Connect Metrics to Traces with Exemplars in Azure Monitor
Following Microsoft’s recent GA announcement for OpenTelemetry (OTel) support, we are excited to announce support for Exemplars for customers instrumenting metrics with Prometheus or OpenTelemetry and traces using OpenTelemetry, enhancing Azure Monitor’s integrated observability experience for cloud-native applications. Modern cloud-native applications generate enormous volumes of telemetry. Metrics help teams detect that something is wrong, but traces explain why. Exemplars bridge these two worlds by attaching trace references directly to metric data points, making it dramatically easier to pivot from a spike in latency or errors to the exact distributed trace responsible for the issue. With Azure Monitor, customers can now ingest metrics with exemplars and visualize them in Azure Managed Grafana. This enables seamless correlation between metrics and traces, helping engineering teams troubleshoot issues faster and reduce mean time to resolution (MTTR). Why Exemplars Matter Traditional monitoring workflows often require users to manually correlate data across multiple systems. Exemplars simplify this workflow by embedding trace context directly into metric samples. For example, if a latency metric spikes at a specific timestamp, the exemplar associated with that data point can link directly to the distributed trace responsible for the outlier. This provides several benefits: Faster root cause analysis Quicker transition from aggregate metrics to request-level details Simplified debugging workflows for SRE and platform teams Better observability experiences for microservices and distributed applications Unified Observability with Azure Monitor With Azure Monitor and Azure Managed Grafana, you can now: Ingest OTLP or Prometheus metrics with exemplars into Azure Monitor Workspace Store and analyze traces in Azure Monitor Application Insights Visualize exemplar markers directly in Grafana charts Navigate from a metric spike to the exact distributed trace associated with that data point By combining these signals in a single observability platform, organizations can correlate infrastructure health, application behavior, and request traces without context switching between tooling. How It Works Once metrics, exemplars, and traces are ingested into Azure Monitor, Azure Managed Grafana can consume exemplar information from the configured Prometheus data source. When exemplars are enabled in Grafana dashboards, users will see markers associated with individual metric data points. Selecting an exemplar opens the associated trace in Azure Monitor, providing end-to-end diagnostic context. Getting Started Setup data ingestion: Instrument your application to emit OpenTelemetry traces, OpenTelemetry or Prometheus metrics with exemplars, and enable ingestion of the same to Azure Monitor using OpenTelemetry Collector. Follow the instructions in Ingest OTLP Data into Azure Monitor with OTel Collector - Azure Monitor | Microsoft Learn. After this step, you will have the Log Analytics Workspace, Azure Monitor Workspace and Application Insights resources all set up to store the telemetry data. Create an Azure Managed Grafana instance and connect it with the Azure Monitor Workspace by navigating to your Azure Monitor Workspace in the Azure portal and then clicking on “Linked Grafana workspaces”. To learn more, see Manage an Azure Monitor workspace - Azure Monitor | Microsoft Learn Optionally, enable Azure Managed Prometheus on your AKS cluster or use remote-write and configure it to use the same Azure Monitor Workspace to centralize infrastructure and application metrics. Enable Exemplars in Azure Managed Grafana: After setting up the data ingestion, ensure that logs and traces are flowing into Log Analytics Workspace, and metrics are flowing into Azure Monitor Workspace. Step 1: Enable Exemplars on Prometheus Data Source in Azure Managed Grafana Navigate to Connections -> Data Sources in Azure Managed Grafana. Since you have connected Azure Managed Grafana to Azure Monitor Workspace, you will see the data source (Managed_Prometheus_<AMW-Name>) already configured. If the data source is not configured, follow the steps here to add your Azure Monitor Workspace as a data source. Open the data source configuration. Click Add Exemplars to enable exemplar support. Step 2: Configure Trace Linking with Azure Monitor In the exemplar configuration section, toggle Internal Link to On. Select Azure Monitor as the data source. In the