Operations | Monitoring | ITSM | DevOps | Cloud

Accelerate your Azure integration setup with guided onboarding

Getting started with monitoring for Microsoft Azure environments can be a lengthy and manual process. Many tools require users to create app registrations, assign permissions, and enable log forwarding or telemetry data collection across multiple portals and scripts. These fragmented steps slow down onboarding and introduce opportunities for misconfiguration, making it harder for teams to quickly achieve full visibility.

Monitor OCI spend, AI in DDSQL Editor, OTLP Metrics API, and more | This Month in Datadog

See how you can gain insights into cloud costs by tracking OCI spend and easily comparing instance types in October’s episode of This Month in Datadog. Join us for a spotlight of Cloud Cost Management’s support for Oracle Cloud Infrastructure, and the product’s new feature, Instance Explorer, which enables you to visualize and easily compare the cost and performance of instances across AWS, Azure, and Google Cloud.

Store and search logs at petabyte scale in your own infrastructure with Datadog CloudPrem

As AI workloads and cloud-native applications expand, organizations are generating more log data than ever. Each service, container, and model inference produces continuous telemetry that must be stored, secured, and analyzed. As telemetry grows more complex, teams must balance full visibility with new retention and residency needs.

Automating your synthetic test infrastructure with Datadog Synthetic Monitoring and Terraform

Testing ecosystems contain massive amounts of data, including outlined test scenarios, prerequisite configurations, and the tests themselves. As a result, these ecosystems are prone to data sprawl. This makes it difficult to prevent configuration drift and quickly spin up new tests, especially at the frequency needed to support a fast-growing application. Teams can handle these challenges by treating their tests as part of their application infrastructure.

Store and search logs at petabyte scale in your own infrastructure with Datadog BYOC Logs

As AI workloads and cloud-native applications expand, organizations are generating more log data than ever. Each service, container, and model inference produces continuous telemetry that must be stored, secured, and analyzed. As telemetry grows more complex, teams must balance full visibility with new retention and residency needs.

Datadog named Leader in 2025 Gartner Magic Quadrant for Digital Experience Monitoring

We are thrilled to announce that, for the second consecutive year, Datadog has been named a Leader in the 2025 Gartner Magic Quadrant for Digital Experience Monitoring. We believe that this recognition reflects our continued focus on helping customers observe, secure, and act on everything that matters across their technology stack.

Transform and Migrate Logs with Datadog Custom Processor

See how Datadog’s new Custom Processor in Observability Pipelines helps you transform and migrate logs from platforms like Splunk and Sumo Logic with precision and control. This demo walks through real examples of using VRL (Vector Remap Language) to enrich log data, rewrite timestamps, apply quotas, and securely process archives.

Redefining Frontend Observability with Datadog RUM

Discover how Datadog is redefining frontend observability with Real User Monitoring (RUM). In this demo, see how RUM helps teams detect, investigate, and resolve frontend issues that directly impact user experience and business outcomes. With RUM Without Limits, you get full visibility into every user session, giving you an accurate and comprehensive view of your users’ experiences. Monitor performance, track errors, and understand how your application behaves in real time.

Get organized, actionable insights from complex test environments with Datadog Test Suites

Modern teams often run hundreds of synthetic tests across multiple services, environments, and user journeys. While these tests provide deep visibility, managing them as a flat list can quickly become overwhelming, especially as organizations scale and teams specialize.