Matt McSpiritHost
It's a multi-tier app with a modern microservice backend hosted on Kubernetes with a SQL database, Redis cache, and more.

And with the new Foundry capabilities, I can also observe how it's performing from operational metrics, including agent runs, GenAI errors, tool calls, underlying models, and token consumption.

And scrolling up, we can even view traces with GenAI errors and see a list of traces.

And if I click in, I can see a trace view of all the agent's activities with direct integration into our existing backend APIs through an MCP server.

This is where Azure Monitor and unified logging is foundational to connecting the dots for a more complete view of the health of your service.

It unifies telemetry in real time across the stack using open telemetry as well as native integrations with Azure services and normalizes those signals into a consistent schema.

And because everything shares the same data foundation, it's easy for either you or the Observability Agent to move instantly from insights, such as failed requests, to more details across different failure categories, which can be drilled into and queried further without having to stitch anything together.

So this way, even though there are several teams involved across app and infrastructure managing my app, everyone shares a common operational view to keep it operating smoothly.

It's a multi-tier app with a modern microservice backend hosted on Kubernetes with a SQL database, Redis cache, and more.

And with the new Foundry capabilities, I can also observe how it's performing from operational metrics, including agent runs, GenAI errors, tool calls, underlying models, and token consumption.

And scrolling up, we can even view traces with GenAI errors and see a list of traces.

And if I click in, I can see a trace view of all the agent's activities with direct integration into our existing backend APIs through an MCP server.

This is where Azure Monitor and unified logging is foundational to connecting the dots for a more complete view of the health of your service.

It unifies telemetry in real time across the stack using open telemetry as well as native integrations with Azure services and normalizes those signals into a consistent schema.

And because everything shares the same data foundation, it's easy for either you or the Observability Agent to move instantly from insights, such as failed requests, to more details across different failure categories, which can be drilled into and queried further without having to stitch anything together.

So this way, even though there are several teams involved across app and infrastructure managing my app, everyone shares a common operational view to keep it operating smoothly.
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