Operations | Monitoring | ITSM | DevOps | Cloud

Easily Map Logs to OCSF with Datadog Observability Pipelines

Normalizing security logs into the Open Cybersecurity Schema Framework (OCSF) is often complex, manual, and time-consuming. With Datadog Observability Pipelines, you can easily transform logs into OCSF format—right in your own environment—before routing them to destinations like Splunk, CrowdStrike, and AWS Security Lake. This video show how Security teams can use Observability Pipelines to: Collect, process, and transform logs into OCSF format automatically.

Build custom apps in seconds with conversational AI in App Builder

Using a drag-and-drop interface, engineering teams can create apps that support troubleshooting, improve day-to-day operations, and offer self-service access without leaving Datadog. With the new conversational AI feature, teams can turn an idea into a working app in seconds. Watch the video to see how it works..

Check out features we announced at AWS re:Invent in the latest episode of This Month in Datadog

Tune in for spotlights of Bits AI SRE, now generally available, and Datadog’s MCP Server, which connects AI agents to our platform by ingesting prompts and mapping them to Datadog resources and data. Plus, we cover how to: Search logs at petabyte scale in your own infrastructure with CloudPrem Break down costs drivers at the prefix level with Storage Management Create workflows that adapt to real-world complexity with Agent Builder Detect and block credential leaks with Secret Scanning.

Drive business outcomes with Unit Economics in Datadog Cloud Cost Management

See how Datadog turns cloud usage and performance data into actionable business insights by helping teams calculate unit economics to measure and optimize the efficiency of every service. You’ll discover how to: Datadog bridges the gap between cloud costs and business value—helping organizations get the most value out of their cloud investment.

From Zero to Open Source Contributor

Never contributed to open source and feeling intimidated? Same. Before joining Datadog, Alessandro had zero open source experience. Now he's a regular contributor to Apache Iceberg. Here's exactly how he got started. Step 1: Join the Slack community and answer user questions. Step 2: Look for "good first issue" tags in the repo. Step 3: Remember that opening bug reports and doing code reviews count as contributions too.

The Hidden Costs and Concerns of Iceberg Maintenance

Everyone talks about how great Apache Iceberg is, but nobody warns you about this: without proper maintenance, your tables will bloat, queries will slow down, and your catalog will run out of memory. Here are the 4 critical operations you MUST run regularly. Expiring snapshots prevents metadata bloat (Datadog learned this the hard way with catalog memory pressure). Deleting orphan files cleans up failed writes. Compacting data files keeps streaming workloads fast. Compacting manifests optimizes query planning.