Sumo Logic enhanced its service portfolio, adding outlier detection and predictive analytics capabilities to its cloud-based data analytics platform.
The platform is designed to give customers visibility across thousands of data streams and help detect and predict performance, reliability or security issues before they happen within their apps and services.
“Advancements in machine learning and predictive analytics are making it possible for organizations to optimize business and security processes to determine and address impending issues rather than running in place to continuously fix them,” Sahir Azam, director of product management at Sumo, told eWEEK. “Analyzing trends, predicting violations and abnormal behaviors can also guide organizations when planning and executing critical strategic and operational decisions, and become especially critical for customer-facing and revenue-generating apps.”
The new outlier detection capability is powered by an algorithm that can analyze thousands of data streams with a single query, determine baselines and identify outliers in real-time, the company said.
Purpose-built visualization highlights abnormal behaviors and provides visibility into key performance indicators (KPIs) and key risk indicators (KRIs).
In addition, real-time alerts help teams fix critical issues, such as a sudden rise in response time or unusual spike in network traffic, as they are detected.
Users can customize simple input parameters to manage sensitivity, baselines, direction and duration of change, the company said.
The predictive analytics capability extends and complements 0utlier detection by predicting future KPI violations and abnormal behaviors through a linear projection model.
The ability to observe violations that may occur in the future, such as declining transaction volumes, rise in latency, and decrease in available application resources, helps users address issues in advance of business impact.
“Sumo Logic’s service is constantly upgraded with new features and capabilities, and Outlier Detection & Predictive Analytics represents the latest for us as the leading end-to-end machine data analytics service on the market,” Azam said. “We first introduced pattern detection through LogReduce, then we added anomaly detection capabilities and transaction analytics, and now we’re moving the ball even further with Outlier Detection and Predictive Analytics. You can expect continued innovation and sophistication in our analytics capabilities as we move toward helping customers better manage and secure their applications and services.”