Our Data Scientists not only give you a good handle on the hot button issue(s) at any given time, best way to react to a situation, but also predict incidents even before they happen and prevent or give automated solution when it happens.What can we do for you?
Multiple sources can create a flood of noisy alarms. Our ITOA solution intelligently clusters the IT alarms/alerts and correlates into high-level related incidents know as ‘situations’. Managing one or two situations is better than trying to manage thousands of disparate alerts. This incident correlation reduces the noise and helps spot critical issues faster.
Manual prioritization is subjective and often devolves into FIFO which is not optimal.
Our ITOA solution automatically prioritizes the incidents (or situations, once the incidents are correlated) by analyzing a comprehensive history of:
This will help your IT Operations to solve the problems that really matter.
Once the incidents are correlated and a score is assigned, our ITOA solution applies ML (Machine Learning) techniques to
Machine Learning Algorithms are also used to generate Bayesian Networks for Incident Duration Prediction.
Our ITOA solution applies machine learning to automatically sort through the massive volumes of log messages. It quickly and efficiently finds and identifies messages that are truly relevant, applies powerful analysis algorithms that self-learn over time, and leverages the knowledge of experts, enabling it to provide fresh insights to find the root cause of the problem every time. These insights can be applied to accelerate problem resolution and help prevent future issues.
The above can be applied for
The demands on modern IT infrastructure is such that reacting to an incident is too late. Emerging need is to predict incidents even before they happen.
Our ITOA solution applies Machine learning techniques in real-time from multiple event sources to analyze and detect anomalies before they become systemic and are reported by end users. This has proved 75% reduction in MTTD (Mean Time To Detect).