MicroAI™ Brings Machine Learning Libraries to IT Administrators
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MicroAI™ Brings Machine Learning to IT Administration

MicroAI™ Brings Machine Learning to IT Administration

19 Feb 21

it-administration

MicroAI™ Brings Machine Learning to IT Administration

MicroAI™ Brings Machine Learning to IT Administration

An important aspect of an IT administrator’s job is to monitor the status of a wide variety of devices and systems contained within a typical IT ecosystem. The administrator often needs to actively monitor real-time data displayed via various types of charts, graphs, data displays, etc. Monitoring these sources of information is critical to being able to maintain an active assessment of system status.

The Challenge

Most of today’s IT ecosystems must meet strict reliability and uptime requirements. Immediate action and remediation are required whenever a system component stops working properly. As the complexity of IT ecosystems continue to evolve, the volume of data that needs to be monitored can increase dramatically. This can put significant stress on IT administrators and create a host of system performance issues.

MicroAI™ and its Machine Learning Library

IT administrators monitor data that is typically time series in nature.  Examples of these data points would CPU utilization, memory utilization, disk I/O, network I/O, power consumption, etc. These data points are normally plotted in a line chart graph where each data point represents a time frame for the data. This type of data is a perfect candidate for application of MicroAI™. MicroAI’s machine learning library can be trained when the systems are operating normally, thereby creating a baseline for normal performance. Once trained, MicroAI™ will continuously monitor the status of every system parameter. Once an anomaly is detected, MicroAI™ sends a real-time alert (email, text notification, etc.) to the IT administrator.

The deployment of MicroAI™ helps reduce IT administer workloads associated with constant—manual—surveillance of high volumes of data sources. With proper tuning, the MicroAI™ algorithms will provide exceptional performance in the areas of system monitoring, issue detection, self-learning issue resolution, and cyber threat detection.

For most IT administration use cases, computing power is not a limiting constraint. This means that administrators can take advantage of the network features of MicroAI™ to distribute elements of control to different nodes across the network. MicroAI™ can work as a living organism that resides on many corners of the whole system and can be scaled to grow with the ecosystem. Not only is the load more evenly distributed, but the rigidity of the entire AI system is also significantly increased. MicroAI™ will continue to work even if some parts of the system fail.

MicroAI™ provides IT administrators with a cutting-edge, AI-enabled, approach to IT ecosystem management. An approach that improves performance, reduces human workload, and reduces cost.