Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

CloudFabrix

How to Easily perform Data Masking of Social Security Numbers (SSNs) in Log files or Events in 4 Ways using Data Bots

This blog post covers 4 data masking techniques and data obfuscation techniques that you can implement with Robotic Data Automation (RDA) to mask or hide sensitive data or personally identifiable information (PII) like social security numbers (SSNs) that may have crept unintentionally in logs or events.

How organizations handled incidents before and after deploying AIOps - Part 2

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.

Face Detection using Robotic Data Automation(RDA) in 4 mins

Perform real-time face detection through a webcam/recorded video using Robotic Data Automation(RDA) in 4 mins. This method is so quick that we can start getting real-time reports on the faces of every person/object in the video without much performance overhead. The best part is it's a low code tool. Intriguing enough?
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Robotic Data Automation (RDA): Top 5 emerging opportunities for CXO/IT leaders

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.

How organizations Handled Incidents Before and After Deploying AIOps - Part 1

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.

Robotic Data Automation (RDA): Reducing Costs and Improving Efficiencies of Your Log Management Investment

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.

Transform your Data Center with Confidence | Joint Webinar by CloudFabrix and Verge.io

Verge.io is partnering with CloudFabrix, a leader in artificial intelligence for IT operations, to chat about why software-defined everything is the way to go. This is a great opportunity to learn how to transform your current data center operations using the latest technology and intelligence. Here’s what we’ll cover: – How artificial intelligence and data center virtualization operating systems work together to change the thinking around traditional data centers.

RDA Addresses Top 5 Enterprise IT Challenges faced by CXO/IT Leaders

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.

Is Data the biggest barrier for AIOps adoption?

Much like oil, data that is available in a raw form is not useful at all. It has to go through various steps before AI/ML could touch it and derive valuable!! Check out the latest video by Shyam Sreenivasan, where he talks about DataOps and why you should automate your data pipelines to run AIOPS at scale.