Top AIOps Tools That Use Machine Learning—and How They Compare

As modern IT environments grow more complex, businesses increasingly rely on machine learning in IT operations to reduce noise, predict failures, and automate responses.

AIOps (Artificial Intelligence for IT Operations) platforms are now essential tools for teams managing cloud-native, hybrid, or large-scale infrastructure. In this blog, we compare some of the top AIOps tools using machine learning to enhance visibility and streamline operations.

Dynatrace

Dynatrace is widely known for its full-stack observability capabilities and Davis, its AI engine. Using powerful anomaly detection and root-cause analysis, Dynatrace helps teams instantly pinpoint issues across applications, infrastructure, and user experience layers.

Its strength lies in its automatic dependency mapping, which provides precise context for incidents. For businesses seeking all-in-one observability with intelligent insights, Dynatrace stands out.

Splunk IT Service Intelligence (ITSI)

Splunk ITSI leverages ML-based analytics to reduce alert noise and highlight events that matter most. The tool excels in creating service health scores and detecting anomalies before they impact users.

Its integration with Splunk’s broader ecosystem makes it ideal for large enterprises already using Splunk for log analytics. ITSI’s customizable dashboards give IT teams clear visibility into performance patterns and emerging threats.

Moogsoft

Moogsoft is one of the earliest AIOps platforms, designed specifically to improve event correlation and incident management. Using machine learning in IT operations, Moogsoft identifies patterns, clusters related alerts, and helps teams quickly determine the root cause of issues. Its platform is lightweight, easy to integrate, and well-suited for organizations adopting AIOps for the first time.

Datadog AIOps (Watchdog)

Datadog Watchdog automatically identifies performance anomalies across applications, hosts, and services. Its ML-driven insights reduce the time spent on troubleshooting by highlighting unusual spikes, latency increases, or infrastructure bottlenecks. Datadog’s strength lies in its seamless integration with hundreds of cloud and DevOps tools, enabling unified monitoring and intelligent automation.

New Relic Applied Intelligence

New Relic uses AIOps to detect anomalies, correlate incidents, and reduce noise across dynamic cloud environments. With its ML-driven alerting and guided incident response, teams can quickly resolve issues before they affect users. New Relic’s open-source-friendly ecosystem is a plus for teams using multiple toolsets.

Which AIOps Tool Is Right for You?

Choosing the right tool depends on your ecosystem and goals. Organizations needing deep full-stack observability may prefer Dynatrace or Datadog, while those focused on event correlation might lean toward Moogsoft. For enterprises already using Splunk or New Relic, their AIOps modules integrate naturally into existing workflows.

No matter the choice, adopting machine learning in IT operations helps IT teams work smarter, reduce downtime, and deliver more reliable digital experiences.

Also read: Data on Wheels: Using Consumer IoT to Create Smarter, Safer Driving Experiences

Author - Purvi Senapati

Having accumulated over three years of expertise in crafting blogs and content marketing materials, Purvi is a motivated self-starter. Her writing style is characterized by its clarity and adaptability, infused with impactful language. Her insatiable appetite for knowledge, coupled with a talent for generating innovative concepts, equips her to produce meticulously crafted, captivating content that caters to diverse clientele.