Datadog Expands Focus on Visibility, Data Retention and User Experience Data Management

As organizations collect growing volumes of application and customer interaction data, technology teams are increasingly looking for ways to understand user experience issues, retain session data for investigations, and move data into their own storage environments for further analysis.

Datadog has announced the general availability of three new capabilities within its Real User Monitoring (RUM) suite: RUM Profiling, Managed Archive and Export Pipelines. According to the company, the additions are designed to help organizations gain greater visibility into application performance and manage user session data more effectively.

The new RUM Profiling capability links user-facing performance issues to the underlying code associated with a degraded experience. The feature is available across Chrome, iOS and Android environments. According to Datadog, it enables engineering teams to correlate user sessions and actions with profiling data to aid troubleshooting.

“RUM tells you what broke; RUM Profiling tells you why,” the company said in the announcement.

The company has also introduced Managed Archive, which allows organizations to store user sessions in Datadog-managed storage and retrieve them when required. Datadog said the capability can be used for support investigations, incident response activities and situations requiring access to historical session data.

“Teams can access session-level data well beyond standard retention windows, giving compliance, legal and regulated teams the data they need whenever an audit or investigation calls for it,” the company stated.

The third addition, Export Pipelines, enables organizations to continuously export RUM and Product Analytics data to cloud storage environments they own. According to Datadog, the exported data can be retained for as long as an organization requires and used for downstream analytics workflows.

“Teams can also power their data analysis and ML models with Export Pipelines by feeding large volumes of raw behavioral events into their warehouse or data lake for ML training and cross-dataset analysis,” the company said.

The announcement reflects a broader industry focus on application observability, user experience monitoring and data management. As enterprises expand digital services across web and mobile channels, technologies that help collect, retain and export operational and user-experience data are becoming an increasingly important part of software operations and analytics strategies.