Data – Most organizations are swimming pretty deep in an endless pool of collected data from applications, infrastructure, and machines.  Even with some of the great tools available, getting through that data into intelligence that is actionable means writing queries.  Writing rules and queries means having a solid idea on what you would like to extract from the data in the first place.  That’s a lot of data, rules creation and human intervention involved.  It’s a problem that Sumo Logic has produced a solution for.  It’s called Anomaly Detection, and its design is a combination that brings together the power of the specialized knowledge that humans bring to the picture, along with machine learning and statistical analysis.  In other words, it can help a business accelerate the value they receive from the insights built on massive amounts of machine data.

Sumo Logic’s Anomaly Detection service gives customers a number of capabilities including:

• Identify imminent security threats
• Detect anomalies across the entire application and operations infrastructure
• Provide user feedback to turn anomalies into known events and classify events with the appropriate severity levels
• Detect any future events that match the patterns associated with past anomalies
• Visually identify and track anomalies, corresponding events and underlying log patterns through an Anomaly Dashboard
• Use LogReduce to rapidly investigate and identify the root cause of these events
• Set alerts for users whenever an important event appears
• Scale anomaly detection to the scope of users’ IT infrastructure

Basically you have an anomaly detecting machine, one that is learning all the time.  The system actively analyzes information, notifies an analyst when something unusual comes up, then that anomaly is categorized for how severe of an anomaly that truly is.  If the anomaly comes up again, the severity that was previously attached to it is presented and that is also complete with all related annotations made when the anomaly first came up.  This is a major enablement as it can be used to track anomalies across systems, servers, networks, applications, and security in a single platform with massive amounts of data.  The value that this brings is real-time analytic data that can help prevent incidents, outages, help with triage, incident response, and forensics – but most importantly it can help an organization shift from being a reactive organization to a predictive state where proactive methodologies are preventing incidents before they become incidents.  Most importantly, this is a system that produces this on an automated basis once its rolling along.

“The ever-growing influx of machine data has created a huge challenge for the CIO’s team. Uncovering and fixing relevant ‘events’ that occur is time-intensive, costly and often impossible,” said Vance Loiselle, CEO of Sumo Logic. “The only way to truly understand what your data is telling you is to use machine learning, not outdated methods such as writing and maintaining rules. Anomaly Detection is a 24x7x365 ‘advance warning system’ that identifies and uncovers the root cause of events, driving rapid time-to-value and supporting critical goals of revenue, brand reputation and customer satisfaction.”

Anomaly Detection is built on Sumo Logic’s Log Management and Analytics service which utilizes LogReduce technology.  This alignment of cloud technology, machine learning, and big data analytics is what sets this solution apart from the pack.  Seamlessly working together, the solution provides a powerful, predictive weapon in the world of advanced business solutions and is ideal for nearly every environment,  but especially those that cannot afford interruptions of service or quality.