Datadog expands OCI support with GPU, cost & SIEM features
Datadog has released new integrations for its observability and security platform on Oracle Cloud Infrastructure, focusing on Cloud Cost Management, GPU Monitoring, and Cloud SIEM.
The newly launched features aim to provide customers with comprehensive monitoring and management capabilities across their Oracle Cloud Infrastructure (OCI) deployments, covering AI and machine learning applications as well as broader cloud workloads.
As organisations increasingly leverage OCI to deliver scalable and low-latency services, the enhancements are designed to support migration from on-premises environments and provide detailed insights into infrastructure health and performance.
Expanded integrations
Datadog's new integrations comprise GPU Monitoring, Cloud Cost Management, and Cloud SIEM. These build on the company's existing monitoring capabilities to deliver a consolidated view of compute, networking, and database performance for customers working within OCI.
The GPU Monitoring integration helps teams make informed decisions regarding resource provisioning by offering data on GPU core and memory utilisation, temperature, and power metrics. This enables optimisation of AI workloads, rapid issue troubleshooting and opportunities to reduce idle GPU expenditure.
The Cloud Cost Management integration provides a centralised dashboard for tracking and analysing OCI utilisation by service and project. With this, teams can attribute costs, receive recommendations for usage optimisation, and identify potential savings without sacrificing operational performance.
For security, Datadog's Cloud SIEM integration brings OCI security telemetry into the platform, aiming to streamline detection and investigation of threats across hybrid and cloud-native environments.
Industry collaboration
Organisations relying on OCI benefit from a combination of Datadog's monitoring approach and Oracle's cloud capabilities, leading to a unified source of observability and security analytics. The company highlights that these improvements are aligned with the needs of enterprises running high-performance and AI-enabled services on OCI and other cloud platforms.
"Organisations need data-driven insight to make smart provisioning and scaling decisions for critical AI workloads," said Yrieix Garnier, VP of Product, Datadog. "With this expanded support, Datadog becomes one of the first observability vendors to deliver streamlined GPU monitoring for OCI. This expansion builds on Datadog's 70+ AI/ML integrations-including OpenAI, Anthropic and GitHub-to help customers manage next-generation workloads at scale."
The expanded integrations come as organisations seek more effective ways to manage the complexity and cost of AI and machine learning workloads in the public cloud, while maintaining the necessary levels of performance and security.
Support for AI and ML
According to Datadog, the GPU Monitoring feature is especially relevant for teams running machine learning and AI workloads. Detailed visibility into resource usage and performance is considered vital to ensuring reliable operations and controlling infrastructure expenses.
Cost management is also a focus, particularly as enterprises deploy a wider array of services across OCI. By offering visibility into usage attribution, Datadog aims to equip teams with the information required to optimise spending and align resources with business objectives.
The company's Cloud SIEM integration aims to further assist security and operations teams by merging security data from OCI into a single console, enabling more efficient threat detection and streamlined investigations.
Unified platform strategy
Datadog states that its overall strategy is to unify observability and security telemetry from OCI and other public cloud providers under a single monitoring platform. The company says this supports cross-functional collaboration among development, operations, and security teams while supporting cloud migration and digital transformation strategies.
The new additions build on Datadog's ecosystem of over 70 integrations for AI and machine learning, including integrations with OpenAI, Anthropic, and GitHub, offering expanded support for customers managing complex, large-scale workloads across multiple environments.
