Datadog lists Nebius, Inc. as a United States subprocessor providing AI services. Its register identifies subprocessors by their locations and the services they provide to Datadog.
Datadog’s merged Agent code preserves a device specification observed on a Nebius H200 node running dynamic MIG. The observed resource pool was computeinstance-u00gcpath9ehe3c8xe. MIG splits one physical GPU into separately allocated compute and memory slices so separate workloads can share it.
The associated pull request reports a test with two pods using slices labelled 1g.35gb and 1g.18gb on the same GPU. Each pod’s metrics were attributed to its own MIG UUID. Validation also covered attribution after initial allocation, its removal after pod deletion, re-attribution after pod recreation, and automatic recovery after an Agent restart.
The implementation resolves Kubernetes DRA resource claims into device identities the GPU check can use for pod tagging. Allocated device names are scoped to a resource pool rather than being NVML UUIDs. Node-local CDI specifications map those names to device nodes, which the implementation resolves through NVML to MIG UUIDs. Those UUIDs let the Agent associate GPU metrics with the containers and pods holding the allocated slices.
Agent PR #55271: node-local DRA device resolution for MIG attribution
Listed 22 Oct 2026 · GitHub · Web page
For Datadog’s Nebius H200 monitoring validation, zhuminyi reports two pods using 1g.35gb and 1g.18gb slices on the same GPU, each attributed to its own MIG UUID. The PR records resource pool computeinstance-u00gcpath9ehe3c8xe and explains how node-local CDI specifications resolve DRA allocations for GPU-metric pod tagging. Tests cover allocation, deletion, recreation and Agent restart recovery.
Agent PR #55271: node-local DRA device resolution for MIG attributionListed 22 Oct 2026 · GitHub · Web pageFor Datadog’s Nebius H200 monitoring validation, zhuminyi reports two pods using 1g.35gb and 1g.18gb slices on the same GPU, each attributed to its own MIG UUID. The PR records resource pool computeinstance-u00gcpath9ehe3c8xe and explains how node-local CDI specifications resolve DRA allocations for GPU-metric pod tagging. Tests cover allocation, deletion, recreation and Agent restart recovery.
Datadog subprocessors listListed 22 Oct 2026 · Datadog · Web pageDatadog lists Nebius, Inc. as a United States subprocessor providing AI services to Datadog.
Datadog provides a cloud-based monitoring and analytics platform used by developers, IT operations and security teams, as well as business users. Its products help organizations monitor infrastructure and application performance, manage logs, observe user experience and assess cloud security across cloud, hybrid and on-premises environments. The platform brings together metrics, traces, logs and security signals to help teams investigate issues and understand the health and performance of their technology systems.
Datadog Security Labs released pathrunner, an open source framework for testing AWS privilege escalation paths. It includes more than 80 exploit modules and modular payloads to help security teams validate exposure and detections.
Datadog introduces Scout 1.0 for production incident investigations
Datadog introduced its first AI model specialized for investigating production issues, powering Bits Investigation. Datadog engineers and a small group of customers were using it in closed preview, with additional preview registrations open.
Code Execution became generally available in the Datadog MCP Server. AI agents can write JavaScript to query Datadog through a managed sandbox and return consolidated results.
Observability and security platform for applications, infrastructure, data and AI models. · Infrastructure
How they use Nebius AI Cloud
Datadog lists Nebius, Inc. as a United States subprocessor providing AI services. Its register identifies subprocessors by their locations and the services they provide to Datadog.
Datadog’s merged Agent code preserves a device specification observed on a Nebius H200 node running dynamic MIG. The observed resource pool was computeinstance-u00gcpath9ehe3c8xe. MIG splits one physical GPU into separately allocated compute and memory slices so separate workloads can share it.
The associated pull request reports a test with two pods using slices labelled 1g.35gb and 1g.18gb on the same GPU. Each pod’s metrics were attributed to its own MIG UUID. Validation also covered attribution after initial allocation, its removal after pod deletion, re-attribution after pod recreation, and automatic recovery after an Agent restart.
The implementation resolves Kubernetes DRA resource claims into device identities the GPU check can use for pod tagging. Allocated device names are scoped to a resource pool rather than being NVML UUIDs. Node-local CDI specifications map those names to device nodes, which the implementation resolves through NVML to MIG UUIDs. Those UUIDs let the Agent associate GPU metrics with the containers and pods holding the allocated slices.
Agent PR #55271: node-local DRA device resolution for MIG attribution
Listed 22 Oct 2026 · GitHub · Web page
For Datadog’s Nebius H200 monitoring validation, zhuminyi reports two pods using 1g.35gb and 1g.18gb slices on the same GPU, each attributed to its own MIG UUID. The PR records resource pool computeinstance-u00gcpath9ehe3c8xe and explains how node-local CDI specifications resolve DRA allocations for GPU-metric pod tagging. Tests cover allocation, deletion, recreation and Agent restart recovery.
Agent PR #55271: node-local DRA device resolution for MIG attributionListed 22 Oct 2026 · GitHub · Web pageFor Datadog’s Nebius H200 monitoring validation, zhuminyi reports two pods using 1g.35gb and 1g.18gb slices on the same GPU, each attributed to its own MIG UUID. The PR records resource pool computeinstance-u00gcpath9ehe3c8xe and explains how node-local CDI specifications resolve DRA allocations for GPU-metric pod tagging. Tests cover allocation, deletion, recreation and Agent restart recovery.
Datadog subprocessors listListed 22 Oct 2026 · Datadog · Web pageDatadog lists Nebius, Inc. as a United States subprocessor providing AI services to Datadog.
Datadog provides a cloud-based monitoring and analytics platform used by developers, IT operations and security teams, as well as business users. Its products help organizations monitor infrastructure and application performance, manage logs, observe user experience and assess cloud security across cloud, hybrid and on-premises environments. The platform brings together metrics, traces, logs and security signals to help teams investigate issues and understand the health and performance of their technology systems.
Datadog Security Labs released pathrunner, an open source framework for testing AWS privilege escalation paths. It includes more than 80 exploit modules and modular payloads to help security teams validate exposure and detections.
Datadog introduces Scout 1.0 for production incident investigations
Datadog introduced its first AI model specialized for investigating production issues, powering Bits Investigation. Datadog engineers and a small group of customers were using it in closed preview, with additional preview registrations open.
Code Execution became generally available in the Datadog MCP Server. AI agents can write JavaScript to query Datadog through a managed sandbox and return consolidated results.
