AIOps Platform

Our AIOps platform, powered by LM Intelligence, enables businesses to see what’s coming before it happens. For engineers, this includes spending less time troubleshooting and more time innovating. LogicMonitor’s LM Intelligence will deliver AI and machine learning that provide context, meaningful alerts, illuminate patterns, and enable foresight and automation.

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The AIOps Early Warning System

LogicMonitor’s Early Warning System will detect the warning signs and symptoms that precede issues, such as patterns or anomalies in alerts or performance data, and warn users accordingly. These early warnings will be able to trigger actions, such as integrations and custom scripts, to prevent issue occurrence. By warning users sooner, this Early Warning System will help enterprises prevent outages, saving them time, money, and avoid negative impact on their brands.

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Using LogicMonitor’s AIOps Early Warning System, you can easily see and understand potential issues in the system and be more proactive in resolving them. This is a great feature that is helpful in many use cases across IT infrastructures.

Idan Lerer

Sr. Director, US Operations at OptimalPlus

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The future of IT operations is now

At LogicMonitor, we believe technology should enable businesses to see what’s coming before it happens. For engineers, this includes spending less time troubleshooting and more time innovating. LogicMonitor’s LM™ Intelligence will deliver AI and machine learning that provide context, meaningful alerts, illuminate patterns and enable foresight and automation.

Dynamic Thresholds

Dynamic thresholds use anomaly detection algorithms to detect a resource’s expected range based on past performance and limit alert notifications to those that correspond to values outside of this range (i.e. anomalies). Dynamic thresholds will catch anomalies in metric values, metric rate of change, and even metric patterns (such as a drop in traffic where it isn’t normal). In addition to ensuring that alerts are generated for anomalies, dynamic thresholds can be used to reduce noise where static thresholds aren’t tuned well, so you can ensure your team is focusing on what’s really important.

Increase IT efficiency: Customizing thresholds can be time-consuming & difficult for large environments. With dynamic thresholds, we’ll ensure that alerts are sent for anomalies, eliminating the need for manual management of monitoring thresholds & enabling you to increase your monitoring ROI.

Detect issues sooner: Dynamic thresholds enable teams to understand expected performance and where performance deviates from what’s normal & needs attention before these deviations are caught by traditional thresholds.

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Root Cause Analysis

With root cause analysis, LogicMonitor uses automatically discovered relationships between monitored resources to identify the root cause for triggered alerts and notify users of the originating issue, while preventing notifications for dependent resources in alert. When a core or root device goes down affecting connectivity for downstream devices, Root Cause Analysis (RCA) will identify the originating and dependent resources and subsequent alerts and disable notifications for dependent resources.

Avoid alert fatigue: Users are only notified for the root cause issue allowing them to focus on what’s important without getting overwhelmed by dependent side-effect issues.

Improve MTTR: Alert notifications that identify the root cause and filterable in-app alert data enable your team to zero in on resources that play a key role in outages & more quickly identify and resolve issues.

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Forecasting

LogicMonitor’s data forecasting allows you to predict future trends for your monitored infrastructure, using past performance as the basis. Forecasting is an AIOps tool that is very helpful for issue diagnosis and mitigation and can help you determine whether an alert represents a one-time anomaly, requires immediate attention, or will require attention in the near future.

Proactively prevent issues: Forecasting can help you identify upcoming issues before they trigger alerts, so you can prevnt downtime.

Budget planning and resource management: Infrastructure components that have lifeetimes or capacity associated with them, forecasting based on the predicted health and performance of your monitored devices can provide insight into the timeframe and magnitude of recurring events, as well as upcoming expenses.

Proactive Monitoring with
AIOps Early Warning System
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The benefits of AIOps

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Increase IT efficiency

Customizing thresholds can be time-consuming & difficult for large environments. With dynamic thresholds, we’ll ensure that alerts are only sent for anomalies, eliminating the need for manual management of monitoring & enabling you to increase your monitoring ROI.

Maximize performance

Dynamic thresholds enable teams to understand expected performance and where performance deviates from what’s normal & needs attention. At the same time, teams can ensure that they aren’t receiving alerts for optimized machines that are regularly highly utilized.

Rapidly identify issues

Users are only notified for the root cause issue allowing them to focus on what’s important without getting overwhelmed by dependent side-effect issues.

Improve MTTR

Alert notifications that identify the root cause and filterable in-app alert data enable your team to zero in on resources that play a key role in outages & more quickly identify and resolve issues.

Prevent downtime

The AIOps early warning system will detect the warning signs and symptoms that precede issues, such as patterns or anomalies in alerts or performance data, and warn users accordingly. These early warnings will be able to trigger actions, such as integrations and custom scripts, to prevent issue occurrence.

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Enable digital transformation

Modern enterprises going through digital transformation can’t afford for traditional monitoring to slow them down and prevent them from fully realizing the benefits that digital transformation enables. These enterprises need monitoring that is intelligent enough to help prevent failures across their entire complex and distributed infrastructures.

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Linux machines notoriously generate lots of CPU performance alerts. These machines are being highly utilized intentionally and well within their limits, but it’s creating noise, with LogicMonitor’s dynamic thresholds, we only get alerted when CPU is truly abnormal.

Jason Smith

Associate Director at Agio

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