Troubleshoot 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

Diagram: Choose your ingestion path

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.
  

   

  Application Map on OpenTelemetry signals

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 More