Datadog | The Monitor blog

Monitor your .NET MAUI apps with Datadog RUM

Datadog has launched an official .NET MAUI SDK to provide a supported, reliable solution for monitoring cross-platform mobile applications. The SDK automates essential features lik…

Protect AWS Strands Agents with Datadog AI Guard

Datadog AI Guard now features a plugin for AWS Strands Agents that provides real-time security by evaluating prompts, responses, and tool interactions within the agent loop. This i…

DASH 2026 recap: Product news, sessions, and highlights

Datadog’s DASH 2026 event in New York City brought together thousands of technology professionals to explore the future of observability, security, and AI-driven operations. The co…

Reduce SAST false positives with agentic evaluation and Bits Memories

Datadog is enhancing its Static Code Analysis tool with "agentic evaluation" and "Bits Memories" to reduce the high volume of false positives common in traditional SAST tools. Agen…

Monitor watchOS and visionOS apps with Datadog RUM

Datadog RUM has expanded its support to include Apple’s watchOS and visionOS, providing developers with much-needed observability for these growing platforms. By leveraging the exi…

The effect distribution: The missing piece in experimentation programs

The article argues that successful experimentation requires understanding the "effect distribution"—the true underlying impact of all product changes—rather than relying solely on …

Accelerate investigations with AI in Datadog Incident Response

Datadog Incident Response has launched three new AI-powered capabilities—Bits Investigation, AI chat summaries, and automated bridge call transcription—designed to streamline how e…

How Datadog uses AI to build internal software delivery tools and improve system performance

Datadog is leveraging AI-driven agent orchestration and coding assistants to optimize its software development lifecycle through the creation of advanced internal tools. Key implem…

How we measure data completeness at scale

To ensure reliability for both users and automated AI agents, Datadog developed a system that monitors the completeness of its massive ingestion pipelines by dividing complex workf…

5 pitfalls to avoid when measuring DevEx in the AI era

To effectively measure Developer Experience (DevEx), organizations should avoid the pitfalls of tracking individual output or assuming that AI adoption automatically equates to inc…

Debug and evaluate your AI app from your coding agent with Datadog Agent Observability

Datadog has introduced a suite of new "Agent Skills" designed to help coding agents automate the complex tasks of evaluating and debugging AI applications. By leveraging the Datado…

Datadog acquires Adaptive ML

Datadog is acquiring Adaptive ML to enhance its ability to build and deploy specialized, high-performance AI agents. By integrating Adaptive ML’s fine-tuning platform with Datadog’…