Label Name, enter the name of the field in the labels object that should be used to get the trace id, eg. trace_id. Click Save & Test. This configuration enables direct navigation from exemplar markers in Grafana charts to the associated traces stored in Azure Monitor. Azure Managed Grafana also supports trace correlation from other solutions like Jaeger etc. To use your trace solution, use the appropriate links. Step 3: Enable Exemplars in Dashboards Navigate to a Grafana dashboard that uses your configured Prometheus data source. Open the panel options for a metrics chart. Toggle Exemplars to On. Once enabled, exemplar markers will appear on supported metric visualizations. Clicking on it will show exemplar details along with an option to open the corresponding distributed trace in Azure Monitor. To learn more, visit https://aka.ms/azmon-exemplarsDirect OpenTelemetry ingestion into Azure Monitor is now generally available
OpenTelemetry is powering a new era of observability. Built on open standards, designed for portability, and made for developers who want flexibility without compromise. And now, you can send OpenTelemetry logs, metrics, and traces straight into Azure Monitor OTLP endpoints and data storage. This capability is generally available, production-ready, and built to scale from day one. With direct OTLP ingestion, you can keep your existing OpenTelemetry instrumentation and OpenTelemetry collector pipelines while sending telemetry to Azure Monitor for investigation in Application Insights, analysis in Log Analytics, Prometheus metric storage and visualization in Grafana. What’s now generally available Direct OTLP ingestion into Azure Monitor for logs, metrics, and traces. Production-ready onboarding for deploying data collection rules and endpoints. Application Insights experiences for distributed tracing, performance investigation, and troubleshooting powered by OTLP data. Grafana dashboards ready-to-use for visualizing OpenTelemetry signals. Prometheus data storage and query language for metrics OpenTelemetry semantic conventions for logs and traces, so data lands in a familiar standards-based schema. How to send OTLP to Azure Monitor Instrument your application with OpenTelemetry using the open-source SDKs and configure OTLP export to an OpenTelemetry Collector. Configure Azure Monitor OTLP ingestion by using an Application Insights resource with OTLP support, which sets up the required Azure Monitor resources and investigation experiences or manually create the required resources. Export traces, metrics, and logs directly to Azure Monitor from the OpenTelemetry Collector using the built-in OTLP over HTTP exporter. Get started Where your telemetry lands Azure Monitor brings these signals together so your teams can triage and troubleshoot root cause faster without modifying code and instrumentation. Metrics are stored in an Azure Monitor Workspace, a Prometheus metrics store. Logs and traces are stored in a Log Analytics workspace using an OpenTelemetry semantic conventions–based schema. Application Insights lights up distributed tracing and end-to-end performance investigations. Pre-built Grafana dashboards for OpenTelemetry metrics are available directly in the Azure portal alongside Application Insights. Why it matters Standardize once: Instrument with OpenTelemetry and keep your instrumentation vendor neutral and keep your telemetry portable. Reduce overhead: Fewer bespoke exporters and pipelines to maintain. Stick to OTLP for all cases. Debug faster: Correlate metrics, logs, and traces to get from reported issues to root cause with less guesswork. Observe with confidence: Use dashboards and tracing views that are ready on day one. Next step: Try OTLP export from your environment to Azure Monitor, then validate end-to-end signal flow with Application Insights and Grafana dashboards. Get startedTroubleshoot with OpenTelemetry in Azure Monitor - Public Preview
