Sumo Logic announced Predict for Metrics.
When combined with existing capabilities in Sumo Logic, Predict for Metrics provides a comprehensive way to harness observability analytics to better predict variable applications, cloud and infrastructure usage and resource demands.
Predict for Metrics is designed to provide better visibility into production issues, system downtime, and uncontrolled cloud costs.
“To keep pace with the speed of modern application development, it is important that operations leaders are able to predict their app and cloud usage needs to keep operations running smoothly and avoid unplanned downtime,” said Erez Barak, VP of Product Development for Observability, Sumo Logic. “Predictive analytics for logs and metrics telemetry provides the key to managing cloud infrastructure and app development variables. Our customers will gain valuable insights to ensure better resilience to avoidable production issues.”
Similar to the existing predict operator for Logs, Predict for Metrics uses linear and autoregressive models to make predictions by harnessing past data points to predict future trends. It is a metrics query language operator, which allows users to visualize forecasted values and add resulting charts to Sumo Logic dashboards. Here are some additional use cases for Predict for Metrics.
Predict for Metrics enables users to:
- Optimize Ingest: Understanding and planning for anticipated volume is important. Administrators can now leverage Predict for Metrics to forecast volume and adjust ingest accordingly to avoid any surprises or disruptions.
- Forecast App Resource Requirements: Sumo Logic customers can use predictive analytics on APM trace metrics to forecast the load on an application or its underlying microservice. They can also forecast potential infrastructure bottlenecks such as how much CPU, memory or disk space to provision across AWS EC2 or AWS DynamoDB instances.
- Reduce Data Bottlenecks: Unplanned resource bottlenecks are a common root cause for application outages. Organizations can now determine which critical resources will run out of capacity, such as provisioned throughput for AWS DynamoDB or Provisioned Memory for AWS Lambda functions and more.
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