Datadog | The Monitor blog

How to measure developer experience (DevEx) in the AI era

As AI coding assistants increase code volume without necessarily improving quality, traditional output metrics are no longer sufficient to measure true productivity. Instead, organ…

Project and manage cloud spend with Datadog budget forecasting

Datadog Cloud Cost Management (CCM) has introduced a new budget forecasting feature designed to help teams manage the rapid and unpredictable spend associated with cloud and AI ser…

How we made a SQL query optimization agent 59% more accurate using autoresearch and LLM Observability

The Datadog DBM team used Karpathy’s autoresearch tool to autonomously optimize an AI agent designed for SQL query optimization. By conducting 23 overnight experiments to refine pr…

How to audit and clean up monitors effectively

To prevent alert fatigue and critical blind spots, teams should transition from reactive monitoring to a structured audit focused on both coverage and alert quality. This process i…

Reduce CVE noise with OpenVEX assessments in Datadog

Datadog is addressing the challenge of "vulnerability noise" in security scans by providing exploitability assessments for its software artifacts via the OpenVEX specification. By …

Diagnose slow PostgreSQL queries faster with explain plan correlation

Datadog Database Monitoring has introduced explain plan correlation for PostgreSQL, a feature that directly links `EXPLAIN` plan nodes to their corresponding SQL clauses. This tool…

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…