to new or existing dashboards New out of the box dashboards for additional Azure resources: Additional Azure Kubernetes Service support including AKS Automatic and AKS Arc connected clusters Azure Container Apps monitoring dashboards Microsoft Foundry monitoring dashboards Azure Monitor Application Insights dashboards OpenTelemetry metrics Microsoft Agent Framework High Performance Computing dashboards with dedicated GPU monitoring When to step up to Azure Managed Grafana? If you store your telemetry data in Azure, Dashboards with Grafana in the Azure portal is a great way to get started with Grafana. If you have additional 3rd-party data sources, or need full enterprise capabilities in Grafana, you can choose to upgrade to Azure Managed Grafana, a fully managed hosted service for the Grafana Enterprise software. See a detailed solution comparison of Dashboards with Grafana and Azure Managed Grafana here. Get started with Azure Monitor dashboards with Grafana today.
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.
Introducing Monitoring Coverage: Assess and Improve Your Monitoring Posture at Scale
As organizations grow their Azure footprint, ensuring consistent monitoring coverage across resources becomes increasingly important. The new Monitoring Coverage (preview) feature in Azure Monitor provides a single, centralized experience to assess, configure at-scale, and enhance monitoring across your environment with ease. A unified view of your monitoring health Monitoring Coverage consolidates insights from Azure Advisor to highlight where monitoring can be improved. You can see which Azure resources already have basic out-of-box telemetry enabled and which could benefit from additional recommended settings, helping you close gaps in your observability strategy at scale. Key capabilities Comprehensive visibility: Get an overview of monitoring coverage across common Azure resource types. Actionable recommendations: Identify and apply Azure Advisor recommendations at-scale to strengthen your monitoring posture. Centralized configuration: Enable recommended monitoring settings for multiple resources from a single pane of glass. Detailed resource insights: Explore individual resource details to review active monitoring configurations and applicable recommendations. How to access In the Azure portal, open Azure Monitor. Under the Settings section of the left navigation, select Monitoring Coverage (preview). You can scope the view using standard Azure filters; Subscriptions, Resource groups, Tags, Locations, and Resource types, allowing you to focus on the resources you manage. Supported resource types During preview, Monitoring Coverage supports Virtual Machines (VMs) and Azure Kubernetes Service (AKS) clusters. Support for additional Azure services will roll out in future updates. Overview tab The Overview tab provides a snapshot of your overall monitoring landscape, showing which resources have: Basic monitoring: Default metrics and logs enabled upon creation. Enhanced monitoring: Microsoft-recommended configurations for deeper insights and improved observability. This view makes it easy to identify coverage gaps and take quick action to enable enhanced monitoring, which may incur additional cost depending on your configuration. Streamlined enablement experience When you choose to enable monitoring: The Enablement screen lists all resources included in the operation. You can deselect specific resources if needed. Selecting View details and configure allows customization by resource type—for example, selecting a Log Analytics workspace. The Review and Enable tab summarizes all changes before application. Once enabled, data typically begins flowing to the designated workspace within 30–60 minutes. During this preview, you can enable monitoring for up to 100 resources at a time, and an existing Log Analytics workspace or Azure Monitor Workspace is required. Monitoring Details page For a deeper look, the Monitoring Details page lets you: View resources as a list or group them by recommendation. Filter using standard Azure filters. See the Monitoring coverage column summarizing enabled recommendations and data collection rules. Enable individual monitoring settings directly from this view when managing resources one at a time. Share your feedback We’re actively evolving Monitoring Coverage based on user input. To share your feedback or suggest new capabilities, use the Feedback link at the top of the page in the Azure portal. Your insights will help shape the future of Azure Monitor. Try Monitoring Coverage (preview) today in the Azure portal to assess your observability coverage and take the next step toward proactive, consistent monitoring across your Azure environment.Comprehensive VM Monitoring with OpenTelemetry performance counters
Monitoring virtual machines often requires multiple tools and manual investigation. You may see high CPU or memory usage, but identifying the process responsible usually means signing in to the VM and running diagnostic commands. Azure Monitor already provides Guest OS performance monitoring through Log Analytics‑based metrics, trusted for its flexibility, deep integration, and advanced analytics, including custom performance counters, extended retention, and powerful KQL queries. Many customers use LA‑based metrics to correlate performance with other log data sources and build rich operational insights. Today, we’re excited to introduce a new preview capability: OpenTelemetry (OTel) Guest OS metrics for VMs and Arc servers, with metric data stored in the metrics-optimized Azure Monitor Workspace (AMW). OTel provides a standards‑based pipeline with a unified schema, richer system and process counters, and streamlined integration with open‑source and cloud‑native observability tooling. It’s designed for simpler onboarding, cost‑efficient metric storage, and more granular visibility into what’s happening inside the VM. What are OpenTelemetry Guest OS metrics OTel Guest OS metrics are system and process‑level performance counters collected from inside a VM. This includes CPU, memory, disk I/O, network, and per‑process details such as CPU percent, memory percent, uptime, and thread count. This level of visibility helps