Through the last several decades, organizations have deployed a significant amount of monitoring tools and instrumentation in hopes of providing operations teams with greater insight into problems occurring in their environment. However, with the massive volume of events and the velocity at which they grow, this additional information is evolving into additional noise. This makes locating issues much more difficult and adds operational risk to the teams trying to quickly resolve the underlying problems.
Organizations do not have many options today to sort through their environmental noise. Turning off the monitoring system results in a loss of visibility; and most organizations do not have the budget to continuously add more resources dedicated to sifting through the data. Grok AIOps noise reduction and event clustering techniques will help users reach a proactive position regarding issue resolution instead of reacting to endless emergencies and constantly fighting fires.
Grok uses advanced machine learning event clustering to reduce noise in your environment. With Grok’s plug and play real-time machine learning model and Intelligent Integration, Grok quickly ingests real-time event feeds and builds sophisticated representational models of your complex infrastructure and topology based on multiple dimensions (such as event type, devices, etc.). Grok leverages an iterative, hierarchical machine learning model which provides the best structure for generating optimal event clusters in modern IT and networked environments. These algorithms are based on both semantic grouping and also dynamic time warping to ensure that clustering of events that can happen hours or even days later. From this model, Grok intelligently builds patterns and groups events based on similarity and relationship, significantly reducing the noise.
Grok groups related events indicative of probable root cause or similar underlying cause into a detection. Parent-child relationships are automatically built between the detection and the events. Operational teams can focus on the detection rather than multiple teams and activities being created to chase separate events. Furthermore, with a centralized contextual view, Grok combines, organizes, and displays the detection with related events, timeline, ticketing and change management information to indicate probable root cause and actions to be taken. Operational teams can focus on this information to quickly diagnose and resolve the underlying problem and keep your services and customers up and running.
