Predicts variable cloud resource needs during production and managing the reliability of digital services

Sumo Logic, the SaaS analytics platform to enable reliable and secure cloud-native applications, today 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. Sumo Logic will showcase this functionality at booth S26 during the KubeCon + CloudNativeCon Europe 2023 event in Amsterdam from April 18-21.

“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.”

As organizations rapidly spin up new infrastructure in the cloud and manage the reliability of their sprawling digital apps and services, the influx of unplanned usage creates strain for developers and operations managers. Understanding fluctuating cloud usage for capacity management and reducing resource bottlenecks and unplanned system loads that cause production incidents is critical.

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.

Using Predict for Metrics

• 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.