you diagnose issues without signing into the VM. Why They Matter Azure Monitor continues to support Guest OS metrics through Log Analytics, and you now have the option to use OTel‑based Guest OS metrics. OTel offers richer insights, faster query performance, and lower cost, and is a good fit when you want a modern, standards‑based pipeline with deeper system visibility. Key Benefits Benefit Description Unified data model Consistent metric names and schema across Windows and Linux for easier, reusable queries and dashboards Richer, simplified counters More system and process metrics (e.g., per‑process CPU, memory, disk I/O) and consolidation of legacy counters into clearer OTel metrics. Easy onboarding Collect OTel metrics with minimal setup. Flexible visualization Use the Azure portal, Metrics Explorer, or Azure Monitor Dashboards with Grafana. Cost‑efficient performance Store metrics in Azure Monitor Workspace instead of Log Analytics ingestion for lower cost and faster queries. When to use LA‑based metrics (GA) vs OTel‑based metrics (Preview) LA-based metrics (GA) OTel-based metrics (Preview) Custom performance counters or extended retention Advanced KQL analytics and log‑metric correlation A mature, fully supported pipeline for operational analytics A standards‑based, unified schema across platforms Easier onboarding and broader system/process coverage Cost‑efficient metric storage with improved query performance We recommend evaluating your requirements to determine which approach best fits your needs. LA-based metrics remain the foundation for customers who need advanced analytics and correlation, while OTel-based metrics open new possibilities for modern VM observability. Onboarding VMs to OpenTelemetry performance counters Onboarding your virtual machines and Arc servers to OpenTelemetry-based counters is now both cost-efficient and easier than ever. With the new onboarding experience, you can enable guest-level metrics using a lightweight, standards-based OTel pipeline with no complex setup required. These system-level counters are available at no additional cost and provide deep visibility into CPU, memory, disk, network, and process activity from inside the VM. Azure Monitor automatically configures your Data Collection Rules (DCRs) to route these OpenTelemetry counters through the Monitor pipeline, ensuring you get full monitoring coverage with minimal configuration. Additionally, you can also onboard your VMs at scale using the new Monitoring Coverage experience or Essential Machine Management (EMM). For teams managing large fleets of virtual machines, these capabilities turn onboarding into a one-click operation, eliminating the need to repeat manual steps for each machine. This is especially valuable in enterprises or environments with dynamic VM creation, where maintaining consistent visibility across every machine is critical for performance, compliance, and troubleshooting. After onboarding at scale, you can further customize your monitoring. By editing the Data Collection Rule (DCR) created during onboarding, you can collect additional metrics and logs, then automatically apply those updates across all VMs associated with that DCR. This allows you to extend monitoring coverage beyond the default counters and adapt to your observability as your environment evolves. New Capabilities Powered by OpenTelemetry New VM monitoring experience powered by OpenTelemetry (preview) We're excited to announce the public preview of the enhanced monitoring experience for Azure Virtual Machines (VMs) and Arc servers. This redesign brings comprehensive monitoring capabilities in a single, streamlined view, helping you more efficiently observe, diagnose, and optimize your virtual machines. The new experience offers two levels of insight within one unified interface: Basic view (Host OS based): Available for all Azure VMs with no configuration required. This view surfaces key host level metrics including CPU, disk, and network performance for quick health checks. Detailed view (Guest OS based): Requires a simple onboarding step and is available at no additional cost. Azure Monitor already provides a GA detailed view powered by Log Analytics based Guest OS metrics, and this remains fully supported. This preview option is powered by OTel Guest OS metrics to provide expanded metric coverage and the new, streamlined monitoring experience introduced above Detailed view (Guest OS based with OTel) and enhanced monitoring experience for VMs You can access the new experience directly in the Azure portal under Virtual Machine → Monitoring → Insights. Building Custom Dashboards with Azure Monitor Dashboards in Grafana Azure Monitor Dashboards with Grafana lets you build custom visualizations on top of OTel Guest OS metrics. In addition to the out-of-the-box VM monitoring experience, you can create tailored dashboards to analyze the specific system or process-level signals that matter most to your workloads. For example, you can build a dashboard that breaks down CPU, memory, disk, and network usage at the process level. This helps you quickly identify unusual behavior or resource hotspots without signing in to the VM. Learn more. Query-based metric alerts (preview) Azure Monitor now supports PromQL-based metric alerts for OTel metrics stored in Azure Monitor Workspace, enabling flexible and powerful query-driven alerting. For example, you can configure an alert to notify you when a specific process shows unusual CPU usage, allowing you to detect issues earlier and take action before they impact users. PromQL based metric alert that triggers when the backupdatawarehouse.exe process exceeds 80% memory usage Get Started Explore the new OpenTelemetry-powered experiences today: Get started with VM Monitoring (Preview) Use Azure Monitor Dashboards with Grafana Query Based Metric Alerts Overview (Preview) We are also starting a limited public preview of application monitoring with OpenTelemetry signal collection from Azure VMs, VMSS and Arc Server. Learn more. Together, these previews mark a major step toward a unified and open monitoring platform designed to make observability simpler, faster, and aligned with open standards across every layer of your environment.
