AIOps platform

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 o11y platform delivers AI and machine learning that provide context, meaningful alerts, illuminate patterns and enable foresight and automation.

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.

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.

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 prevent downtime.

Budget planning and resource management: Infrastructure components that have lifetimes 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.