Datadog (NASDAQ: DDOG), monitoring and security platform for cloud applications, has announced new capabilities connecting user experience data with application traces. It would bridge the gap between frontend and backend performance monitoring.
This new capability would enable on-call engineering teams to pinpoint the root cause of issues impacting customer experience on mobile and web-based applications to backend services.
Traditional Real User Monitoring (RUM) and Application Performance Monitoring (APM) solutions are siloed, requiring separate workflows to troubleshoot across the stack. This would make connecting user experience data from browsers and mobile applications with backend traces, metrics, and logs a complex and tedious task. These manual correlation efforts can slow down on-call engineering teams when trying to remediate issues, as they struggle to pinpoint which part of the application stack is responsible for revenue impacting incidents.
Datadog’s automatic two-way correlation for frontend user sessions in RUM and backend traces in APM eliminates these blind spots. It would allow on-call teams to quickly identify root causes and thus maintain robust user-experience on browser and mobile applications.
MTTD and MTTR
“Typically, frontend and backend engineers use their own, siloed monitoring solutions and rarely even look at the same signals and metrics,” said Renaud Boutet, Vice President of Product, Datadog. “Very often, issues can arise anywhere in the stack and propagate in every direction. By automatically connecting user journeys that start on the frontend with requests made to backend services, Datadog enables organizations to significantly reduce MTTD and MTTR for incidents.”
Datadog’s new APM and RUM capabilities would automatically correlate critical application performance data, providing teams with:
- Full-Stack Correlation – connecting every user request to all backend services to cut down MTTD and MTTR with a unified view across the application stack
- Frontend/Backend Comparison – comparing frontend and backend durations on every request, enabling engineering teams to identify and optimize slow user experiences
- Trace Search and Analytics by User Journey Tags – slicing and dicing backend traces by location, device, operating system, and more to provide context for impacted customers