Technology
Use Case
Organizations across many industries rely on Oracle Cloud Infrastructure (OCI) to run their infrastructure and global-scale applications—from enterprises aiming to bring products to market faster to startups looking to reduce upfront infrastructure cost. As organizations adopt OCI to deploy distributed, scalable infrastructure, they also need visibility into every layer of their OCI environment (as well as any other infrastructure) to maintain and optimize performance. Datadog unifies all of the data streaming from your OCI environment, aggregating logs, metrics, traces, and other telemetry in a single pane of glass for all your teams. We provide 20+ easy-to-install OCI integrations and for a unified view of your systems, out-of-the-box dashboards for troubleshooting, and preconfigured alerts for proactive monitoring. Companies can deploy the Datadog Agent to get comprehensive visibility into their bare metal instances, virtual machines, or via Oracle’s Container Engine for Kubernetes (OKE). Once enabled, teams can visualize their infrastructure and track key metrics across hosts, pods, and containers—down to two-second resolution. And with Datadog’s out-of-the-box OCI integration dashboards, companies not only get a high-level view of their infrastructure and applications but also deeper visibility into specific OCI services, such as Oracle Databases, Compute, Object Storage, and more.
Organizations with hybrid and multi-cloud environments often use multiple monitoring tools for end-to-end visibility. This can create data silos and make it difficult for teams to effectively monitor and address issues. Datadog unifies observability data and metrics from any host and service, providing deep, cross-platform visibility into critical applications. For organizations using Oracle Cloud Infrastructure alongside other cloud providers or on-prem infrastructure, Datadog eliminates the need for multiple point solutions. Datadog spans hybrid and multi-cloud environments to provide a centralized, and ), teams can visualize the dependencies between applications, databases, APIs, containers, and more, enabling them to easily follow the data flowing between OCI, other cloud providers, and on-prem hosts. Companies can set up applications to send traces to Datadog using several official , including Java.
As organizations move AI applications out of development and into production, observability becomes essential to maximize efficiency and performance across the stack. Datadog’s OCI integration provides inference metrics for OCI GPU compute resources, such as GPU utilization, GPU memory utilization, power draw, and temperature. And with Datadog’s integration with NVIDIA’s DCGM Exporter, organizations can also get visibility into their broader GPU infrastructure. Companies using large language models (LLMs) can use Datadog’s LLM Observability to improve and reduce costs. Teams can also quickly identify the root causes of inaccurate LLM responses across the LLM chain, with end-to-end trace visibility for each user request. Companies can use Datadog to correlate GPU infrastructure metrics with performance data on their LLMs and other AI technologies for end-to-end visibility into inference workloads on OCI.
With the growing complexity of applications, companies struggle to monitor and troubleshoot the databases they rely on. A single database failure impacts multiple applications, often taking hours to investigate and resolve. Teams can use Datadog’s for deep visibility into the health and performance of their Oracle databases, including self-hosted, , , and . Teams can optimize database performance by identifying the most resource-intensive queries and bottlenecks, with detailed latency metrics and end-to-end application tracing.
When migrating applications to Oracle Cloud Infrastructure or other cloud platforms, companies often refactor them to leverage the flexibility and scalability of the cloud. This requires choosing the right services to support an application’s architecture in order to decrease friction during the migration. Datadog enables teams to seamlessly track their services’ performance throughout the migration process, so they can ensure they meet expected benchmarks. And with over , Datadog can monitor even more of the infrastructure and technologies companies rely on during a migration, including those not deployed on OCI. IT Infrastructure or SRE teams can use the Host Map (included in Datadog ) to monitor real-time metrics such as network throughput and CPU utilization for all hosts across availability zones before, during, and after a migration.
It’s easier than ever to gain full visibility into OCI, hybrid, and multi-cloud environments. Datadog’s unified observability platform gives teams a single source of truth to proactively monitor, detect, investigate, and resolve issues as you migrate and modernize in the cloud. And with Datadog’s 1,000+ easy-to-install integrations, teams can seamlessly connect Datadog into existing workflows in tools like Slack, PagerDuty, and Jira.