OpenTelemetry is fast becoming the industry standard for modern telemetry collection and ingestion pipelines. With Azure Monitor’s new OpenTelemetry Protocol (OTLP) support, you can ship logs, metrics, and traces from wherever you run workloads to analyze and act on your observability data in one place. What’s in the preview Direct OTLP ingestion into Azure Monitor for logs, metrics, and traces. Automated onboarding for AKS workloads. Application Insights on OTLP for distributed tracing, performance and troubleshooting experiences. Pre-built Grafana dashboards to visualize signals quickly. Prometheus for metric storage and query. OpenTelemetry semantic conventions for logs and traces, so your data lands in a familiar standard-based schema. How to send OTLP to Azure Monitor: pick your path AKS: Auto-instrument Java and Node.js workloads using the Azure Monitor OpenTelemetry distro, or auto-configure any OpenTelemetry SDK-instrumented workload to export OTLP to Azure Monitor. Get started Limited preview: Auto-instrumentation for .NET and Python is also available. Get started VMs/VM Scale Sets (and Azure Arc-enabled compute): Use the Azure Monitor Agent (AMA) to receive OTLP from your apps and export it to Azure Monitor. Get started Any environment: Use the OpenTelemetry Collector to receive OTLP signals and export directly to Azure Monitor cloud ingestion endpoints. Get started Under the hood: where your telemetry lands Metrics: Stored in an Azure Monitor Workspace, a Prometheus metrics store. Logs + traces: Stored in a Log Analytics workspace using an OpenTelemetry semantic conventions–based schema. Troubleshooting: Application Insights lights up distributed tracing and end-to-end performance investigations, backed by Azure Monitor. Why it matters Standardize once: Instrument with OpenTelemetry and keep your telemetry portable. Reduce overhead: Fewer bespoke exporters and pipelines to maintain. Debug faster: Correlate metrics, logs, and traces to get from alert to root cause with less guesswork. Observe with confidence: Use dashboards and tracing views that are ready on day one. Next step: Try the OTLP preview in your environment, then validate end-to-end signal flow with Application Insights and Grafana dashboards. Learn MoreCopy dashboards from Dashboards with Grafana to Azure Managed Grafana
Azure Monitor Dashboards with Grafana provides an in‑portal Grafana experience optimized for Azure Monitor and managed Prometheus data. For many teams, that simplicity is exactly what they need. As observability practices mature, teams often need more than visualization: broader data source support, stronger security controls, and advanced workflows like Azure Managed Grafana MCP. Until now, moving dashboards from Dashboards with Grafana into Azure Managed Grafana often meant recreating them by hand or exporting JSON, extra friction when teams want to move faster. The new Copy to Managed Grafana experience removes that friction. Why a copy experience was needed Dashboards with Grafana and Azure Managed Grafana serve complementary roles. Dashboards with Grafana focuses on: Fast, zero‑setup visualization Tight integration with Azure Monitor and Prometheus An embedded experience directly inside the Azure portal Azure Managed Grafana extends that foundation with: Full Grafana workflows, including alerts, reporting, and automation Support for additional data sources and plugins Enterprise‑grade security features such as private endpoints and managed identity Cross‑team reuse through folders, APIs, and Role Based Access Controls Historically, teams that outgrew Dashboards with Grafana didn’t have a simple, in‑product way to bring their dashboards forward, so continuing in a more advanced Grafana environment required extra manual steps. The goal is simple: copy dashboards to Azure Managed Grafana as needs grow—while continuing to use Dashboards with Grafana for day‑to‑day work. Introducing “Copy to Managed Grafana” Customers can now copy dashboards from Dashboards with Grafana into Azure Managed Grafana directly from the Azure portal—without changing the original dashboard. This feature is: In‑context – start from your dashboard in Dashboards with Grafana Seamless – no exports or re‑creation Non‑disruptive – keep using the source dashboard while you adopt Managed Grafana The flow is straightforward: Select “Copy to Managed Grafana” from your dashboard in Dashboards with Grafana. This feature doesn’t work on built-in dashboards, so you would have to save a copy of built-in Dashboards before you can copy those. Choose an existing Azure Managed Grafana workspace or create a new one Complete the copy and continue working in a full Grafana environment, making data connections where needed Because it appears where teams already build dashboards, the option is easy to find when it becomes relevant. Advanced capabilities, like additional data sources, alerts, and folder organization, are configured after copying, so teams can adopt them when they’re ready. This keeps the transition predictable and avoids surprises. Dashboards with Grafana is the fastest way to visualize Azure Monitor data with Grafana. When teams need more control, scale, or extensibility, Azure Managed Grafana is the natural next step, without forcing you to stop using Dashboards with Grafana. Together, they form a single observability journey: Start quickly with Dashboards with Grafana Copy dashboards into Azure Managed Grafana when you need more capabilities Enjoy end to end observability within the Azure ecosystem as requirements evolve You don’t have to trade speed today for flexibility later. Learn more by reading the doc: Copy an Azure Monitor dashboard to Azure Managed Grafana - Azure Monitor | Microsoft LearnIntroducing Azure Managed Grafana 12
