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The top AIOps tools and platforms to consider in 2025
As AIOps approaches become more common among IT teams, the AIOps tools and platforms market has expanded. Compare leading options to decide which fits your needs.
New technologies are rapidly outpacing the capacity of IT teams and administrators to manage systems manually. To address this gap, organizations are turning to AIOps platforms, which use AI and machine learning to automate IT operations, perform predictive maintenance and improve system performance.
AIOps tools can help IT teams better understand their infrastructure and resolve problems more quickly and accurately. They can also foster better communication during issue resolution, promoting collaboration between IT and business departments. But despite these benefits, adopting an AIOps approach can be complex, posing challenges such as integration with existing observability and monitoring tools.
The key to success is selecting an AIOps tool that fits the organization's specific IT operations needs. To do so, IT leaders should begin by identifying their team's main challenges and skill levels, as well as the organization's infrastructure requirements. This strategic approach aligns platform choice with operational goals and maximizes the value of the business's IT investment.
Understanding how AIOps works
AIOps platforms collect enormous amounts of data, which machine learning algorithms then process to find patterns, pinpoint system-wide issues and predict impacts. Administrators can use AIOps platforms to correlate extensive alert, event and topology data for more effective incident response and to reduce manual error.
Centralized dashboards are a key feature of AIOps. They enable IT teams to track and analyze performance trends over time, including divergences that could indicate system degradation. AIOps platforms also reduce noise through rule-based filtering, which prioritizes critical events and minimizes unnecessary alerts. This, in turn, boosts overall IT efficiency by reducing fatigue and helping ops staff address important issues more quickly.
How to choose the right AIOps platform
Deciding which AIOps platform is the best fit requires assessing several factors.
Define objectives and establish structure
The process should begin by identifying the IT operational pain points that need resolution, such as insufficient network and application monitoring or inconsistent asset maintenance. For example, automating configuration changes across multiple network devices from different vendors -- rather than having engineers do so manually -- is a tangible way that AIOps can address inefficiencies.
At this stage, IT leaders should also outline clear objectives for adopting AIOps and describe how doing so aligns with their organization's specific requirements and long-term operational goals. Establishing a clear administrative structure for managing and implementing AI initiatives is an important part of this process.
Prioritize data integrity
Information integrity is another critical element, as data quality is the foundation of effective automation. Choosing the right data sources is the only way to generate reliable, consistent and actionable insights.
Take a modular approach
A modular infrastructure foundation can simplify AIOps adoption by providing the flexibility needed to integrate new tools and adapt to evolving IT needs. The ability to mix and match tool sets ensures that the platform can accommodate future tech developments and strategy shifts.
Plan ahead
AIOps adoption positions IT leaders to meet new scalability challenges and support new technologies as their organizations expand. Set clear goals and ensure extensions are in place for must-have and emerging technologies, from cloud services and virtual deployments to software-defined networks and edge data centers.
Top 9 AIOps tools and platforms
This curated list of AIOps tools is based on extensive IT research; input from experienced network engineers; and insights from Informa TechTarget surveys and long-term analysis. The following platforms are available for Linux, Unix, Windows and macOS.
Tools are unranked and listed in alphabetical order.
1. AppDynamics
AppDynamics, a Cisco product, works best for performance monitoring and maintaining business-critical applications. It offers dashboards and real-time analytics for application health, performance and availability, and correlates deduplicated and contextualized event data.
Since Cisco's acquisition of Splunk in 2024, it has started to rebrand AppDynamics as Splunk AppDynamics, highlighting its intent to merge both products -- although Cisco's integration plans suggest more product changes might be in store.
Currently, the tool is still offered as a standalone product with a variety of editions and both monthly and annual payment plans. It's also available as an add-on to Splunk's observability platform, for $6 per CPU core, per month.
2. BigPanda
BigPanda excels in data analytics, using aggregation, its proprietary Topology Mesh and correlation algorithms to consolidate alerts, events and topology data. This approach reduces noise and enables efficient incident response. Main features include alert and ticket generation, orchestration and virtual war rooms for team collaboration.
BigPanda does not disclose its pricing. Teams interested must contact sales for demos and pricing information.
3. Datadog
Datadog is ideal for monitoring cloud applications and automating infrastructure monitoring and log management. Its standout feature, Watchdog, correlates diverse data for root cause analysis and uses forecast algorithms to detect abnormal behavior. Watchdog works across VMs, cloud deployments and serverless functions.
While Datadog offers a free tier with basic monitoring capabilities, advanced features like Watchdog are only available as part of its paid plans. These include Pro, starting at $15 per host, per month, and Enterprise, starting at $23 per host, per month. Datadog also offers DevSecOps tiers and a free 14-day trial.
4. Dynatrace
Dynatrace works best for AI-powered automation. The platform's custom tool, OneAgent, offers a set of specialized services configured specifically for the subscriber's monitoring environment. OneAgent also simplifies Dynatrace deployment, as it eliminates the need to manually configure alerts, dashboards and related instrumentation. The platform supports diverse monitoring approaches for applications, microservices and cloud-native infrastructures.
Dynatrace's pricing includes a full platform subscription licensing model with hourly pricing based on actual use. Dynatrace also offers a 15-day free trial.
5. Ignio
Digitate's Ignio platform assesses system-wide irregularities, automatically remediates problems and provides future-state predictions. It automatically monitors application deployments to detect changes and performs self-healing while analyzing the overall impact on the IT system. But setup and customization require sufficient IT skills to ensure efficient event management and accurate observability parameters.
Ignio does not disclose its pricing. Teams interested must contact sales for demos and pricing information.
6. LogicMonitor
LogicMonitor offers the ability to see various resources in context -- for example, if an organization has workloads in both AWS and Azure VMs -- and troubleshoots using metrics in a single pane. It offers more detail than standard cloud monitoring features. Its AIOps features use machine learning for streamlined metrics analysis from multiple resources and issue remediation, with out-of-the-box setup and management options.
LogicMonitor offers a variety of prices per resource, per month for its monitoring products and features, as well as a 14-day free trial.
7. New Relic AI
New Relic excels at managing and scaling incident response cycles by providing an integrated view of telemetry, logs, traces and metrics. The platform combines large language models with its data platform to provide insights for faster issue resolution. Administrators can access dashboards to automatically monitor applications and infrastructure, with the ability to dynamically adjust widgets on templates.
New Relic offers a free tier, as well as paid standard, pro and enterprise tiers. Teams must contact sales for specific pricing.
8. PagerDuty
PagerDuty AIOps offers comprehensive automation capabilities for fast incident response, as well as root cause analysis and single-pane-of-glass observability to facilitate monitoring and remediation. The platform also reduces alert noise by grouping events and consolidating alarms.
PagerDuty AIOps is an add-on feature within the PagerDuty platform. The feature is priced based on event consumption, starting at $799 per month (or $699 per month when billed annually). A trial option is available for both current and prospective customers.
9. Splunk
Splunk's observability tool -- which now includes AppDynamics capabilities, following Cisco's acquisition of Splunk in 2024 -- uses AI and machine learning algorithms to predict issues, detect anomalies and analyze sources to pinpoint root causes.
Administrators can use the Splunk dashboard to track real-time and historical performance by integrating diverse data sources, including servers, applications, networks and sensors. Splunk has an active user community, with many options for applications, integrations and extensions to boost platform functionality.
Splunk offers a variety of free trials and pricing options, but IT teams must contact sales for pricing details.
Kerry Doyle writes about technology for a variety of publications and platforms. His current focus is on issues relevant to IT and enterprise leaders across a range of topics, from nanotech and cloud to distributed services and AI.
