On the October episode of This Month in Datadog, Jeremy Garcia (VP of Technical Community and Open Source) covers unified Error Tracking, Security Operational Metrics, and a new Datadog Serverless feature for retrying or redriving failed AWS Step Functions executions directly from Datadog. Later in the episode, Shri Subramanian (Group Product Manager) spotlights Datadog LLM Observability’s native integration with Google Gemini. Also featured are our blog posts Operator vs. Helm and How we used Datadog to save $17.5 million annually along with the 2024 State of Cloud Security report.
This Month in Datadog is a monthly update of the company’s latest features, product announcements, and more. Subscribe to our YouTube channel to get notifications about future episodes.
New features
View and search across RUM, APM, and Logs in one place with unified Error Tracking
Datadog Error Tracking groups similar errors together to reduce noise and help teams prioritize remediation efforts. Whereas users could search for browser, mobile, and backend issues separately, now unified Error Tracking enables you to view and search across RUM, APM, and Logs in one place. With this new feature, you get a single source of truth for errors across the front- and backend of your applications and services. Unified Error Tracking is available to all customers today. Check out the release note to learn more.
Assess a team’s effectiveness at responding to threats with Security Operational Metrics
Located on the pre-built Cloud SIEM Overview dashboard, Security Operational Metrics help you assess a team’s effectiveness at responding to threats by capturing their mean time to detect, acknowledge, and resolve. Additionally, you can create dashboards and monitors for these metrics and use tags to filter them by teams, sources, and environments. Check out Security Operational Metrics today on the Cloud SIEM overview dashboard and learn more by visiting our docs.
Retry or redrive failed Step Functions executions from Datadog
AWS Step Functions is a serverless orchestration service that enables you to create application workflows in the cloud. On top of using Datadog to monitor Step Functions, now you can retry executions or redrive them from failed steps from the Serverless UI. Not only does this feature reduce the need to manually document the Amazon Resource Names of failed executions, but this also reduces the time to remediate errors. Users who monitor Step Functions with Datadog can take advantage of this new feature today.
Datadog LLM Observability’s native integration with Google Gemini
Organizations today are racing to adopt LLMs and using a variety of models, such as Google Gemini and Azure OpenAI. Datadog LLM Observability’s native integration with Google Gemini automatically captures the LLM requests your application makes to Gemini’s model. And Datadog’s end-to-end tracing capabilities help you understand the behavior of LLM applications. This native integration is generally available today. Learn more about what Datadog LLM Observability can do by checking out the blog post.
Additional updates
- New App Builder blueprints for GitHub, Azure, AWS, and more
- Optimize Ruby garbage collection activity with Datadog
- Manage and monitor RUM apps with Service Catalog
- Apps Created by Datadog available in dashboards
See you next month
Check out our release notes for a full list of new features and updates. You can see these features and updates in action by logging onto the Datadog platform today or signing up for a 14-day free trial. We will see you next month.