In this release, Azure Managed Grafana makes it easier to tighten access with current-user Entra authentication, speed up Azure Monitor logs exploration, and level up Prometheus and database monitoring experiences. What’s new in Azure Managed Grafana 12 Use current-user Entra authentication for supported Azure data sources to query with the signed-in user’s permissions. Analyze Azure Monitor logs faster with a new query builder and improved visualization and Explore experiences. Explore Prometheus metrics with improved drill-down, prefix and suffix filters, group-by label support, plus OpenTelemetry and native histogram support. Use updated, pre-built database monitoring dashboards for Azure PostgreSQL, Azure SQL, and SQL Managed Instance (SQL MI). Advanced authentication: query with current user’s Entra credentials Current-user Entra authentication is now available in Azure data sources. That means Grafana admins can configure supported data sources to re-use the logged-in user’s credentials when issuing queries. In practice, the signed-in user’s permissions define what data stores they can access, helping teams apply least-privilege access to each user while keeping the option to use Managed Identities and Service Principals in other data sources where that fits best. Supported data sources include: Azure Monitor Azure Data Explorer Azure Monitor Managed Service for Prometheus Faster log analysis: Click-to-build queries and smoother Explore If you live in Azure Monitor logs, this update is for you. Improvements to log visualization in the Logs visualization panel and Grafana Explore make it easier to filter and extract meaningful insights from Azure Monitor logs. There’s also a new Azure Monitor logs query builder, so you can create and refine queries with a few clicks instead of writing Kusto Query Language (KQL) by hand. Performance is significantly faster too. Grafana Explore can now query and render up to 30K log records at a time, so you get much faster load times, faster searches, and more responsive navigation through large log volumes. Prometheus query enhancements: drill down without the query gymnastics Users new to Prometheus get a smoother path to explore metrics and analyze time series. Metrics drill-down now includes sidebar filters for prefix/suffix so you can quickly narrow metrics by naming conventions, and group-by label support to build more context-rich groupings. This is a true queryless exploration of Azure Managed Prometheus metrics when you’re troubleshooting or just identifying what’s been collected. This release also adds OpenTelemetry & native histogram support, including an OTel mode to automate label-join complexities when querying OTLP metrics. New database monitoring dashboards Azure Managed Grafana now includes new versions of pre-built dashboards for monitoring Azure Database for PostgreSQL and Azure SQL Databases (Preview). For teams building on Azure-native databases, these updated dashboards can help you get to a useful baseline faster, so you spend less time wiring panels and more time acting on what the data is telling you. Getting started To try Grafana 12, you can create a new Azure Managed Grafana instance with Grafana 12 selected, or upgrade an existing instance from the Azure portal. From there, consider enabling current-user Entra authentication for supported Azure data sources, test the new Azure Monitor logs query builder in Explore for day-to-day investigations, and take the updated database dashboards for a spin if you run Azure PostgreSQL, Azure SQL, or SQL MI. Check out the doc for more information: Upgrade Azure Managed Grafana to Grafana 12 - Azure Managed Grafana.
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.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 Learn
Advancing 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.
