Operations | Monitoring | ITSM | DevOps | Cloud

Misconfigured infrastructure resources can be easy to miss, especially in multi-account or multi-cloud environments. From EKS clusters running on deprecated versions to RDS engines on extended support, these issues can disrupt services or drive up costs if left unchecked. In this video, we show you how to: By centralizing policies, you’ll gain a clear view of where to focus your remediation efforts.

Tired of surprises on your cloud bills? With Datadog Cloud Cost Management integrated into the Software Catalog, engineers see cost, performance, and reliability side by side—no context switching required. Give every service owner the visibility they need to make cost-aware decisions.

Do you know the true cost per user, API call, or checkout? Datadog Cloud Cost Management lets you break down spend by combining cost, observability, and custom business metrics—all in one place. Track cost per transaction, alert on changes, and align engineering and finance with real-time unit economics.

Datadog is constantly elevating the approach to cloud monitoring and security. This Month in Datadog updates you on our newest product features, announcements, resources, and events. To learn more about Datadog and start a free 14-day trial, visit Cloud Monitoring as a Service | Datadog. This month, we chat with two guests about Bits AI SRE and Datadog Data Observability.

With Datadog's AI Agents Console, you can monitor the behavior and interactions of any AI agent that’s a part of your enterprise stack, whether that’s a computer use agent like OpenAI’s Operator, IDE agent like Cursor, DevOps agent like Github Copilot, enterprise business agent like Agentforce, or your internally built agents. You'll have full visibility into every agent's actions, insights into the security and performance of your agents, analytics on user engagement, and measurable business value from every agent, all in a centralized location.

Datadog’s Latency Investigator for APM—now in Preview—automatically investigates hypotheses in the background, comparing historical traces and correlating change tracking, DBM, and profiling signals. This helps teams quickly isolate root causes and understand impact without combing through raw telemetry data. You can go from detection to resolution in a single workflow, and generate a pull request to apply a recommended fix, all without leaving Datadog..

Datadog Data Observability provides a complete solution with quality checks (e.g., volume, row changes, freshness), custom SQL-based monitors, anomaly detection, column-level lineage across systems like Snowflake and Tableau, full pipeline visibility, and targeted alerts when data issues arise.

Datadog Sheets provides a spreadsheet-style interface for analyzing your telemetry data — you can perform lookups, build pivot tables, and create calculated columns using familiar spreadsheet functionality. This enables teams to join datasets, aggregate results, and explore trends without writing code.

The Datadog Cursor Extension uses the Datadog remote MCP Server to give developers access to Datadog tools and observability data directly from within the Cursor IDE. The Cursor Extension enables you to view live variable values that your logpoints capture during execution, and you can use the Cursor Agent to identify the lines of code responsible for the issue at hand. The Datadog Cursor Extension is now available in Preview.

Datadog Internal Developer Portal (IDP) helps developers quickly track down shared engineering knowledge, execute common production tasks in self-service manner, and evaluate the production-readiness of new service code.