In the September episode of This Month in Datadog, Jeremy shows how you can more easily troubleshoot network slowdowns, track Claude usage and cost data, and gain additional logging capabilities, such as migrating historical logs. Later in the episode, Aaron spotlights Datadog Feature Flags, which help you reduce the risks of feature rollouts.

Plus, we take a look at a blog post series on security threats targeting AI applications and AI Tools Lab, a series by Datadog advocates about AI tools and their applications in software development and beyond.

New features

Safely roll out features with Datadog Feature Flags

Releasing new features is one of the riskiest parts of a software engineer’s job. Datadog Feature Flags integrates flagging and observability, enabling safer releases. With advanced targeting, built-in observability, and automatic rollbacks, teams get the capabilities they need to release confidently. See what else Datadog Feature Flags can do by reading this blog post.

More easily troubleshoot slowdowns with Network Path

Traditionally, troubleshooting network slowdowns has been a manual process, leaving teams to piece together fragmented data. Now with Datadog Network Path, organizations get a clearer view of packets as they travel from source to destination. Our new feature visualizes traffic between applications, enabling teams to easily pinpoint the root cause of network problems. Take a closer look at Network Path by visiting this blog post.

Track Claude usage and cost data with Cloud Cost Management’s integration

Managing the cost of foundation models is a critical challenge, especially for teams using powerful models like Claude Opus. Now, Cloud Cost Management integrates with the Anthropic Usage and Cost Admin API, allowing organizations to ingest Claude usage and cost data directly into their dashboards, reports, and monitors. With this integration, teams can stay on top of total tokens, total cost, token usage, and more.

Check out our blog about Cloud Cost Management’s integration with the Anthropic Usage and Cost Admin API to learn more.

Migrate historical logs and more with the new Custom Processor

Handling logs from multiple vendors and formats is a complex and costly task. The new Custom Processor in Observability Pipelines allows teams to use Vector Remap Language to expand their logging capabilities. This includes migrating historical logs from vendors such as Splunk and Sumo Logic. It also ensures that cost control rules apply consistently across different log formats.

Discover popular use cases for the Custom Processor with this guide, or head over to the Datadog platform to start using this new feature today.

Additional updates

Other features and updates released this month include:

• Debug failing pipelines by viewing Synthetic test runs in Test Optimization
• Eliminate cloud waste across Azure and Google Cloud with Cloud Cost Recommendations
• Visualize observability gaps and security risks in Cloudcraft
• Gain visibility into expired and broken certificate chains with Datadog’s Windows Certificate Store integration

See you next month

This Month in Datadog is a monthly roundup of our latest features, product announcements, and more. Subscribe to our YouTube channel to get notified when future episodes are live.

In the meantime, check out our release notes for a full list of new features and updates. Or see them in action by logging onto the Datadog platform or signing up for a 14-day free trial. See you next month!