Datadog launches advanced GPU & cost tools for Oracle Cloud

Datadog has introduced new integrations for users of its platform through Oracle Cloud Marketplace, now available for deployment on Oracle Cloud Infrastructure (OCI), with a focus on enhancing reliability, optimising costs, and securing workloads-including artificial intelligence and machine learning applications.

Integration features

The latest integrations from Datadog include GPU Monitoring, Cloud Cost Management, and Cloud SIEM, which add to the platform's pre-existing monitoring suite. These additions aim to give customers comprehensive insight into their infrastructure's health and performance, providing information on compute, networking, and database metrics. The tools are also intended to facilitate migration from on-premises environments to OCI, supporting organisations running large-scale AI workloads in the cloud.

The GPU Monitoring integration enables teams to make data-driven decisions by offering detailed resource telemetry, such as GPU core and memory utilisation, temperature, and power consumption. This information can help teams optimise and troubleshoot AI workloads and reduce idle GPU expenditure. The Cloud Cost Management feature gives an aggregated overview of OCI-related spending and offers optimisation recommendations so teams can track and attribute costs by service or project, identifying savings opportunities without negatively impacting performance. Cloud SIEM extends Datadog's security capabilities by bringing OCI security telemetry into Datadog's platform, providing detection and investigation functionality for threats across cloud environments.

Support for cloud migrations

Organisations from a variety of sectors use OCI to deliver high-performance enterprise solutions, leveraging scalable architectures and low latency networks. Datadog's integrations are designed to complement OCI by unifying observability and security telemetry not only from OCI but also from other cloud providers, consolidating these insights into a single platform.

"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."

Platform expansion

Datadog's SaaS platform is used by organisations across industries to manage cloud applications, digital transformation projects, and migrations. The platform integrates and automates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, and cloud security, aiming to facilitate collaboration between development, operations, security and business teams.

The addition of GPU Monitoring for OCI aims to give customers increased control over their AI workload performance, in line with trends of increased adoption of machine learning and artificial intelligence in enterprise settings. With Cloud Cost Management, Datadog seeks to address the common concern of cloud expenditure, offering actionable insights to streamline usage and spending across multiple projects and departments. The integration of security telemetry from OCI complements these cost and monitoring initiatives by providing a layer of visibility and control for organisations focused on compliance and threat detection.

Industry context

As organisations continue to prioritise multi-cloud strategies and seek unified platforms to oversee performance, cost, and security across various infrastructure environments, observability platforms have become central to cloud operations. Datadog's integrations with OCI follow the company's ongoing efforts to expand support for cloud providers and hybrid infrastructure use cases.

According to Datadog, the current expansion brings its total number of AI and machine learning-focused integrations to more than 70, with connections to widely used platforms such as OpenAI, Anthropic, and GitHub. Company representatives note this enhanced compatibility as an important step for customers managing increasingly complex AI-driven workloads and cloud-native application architectures.