AIOps Early Warning System Demo

LogicMonitor’s AIOps Early Warning System uses Artificial Intelligence and Machine Learning-based algorithms to detect warning signs and symptoms preceding issues, enabling IT operations to proactively prevent outages before they occur.

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See our AIOps Early Warning System in action

Today’s modern IT infrastructures are complex. This complexity means failure can occur at any point – from SaaS applications that are critical to employee productivity to the code to the public cloud and everything in between. LogicMonitor’s AIOps Early Warning System helps prevent those failures by surfacing issues before they impact the business.

We’ll cover how to:

Automate alert tuning with Dynamic Thresholds
Track future trends and seasonality with Forecasting
Determine the root of an issue quickly with Root Cause Analysis
Identify deviations from the norm with Anomaly Detection

Intelligently identify issues and warn users accordingly

Root cause analysis identifies the root cause for triggered alerts and notifies users of the originating issue, while preventing notifications for dependent resources in alert.

Trigger actions to prevent issue occurrence

Early warnings will trigger integrations and custom scripts to resolve issues quickly.

Improve MTTR and decrease downtime

With dependent alerts suppressed, teams can identify root cause issues faster and with more confidence.

More resources

Demo

LogicMonitor Platform Demo

Interested in the LogicMonitor platform? Watch this introduction to our SaaS based technology and see how we can level up your monitoring.

Data Sheet

Predict Future Data Trends with Forecasting from LogicMonitor

LogicMonitor’s data forecasting allows you to predict future trends for your monitored infrastructure, using past performance as the basis.

Data Sheet

Avoid Alert Fatigue with Root Cause Analysis from LogicMonitor

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.