
Developed and delivered a Datadog observability integration for the AgentCore Runtime in the awslabs/amazon-bedrock-agentcore-samples repository, enabling monitoring of large language model applications without requiring a separate Datadog agent. Leveraged OpenTelemetry and AWS to export metrics, logs, and traces directly to Datadog using the OTLP protocol. Authored comprehensive onboarding materials, including a tutorial notebook, configuration files, and updated documentation to streamline adoption for engineering teams. Collaborated with partner observability teams to ensure alignment with Datadog best practices and maintainability. The work enhanced the observability posture of Bedrock AgentCore deployments and reduced mean time to resolution for operational issues.
Month: 2026-04 — Key delivery: Datadog Observability Integration for AgentCore Runtime in awslabs/amazon-bedrock-agentcore-samples, enabling OpenTelemetry-based monitoring of LLM applications without a separate Datadog agent; included a tutorial notebook, configuration files, and README updates. This work improves observability posture for Bedrock AgentCore deployments, reduces MTTR by surfacing metrics/logs/traces in Datadog, and simplifies onboarding for teams.
Month: 2026-04 — Key delivery: Datadog Observability Integration for AgentCore Runtime in awslabs/amazon-bedrock-agentcore-samples, enabling OpenTelemetry-based monitoring of LLM applications without a separate Datadog agent; included a tutorial notebook, configuration files, and README updates. This work improves observability posture for Bedrock AgentCore deployments, reduces MTTR by surfacing metrics/logs/traces in Datadog, and simplifies onboarding for teams.

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