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Copy file name to clipboardExpand all lines: articles/azure-monitor/app/distributed-tracing.md
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# What is Distributed Tracing?
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The advent of modern cloud and [microservices](https://azure.com/microservices) architectures has given rise to simple, independently deployable services that can help reduce costs while increasing availability and throughput. But while these movements have made individual services easier to understand as a whole, they’ve made overall systems more difficult to reason about and debug.
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The advent of modern cloud and [microservices](https://azure.com/microservices) architectures has given rise to simple, independently deployable services that can help reduce costs while increasing availability and throughput. But while these movements have made individual services easier to understand as a whole, they've made overall systems more difficult to reason about and debug.
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In monolithic architectures, we’ve gotten used to debugging with call stacks. Call stacks are brilliant tools for showing the flow of execution (Method A called Method B, which called Method C), along with details and parameters about each of those calls. This is great for monoliths or services running on a single process, but how do we debug when the call is across a process boundary, not simply a reference on the local stack?
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In monolithic architectures, we've gotten used to debugging with call stacks. Call stacks are brilliant tools for showing the flow of execution (Method A called Method B, which called Method C), along with details and parameters about each of those calls. This is great for monoliths or services running on a single process, but how do we debug when the call is across a process boundary, not simply a reference on the local stack?
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That’s where distributed tracing comes in.
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That's where distributed tracing comes in.
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Distributed tracing is the equivalent of call stacks for modern cloud and microservices architectures, with the addition of a simplistic performance profiler thrown in. In Azure Monitor, we provide two experiences for consuming distributed trace data. The first is our [transaction diagnostics](https://docs.microsoft.com/azure/application-insights/app-insights-transaction-diagnostics) view, which is like a call stack with a time dimension added in. The transaction diagnostics view provides visibility into one single transaction/request, and is helpful for finding the root cause of reliability issues and performance bottlenecks on a per request basis.
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With the proper Application Insights SDK installed and configured, tracing information is automatically collected for popular frameworks, libraries, and technologies by SDK dependency auto-collectors. The full list of supported technologies is available in [the Dependency auto-collection documentation](https://docs.microsoft.com/azure/application-insights/auto-collect-dependencies).
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In addition to the Application Insights SDKs, Application Insights also supports distributed tracing through [OpenCensus](https://opencensus.io/). OpenCensus is an open source, vendor-agnostic, single distribution of libraries to provide metrics collection and distributed tracing for services. It also enables the open source community to enable distributed tracing with popular technologies like Redis, Memcached, or MongoDB. [Microsoft collaborates on OpenCensus with several other monitoring and cloud partners](https://open.microsoft.com/2018/06/13/microsoft-joins-the-opencensus-project/).
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[Python (preview)](opencensus-python.md)
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[Python](opencensus-python.md)
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The OpenCensus website maintains API reference documentation for [Python](https://opencensus.io/api/python/trace/usage.html) and [Go](https://godoc.org/go.opencensus.io), as well as various different guides for using OpenCensus.
We're aware that several other community-supported SDKs exist. However, Azure Monitor only provides support when using the supported SDKs listed on this page. We’re constantly assessing opportunities to expand our support for other languages, so follow our [GitHub Announcements](https://github.com/microsoft/ApplicationInsights-Announcements/issues) page to receive the latest SDK news.
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We're aware that several other community-supported SDKs exist. However, Azure Monitor only provides support when using the supported SDKs listed on this page. We're constantly assessing opportunities to expand our support for other languages, so follow our [GitHub Announcements](https://github.com/microsoft/ApplicationInsights-Announcements/issues) page to receive the latest SDK news.
- The regional service URIs are based on the [SDK defaults](https://github.com/microsoft/ApplicationInsights-dotnet/blob/e50d569cebf485e72e98f4a08a0bc0e30cdf42bc/BASE/src/Microsoft.ApplicationInsights/Extensibility/Implementation/Endpoints/Constants.cs#L6) and will connect to the public global Azure:
- The regional service URIs are based on provided endpoint suffix:
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- Ingestion: https://dc.ai.contoso.com
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In this example, this connection string specifies explicit overrides for every service. The SDK will use the exact endpoints provided without modification.
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