Datadog Adds ‘Watchdog’ Autonomous Machine Learning-based Monitoring for Cloud Applications

Datadog, a monitoring service for hybrid cloud applications, has announced the availability of Watchdog – a machine learning-based monitoring capability that automatically identifies hidden issues and anomalies in dynamic, cloud-based applications.

In traditional monitoring, engineers explicitly define the expected behavior of their application and set up dashboards and alerts to monitor for deviations from this behavior. However, due to the scale, elasticity, and complexity of modern cloud applications, issues often occur in unexpected places that engineers may not have thought to monitor explicitly.

Watchdog would take a radically different approach: it observes all performance data automatically and surfaces anomalous behavior that would have otherwise remained invisible to the application’s engineers. According to Datadog, these observations help engineering organizations resolve existing performance problems, or head off emerging issues before they are noted by end users.

Watchdog was announced at Dash, Datadog’s conference for engineers who are building and scaling the next generation of applications, infrastructure, and technical teams. This capability is now generally available within Datadog for all customers on Datadog’s Enterprise APM plan.

“As application environments become more complex and the volume of operations data that teams collect grows, engineers require new technologies and tools to glean insight from that data,” said Nancy Gohring, Senior Analyst at 451 Research. “Advanced analytics systems that separate the important data from the noise can help DevOps teams get the most out of operations data so that they can quickly repair or prevent performance problems.”

8,000 Enterprises

Since launching in 2010, Datadog has been adopted by more than 8,000 enterprises including companies like Asana, AT&T, Evernote, Samsung, Seamless, and The Washington Post.

“As the complexity of applications explodes, the need for automated issue detection becomes a necessity for teams to build highly performant and reliable applications in the cloud,” said Homin Lee, Head of Data Science at Datadog. “Watchdog builds upon our years of research and training of algorithms on our customers’ data sets. This technology is unique in that it not only identifies an issue programmatically but also points users to probable root causes to kick off an investigation.”