Datadog has introduced Datadog Monitoring for Oracle Cloud Infrastructure (OCI), which enables Oracle customers to monitor enterprise cloud-native and traditional workloads on OCI with telemetry in context across their infrastructure, applications and services. With this launch, Datadog helps customers migrate with confidence from on-premises to cloud environments, execute multi-cloud strategies and monitor AI/ML inference workloads.
Datadog Monitoring for Oracle Cloud Infrastructure helps customers:
● Gain visibility into OCI and hybrid environments: Teams can collect and analyze metrics from their OCI stack by using Datadog's integrations for 20+ major OCI services and 750+ other technologies. In addition, customers can visualize the performance of OCI cloud services, on-premises servers, VMs, databases, containers and apps in near-real time with customizable, drag-and-drop, and out-of-the-box dashboards and monitors.
● Monitor AI/ML inference workloads: Teams can monitor and receive alerts on the usage and performance of GPUs, investigate root causes, monitor operational performance and evaluate the quality, privacy and safety of LLM applications.
● Get code-level visibility into applications: Real-time service maps, AI-powered synthetic monitors and alerts on latency, exceptions, code-level errors, log issues and more give teams deeper insight into the health and performance of their applications, including those using Java.
“With today’s announcement, Datadog enables Oracle customers to unify monitoring of OCI, on-premises environments and other clouds in a single pane of glass for all teams,” said Yrieix Garnier, VP of Product at Datadog. “This helps teams migrate to the cloud and execute multi-cloud strategies with confidence, knowing that they can monitor services side-by-side, visualize performance data during all stages of a migration and immediately identify service dependencies.”
