15 Best AIOps Platforms: Streamline IT Ops with AI

Artificial Intelligence for IT Operations (AIOps) platforms are becoming invaluable for modern IT teams seeking to optimize workloads and boost efficiency. By leveraging automation, advanced analytics and machine learning algorithms, AIOps solutions empower enterprises to monitor infrastructure proactively, swiftly detect anomalies and reduce disruptive incidents.

However, with the rapid evolution of the AIOps marketplace, selecting the right tool that meets your business needs can prove challenging. Vendors offer varied capabilities and strengths around factors like root cause analysis, cloud monitoring, predictive insights and more.

This comprehensive guide will explore the top 15 AIOps platforms based on their placements in major B2B review platforms. We will analyze the unique pros, cons and highlights of each option to assist you in determining the best fit for your infrastructure and use cases. Let‘s get started!

15 best AIOps platforms

Figure 1 depicts the total number of B2B reviews and average scores for all AIOps solutions on leading review sites G2 and TrustRadius. The tools below are sorted alphabetically.

1. AppDynamics

AppDynamics is a robust application performance monitoring and analysis tool. It delivers real-time insights into critical factors like application performance, user experience, cloud data workflows and infrastructure health.

AppDynamics utilizes several integrated modules including Application Performance Monitoring, Infrastructure Monitoring, Business Performance Monitoring, End User Monitoring and Database Monitoring. Together, these capabilities help track and visualize complex customer journeys.

2. BigPanda

BigPanda is an AIOps-powered event correlation and automation platform. It aggregates and normalizes data from diverse sources like tools, change events and orchestration. This open-box data hub provides a unified view across the IT environment.

3. Datadog

Datadog is a cloud-based data analytics and monitoring solution designed for IT teams, developers and security engineers. It incorporates Watchdog, which performs root cause analysis and acts as an assistant for users.

Beyond application performance management (APM), Datadog provides robust capabilities for security monitoring, log analysis, network analytics and real user monitoring. Its cloud-native architecture supports full-stack observability.

4. Dynatrace

Dynatrace serves as an intelligent application performance monitoring (APM) platform enhanced by artificial intelligence. It offers a comprehensive suite of modern IT operations services including automation, infrastructure monitoring, cloud oversight and digital experience analytics.

The solution enables end-to-end monitoring across the full IT stack including networks, processes and hosts. It also incorporates functionalities for log analysis, information visualization and data querying to derive actionable insights. Additionally, Dynatrace provides guidance to optimize performance and quickly resolve issues.

5. IBM Instana

IBM Instana serves as the core AIOps component of IBM’s product portfolio. It offers full-stack observability capabilities with a specialized focus on enhancing application performance monitoring (APM) for cloud-native and microservices architectures.

Instana excels at expediting and automating CI/CD pipelines regardless of where applications are deployed. It ingests performance data through observability across diverse cloud environments. The platform‘s AI-powered analytics then generate actionable insights to identify root causes and trigger intelligent automation.

6. LogicMonitor

LogicMonitor is a SaaS-based solution designed for monitoring complex IT infrastructures and networks to ensure availability and reliability. With integrated artificial intelligence powering automation, LogicMonitor stands out as an enterprise-ready AIOps platform.

7. ManageEngine OpManager

ManageEngine OpManager centralizes IT data analytics, reporting and visualization. This helps IT teams make data-driven decisions and gain more actionable insights into key business KPIs.

8. Micro Focus OpsBridge

MicroFocus OpsBridge performs as a service for call monitoring, event management and data consolidation. By ingesting signals from disparate systems, it improves visibility across the IT environment.

9. Moogsoft

Moogsoft serves as an enterprise, cloud-native AIOps solution for IT Operations and DevOps teams. Based in San Francisco, this data management and alert platform aims to streamline operations by reducing noise, prioritizing events, minimizing escalations and enhancing monitoring.

10. Netreo

Netreo delivers a unified observability platform with a centralized dashboard presenting a full-stack view of systems, applications, infrastructure and user experience. It leverages AI and machine learning for automatic dependency mapping, event correlation and detecting anomalies.

11. New Relic One

The New Relic One observability platform is well-regarded for its simplified, cloud-native approach to monitoring and optimizing the entire software stack. It delivers robust visibility into distributed services and applications across environments. The Telemetry Data Platform enables real-time aggregation and visualization of operational data.

12. PagerDuty

PagerDuty enhances visibility and reduces noise to help IT teams achieve greater uptime, ROI and business continuity. This leading AIOps solution excels at monitoring and analyzing data, logs, networks and digital experiences. It provides capabilities like automated incident response, alerting, orchestration, event management and advanced operational analytics.

13. Sematext Monitoring

Sematext Monitoring serves as an observability solution for collecting metrics and events across the full technology stack. With over 100 integrations, Sematext makes it easy to set up alerts, detect anomalies and gain end-to-end visibility across applications, servers, containers, infrastructure and more.

14. Splunk Enterprise

Splunk Enterprise revolves around the notion that “data is everything” for modern IT teams. This platform simplifies data collection through auto-configuration across cloud environments. It also enables efficient visualization, indexing and analysis of ingested data.

15. Zenoss Cloud

Zenoss Cloud provides a robust SaaS-based monitoring service and AIOps platform. It helps technology teams gain deep visibility into data health and performance. Zenoss offers strong analytics without requiring agents – instead it uses a collector to forward system data to a centralized server for processing.

Key factors to evaluate in AIOps solutions

AIOps platforms consist of several integral components working together to enable AI-powered automation and insights. Evaluating vendors based on these capabilities can help determine the right solution for your needs. Here are six key aspects to analyze:

1. Visibility

This refers to the data collection and insight generation capabilities. Aspects like integrations, breadth of data sources and processing should be assessed.

2. Monitoring & Management

Evaluate automation, anomaly detection, alerting and other features used to monitor and manage the stack. Prioritize must-have capabilities.

3. Performance

Review how the platform analyzes and optimizes system efficiency, resources and bottlenecks.

4. Functionality

Consider the algorithms leveraged, integrations available and other functionalities needed to address your specific IT Ops challenges.

5. Issue Resolution

Assess the tool‘s ability to swiftly and accurately detect, diagnose and resolve incidents through root cause analysis, correlation and anomaly detection.

6. Analysis

Examine the visualization formats, predictive analytics and other analytical features offered to contextualize data and provide actionable insights.

How to select the right AIOps platform

Choosing the optimal AIOps solution requires aligning it with your infrastructure and requirements. For instance, you may want robust root cause analysis or infrastructure monitoring capabilities. Follow these tips to identify top contenders:

• Clearly identify your must-have use cases and objectives
• Shortlist tools that meet your needs based on their pros/cons
• Reach out to vendors for demos and free trials
• Test anomaly detection, ease of integration etc. during evaluations
• Consider your scale – larger firms often need more advanced AI capabilities
• Review integrations with your existing stack
• Choose an option that perfectly matches your current and future needs

Conclusion

AIOps platforms empower enterprises to leverage data, automation and artificial intelligence to optimize IT operations management. With capabilities ranging from predictive insights to noise reduction, these tools provide immense value.

However, not all vendors excel equally across the key components like monitoring, analytics and issue resolution. By clearly identifying your infrastructure and requirements, analyzing the top solutions‘ pros and cons, and thoroughly evaluating via demos/trials, you can determine the ideal AIOps partner for your needs.

We hope this guide provides a comprehensive overview of the AIOps landscape and wish you the best in streamlining your IT operations!