Datadog | The Monitor blog

Explore Datadog metrics with Natural Language Queries

Datadog’s new Natural Language Queries (NLQ) feature enables users to generate complex metric queries and visualizations using plain English instead of manual, syntax-heavy constru…

Simplify micro-frontend observability with Datadog RUM

Datadog RUM’s build plugin addresses the observability challenges of micro-frontend architectures by automatically attributing telemetry data, such as errors and performance metric…

Toto 2.0: Time series forecasting enters the scaling era

The developers have released Toto 2, a family of open-weights time series foundation models ranging from 4m to 2.5B parameters that demonstrates significant performance gains throu…

Attribute AI costs across providers with Datadog Cloud Cost Management

Datadog Cloud Cost Management (CCM) has introduced a new AI Costs feature to provide unified visibility and attribution for AI spending across multiple providers like OpenAI and An…

Diagnose and resolve database performance issues faster with Database Investigator

Datadog’s Database Investigator uses an agentic approach to automate the complex process of diagnosing database performance issues by correlating application and database metrics. …

Analyze cloud costs with flexible spreadsheets in Datadog Sheets

Datadog Sheets integrates with Cloud Cost Management (CCM) to allow FinOps teams to perform advanced analysis, such as currency conversion and budget forecasting, directly within t…

Datadog for Government achieves FedRAMP® High certification

Datadog for Government has achieved FedRAMP® High certification, enabling the platform to support the federal government's most sensitive and mission-critical civilian workloads. T…

Connect triage and investigation in a single workflow with Datadog Cloud SIEM

Datadog Cloud SIEM streamlines security operations by unifying detection, investigation, and response within a single, connected workflow. The platform enables analysts to escalate…

Inside Datadog’s AI Research Lab: Meet two PhD candidates behind Toto

Datadog’s AI Research Lab in Paris utilizes the CIFRE program to bridge the gap between academic research and industrial application, allowing PhD students to apply advanced models…

Monitor and optimize Supabase query performance with Datadog Database Monitoring

Datadog’s Database Monitoring (DBM) for Supabase offers an agentless, one-click solution that provides developers with deep, query-level visibility and actionable optimization reco…

This Month in Datadog - April 2026

The latest Datadog update highlights several AI-driven advancements, including the new MCP Server for providing AI agents with real-time access to observability data and the Bits A…

Add dynamically updating context to logs with Reference Tables and Observability Pipelines

Datadog Observability Pipelines utilizes Reference Tables to centrally enrich logs with real-time metadata from external sources like Snowflake, ServiceNow, and cloud storage befor…