Sumo Logic Showcases Next Generation Operational and Security Analytics Solutions at AWS re

Invent 2016

LAS VEGAS, NV--(Marketwired - Nov 29, 2016) - Sumo Logic, the leading cloud-native, machine data analytics service, today announced it will showcase next generation operational and security analytics solutions at AWS re:Invent 2016 in Las Vegas Nov. 29 to Dec. 2, 2016. Powered by advanced machine learning technology, these solutions dramatically improve IT operations and security intelligence of modern applications leveraging Amazon Web Services (AWS).

Advanced Machine Learning for Improved IT Operations
According to a recent Sumo Logic report on the 'State of Modern Applications in AWS,' most customer-facing digital services are built on custom modern applications -- relying on a complex application stack with new tiers and technologies, and typically running on cloud platforms like AWS to deliver fast time-to-value and unlimited scalability. But traditional siloed tools for monitoring are ineffective for today's modern applications, requiring full-stack visibility for meaningful troubleshooting.

Only by combining logs, metrics and events in a unified platform can organizations analyze data, perform root-cause analysis, and monitor modern apps and infrastructure in real-time. Sumo Logic's Unified Logs and Metrics (ULM) platform is the industry's first to natively ingest, index and analyze logs, metrics and event data together in real-time. Through machine learning-based analysis of patterns, Sumo Logic provides users with actionable and immediate insights into problems with their system as well as a path to solve it. New advanced capabilities released include:

• Industry's first correlation and visual overlay of logs and metrics: Sumo Logic's innovative dashboards enable customers to easily do ad-hoc analysis, and visually integrate and correlate logs and time-series metrics quickly, identifying issues and reducing troubleshooting times.
  
  
• Comprehensive outlier detection for logs and metrics: The Sumo Logic solution now extends Outlier Detection to time-series metrics based machine data. Outlier Detection is powered by a unique algorithm that can analyze thousands of data streams (logs or metrics) with a single query, determine baselines and identify outliers in real-time. Outlier Detection also provides purpose-built visualization, highlighting abnormal behaviors and giving operations visibility into the behavior of critical KPIs (Key Performance Indicators).