Deepgram expands SageMaker AI observability metrics

Deepgram's move addresses a long-standing pain point for self-hosted speech AI: the lack of visibility into what happens inside the vendor's container. Previously, you could see basic endpoint metrics like request counts, but not the billing units, feature usage, or engine behavior that drive capacity planning and cost management. By publishing these metrics into your own CloudWatch account, Deepgram lets you reconcile your AWS bill against actual traffic and understand which features your applications use, without compromising network isolation.

The two innovations complement each other. Deepgram Enhanced Metrics focus on billing and usage, answering questions like what you're billed for and how much streaming versus pre-recorded traffic you handle. The Prometheus and OpenTelemetry support goes deeper, offering per-GPU and host-level metrics that can reveal a saturated device hiding behind a summed average. Together, they provide a complete picture, from cost to engine headroom.

For teams running Deepgram on SageMaker AI, this could simplify compliance and cost governance. The billing stream cannot be disabled, ensuring a permanent audit trail, while the usage stream can be turned off if needed. As these metrics are standard CloudWatch metrics, you can build dashboards and set alarms, integrating AI operations into your existing monitoring workflows.