AIOps platform

LogicMonitor’s AIOps platform enables businesses to see what’s coming before it happens, and to quickly understand the source of problems when they do. Spend less time troubleshooting and fore time innovating. AIOps delivers AI and machine learning that provide context, meaningful alerts, illuminate patterns, and enable forsight and automation.

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Webinar – How to enable smarter and faster IT operations through AI

Join us for a transformative webinar, “How to enable smarter and faster IT operations through AI,” and discover how artificial intelligence for IT operations (AIOps) and machine learning (ML) can revolutionize your incident management.

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Webinar – AIOps and hybrid observability converge: the road to proactive operations

Watch our on-demand webinar, “AIOps + Hybrid Observability Converge: The Road to Proactive Operations,” where LogicMonitor’s Ranjan Goel, Vice President of Product Management, and Jason Odden, Principal AIOps Strategic Advisor, outline their recommendations for how companies can get the most out of AIOps, avoid risk, and experience tangible benefits from their AIOps strategy.

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Constellation Research Report – LogicMonitor adds AIOps capabilities to its hybrid observability platform

In this analyst report, Andy Thurai summarizes how Edwin AI, LogicMonitor’s new AIOps solution, unites hybrid observability and out-of-the-box machine learning models to prevent outages, increase operational efficiency and accelerate MTTR.

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AIOps for Monitoring Cover

AIOps for Monitoring eBook

As the world continues to embrace automation, IT teams can finally focus on growth and innovation. The goal is to pivot from manual, repetitive work to more abstract and strategic problem solving that can’t be automated. Artificial Intelligence (AI) is leading the charge. This eBook illustrates and defines AIOps, key uses, and trends in development.

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AIOps Constellation

AIOps Q3 2023 Constellation Shortlist

The Constellation ShortList presents vendors in different categories of the market relevant to early adopters. In addition, products included in this document meet the threshold criteria for this category as determined by Constellation Research.

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Edwin AI: AI for Hybrid Observability

LogicMonitor’s enterprise capabilities, powered by Edwin AI, ingest events and seamlessly transform them into episodes to reduce alert noise by up to 80%.

Advanced machine learning techniques automatically identify features in the alert data to correlate the disparate alerts into connected insights based on time, resources involved, environment, and other significant features of the enriched alert data.

Using advanced machine learning and natural language processing (NLP) algorithms, Edwin AI helps ITOps teams effortlessly identify problems, determine the root cause of those problems faster than ever before, and prevent events from exploding into business-critical incidents.

The Edwin AI Difference

Benefits and challenges of containerization for IT operations

Quick Time to Value

Get started with Edwin AI immediately. Edwin AI employs out-of-box ML models with no need for training and includes a seamless integration with LogicMonitor. With multi-tenancy, Edwin AI is completely scalable and MSP-ready with correlations scoped to each tenant, so you can help your customer quickly identify incidents.

The Road Ahead: 4 Ways AIOps Will Build More Resilient IT Operations

Explainable AI

With Edwin AI’s open and customizable machine-learning models, users can define their own correlation models to target the alert and enriched CMDB data that makes sense for their business. In addition, using Adaptive correlation, Edwin AI automatically re-clusters alerts when it identifies a more optimal clustering option. This avoids any delay in escalating insights to ServiceNow.

Pump the Brakes: Some Key Considerations in Your Journey to AIOps

ServiceNow Ready

Edwin AI integrates seamlessly with the ServiceNow Incident module for full bi-directional synchronization of alerts in Edwin AI and incidents in ServiceNow. Edwin AI event episodes are enriched with ServiceNow CMDB information so responders have additional context for rapid problem identification and resolution.

How to Ace Your Behavioral Interview

Adaptable Alert Clustering

Many teams struggle with too many alerts, especially when the same alerts are repeatedly created. Edwin AI clusters alerts using AI-driven methods across time, infrastructure and other items to convert hundreds of alerts into a single episode, which can be used to automatically open an incident in ServiceNow and get enriched with ServiceNow CMDB information to accelerate troubleshooting.

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.

Datapoint Analysis – Metric Correlation for faster RCA

Without Datapoint Analysis, ITOps teams must manually correlate metrics across various resources. Datapoint Analysis automates metric correlation so teams can get to the root cause faster than ever before.

For example, if CPU on a VM is spiking, Datapoint Analysis can show you what other metrics were showing similar behavior immediately before and during the incident. For instance, perhaps memory or network traffic spiked across different VMs. This helps you get to a common root cause faster.

Dynamic Thresholds – Preventive Early Warning System

Increase IT Efficiency and detect issues sooner. Before an issue becomes catastrophic, Dynamic Thresholds can warn you so you can take preventive measures.

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 also reduce noise where static thresholds aren’t tuned well, so you can ensure your team is focusing on what’s really important.

Forecasting – Predict trends for capacity planning

Forecasting helps you proactively prevent issues, budget plan and manage resources so you can prevent downtime and keep your business services operating efficiently. Predict the health and performance of your critical infrastructure and determine whether an issue represents a one-time anomaly, requires immediate attention, or will require attention in the near future.

Dependent Alert Mapping – Suppress dependent alert notifications

With Dependent Alert Mapping, LogicMonitor uses automatically discovered relationships between monitored resources to identify the root cause for triggered alerts and notify users of the originating issue, while suppressing notifications for dependent resources in alert. When a core or root device goes down affecting connectivity for downstream devices, Dependent Alert Mapping will identify the originating and dependent resources and subsequent alerts and disable notifications for dependent resources.

Turn Alerts into Episodes – Alert Clustering

Many teams struggle with too many alerts, especially when the same alerts are repeatedly created. LogicMonitor’s new Edwin AI product, clusters alerts using AI-driven methods across time, infrastructure and other items to convert hundreds of alerts into a single episode, which can be used to automatically open an incident in ServiceNow and get enriched with ServiceNow CMDB information to accelerate troubleshooting.

CPU time showing thresholds outside of the normal range.
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The bottom line: Edwin AI is a no-brainer addition for existing LogicMonitor observability customers

Andy Thurai, Vice President and Principal Analyst Constellation Research

AiOps and dynamic thresholds help our customers with easy-to-understand trend forecasting and proactive insights into their environment

Steve N., Senior Cloud Systems Engineer Ascend Technologies Group

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

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.

Does LogicMonitor use customer data to train their models?

For Edwin AI, the AI engine is pre-trained and the models do not combine data from other customers. In features like dynamic thresholds, we use your historical data but it’s only your data – we do not combine it with other customers’ private data.

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.

What is Edwin AI?

Edwin AI is LogicMonitor’s enterprise AIOPs event management offering. Edwin AI ingests events from the LogicMonitor platform and seamlessly transforms them into episodes. Advanced machine learning techniques automatically identify features in the alert data to correlate the disparate alerts into connected insights based on time, resources involved, environment, and other significant features of the enriched alert data.

What is event clustering?

Event clustering automatically groups event alerts in a correlation into their most succinct form, vastly reducing the time it takes for support teams to reason about the mass of alerts. Effective event clustering can reduce alerts by over 97%.

It’s almost like magic. Let’s chat.