In this highly dynamic environment, organizations are looking for ways to innovate and manage resources efficiently. In the first part of the two-part blog series, we saw how organizations handled incidents without an AIOps solution and how long it took to resolve that incident — a scenario representing different steps to resolve an incident. In the second part of the two-part blog series, we look at how organizations were able to handle incidents after deploying AIOps.

As per Gartner, Hyper Automation is the top strategic technology trend for Enterprises. “The shift towards hyper automation will be a key factor enabling enterprises to achieve operational excellence, and subsequently cost savings, in a digital-first world,” said Cathy Tornbohm, Distinguished Research Vice President at Gartner. Businesses want to enable employees to make better decisions in the most cost effective way.

Organizations are always looking for new ways to innovate and reduce costs and allocate resources more efficiently. In this blog post, we will look at how enterprises handled incidents before and after deploying AIOps.

People’s involvement has been inevitable with log management despite advancements in ITOps. Log management at a high level collects and indexes all your application and system log files so that you can search through them quickly. It also lets you define rules based on log patterns so that you can get alerts when an anomaly occurs. Log management analytics solution leveraging RDA has been able to detect anomalies and aid predictive models over a machine learning layer.

Robotic data automation (RDA) is designed to optimize IT functions for a broad spectrum. It is the next generation data automation technology that is specifically designed to bring efficiencies to multiple IT functions including CXO/IT leaders decision making, IT Ops, Helpdesk, Salesforce.com, ServiceNow and other applications used by enterprises.