LogicMonitor’s AIOps platform enables businesses to see what’s coming before it happens. For engineers, this includes spending less time troubleshooting and more time innovating. AIOps delivers AI and machine learning that provide context, meaningful alerts, illuminate patterns, and enable foresight and automation.
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.
Enabling streamlined operations with AIOps
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 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.
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.
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.
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 OPTIMALPLUS
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 AGIO
Proactive Monitoring with AIOps
See our AIOps Early Warning System in action with a quick on-demand demo highlighting dynamic thresholds, root cause analysis, and anomaly detection for all of your infrastructure and applications.
Increase IT efficiency
Customizing thresholds can be time-consuming and 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 and enabling you to increase your monitoring ROI.
Dynamic thresholds enable teams to understand expected performance and where performance deviates from what’s normal and 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.
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.
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.
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.
AIOps frequently asked questions
- What is AIOps?
AIOps which stands for Artificial Intelligence for IT Operations, is a method for analyzing and displaying data for IT teams based on machine learning algorithms. The AI used in AIOps is often based on historical patterns coupled with current learned data trends.
- Is LM’s AIOps really using AI?
Yes. LogicMonitor’s AIOps goes beyond simple machine learning and pattern detection to learn and report based on individual relationships within each company’s tech stack.
- What is root cause analysis?
Root cause analysis is the process of finding the core of an issue that caused a chain reaction effect ending in problems.
- What is anomaly detection?
Anomaly detection is the identification and notification of outliers within gathered datapoints. An anomalous datapoint is something that significantly deviates from a normal data range without reason.
- What are dynamic thresholds?
Dynamic thresholds are dataranges that show an acceptable changing range of datapoints based on similar historical factors.
- What is machine learning?
Machine learning is the use of algorithms that improve automatically through historical analysis and experience.
Root cause analysis immediately finds the core of your cloud-related issues, drastically reducing MTTR and allowing you more time to innovate.
Alert on anomalous log patterns with AIOps by using LogicMonitor’s continuous profiling algorithms. These algorithms learn automatically, limiting the need for complex manual analysis.
Application performance monitoring
Proactively identify and resolve issues within your deployment before they become problems allows DevOps teams to create in a more agile environment.
Only be alerted when critical network devices are out of their normal operating range, keeping the spam out of your inbox, and allowing focus for critical infrastrucure improvements.