Datadog | The Monitor blog

How we migrated a live routing system using AI-assisted refactoring

To overcome scaling limits caused by an inadequate key-value storage model, Datadog redesigned its Stream Router architecture using a relational schema to better manage complex dat…

How to migrate feature flags without breaking production

Feature flag migrations can be executed safely by replacing high-risk, large-scale cutovers with an incremental approach that allows two systems to run in parallel. By redirecting …

Using Evaluation Frameworks with Agent Observability

Datadog Agent Observability enables AI teams to operationalize LLM evaluations by natively supporting existing open-source frameworks, such as DeepEval and Pydantic Evals, within i…

Store and search high-volume logs with ClickHouse and Datadog

Datadog and ClickHouse have introduced a new integration that allows users to route high-volume logs to ClickHouse via Observability Pipelines for cost-efficient storage and proces…

Datadog MCP Apps: Interactive experiences in AI workflows

Datadog’s new MCP Apps extend the Datadog MCP Server by integrating interactive UI elements, such as live graphs and monitor cards, directly into AI interfaces like Claude, Cursor,…

Automate threat hunting with Datadog Cloud SIEM

Datadog has introduced Bits Threat Hunting, an autonomous AI agent for its Cloud SIEM designed to transition security operations from reactive detection to proactive, hypothesis-dr…

Comprehensively connect your service data with Service Remapping

Datadog has introduced "Service Remapping," a new feature that allows users to rename, merge, or split services directly through the UI without requiring code changes or redeployme…

Ship internal applications from your AI Agent with Datadog Apps

Datadog Apps provides a code-first framework for building and running custom internal applications directly within the Datadog platform, specifically optimized for use with AI codi…

Ship code safely at AI speed with Bits Release

Bits Release is a new Datadog tool designed to manage the increasing velocity of AI-driven code deployments by automating release validation and rollout intelligence from pull requ…

Detect source code attacks with Datadog Code Threat Detection

Datadog Code Threat Detection uses AI-assisted analysis to identify malicious pull requests that target CI/CD pipelines, dependencies, and development workflows. Unlike traditional…

Investigate logs across your entire stack with Federated Logs

Datadog Federated Logs enables users to query external data stores, such as Databricks and ClickHouse, directly from the Datadog Log Explorer using a single, consistent syntax. Whe…

Trace network paths from devices to SaaS applications

Datadog is combining its End User Device Monitoring with Network Path to allow IT teams to trace the entire network journey from a user's device to a SaaS application. This integra…