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AIOps Across 17 Vendors: What the Data Shows

Dennis Drogseth

One of the benefits of doing the EMA Radar Report: AIOps- A Guide for Investing in Innovation was getting data from all 17 vendors on critical areas ranging from deployment and adoption challenges, to cost and pricing, to architectural and functionality insights across everything from heuristics, to automation, and data assimilation.

Listen to EMA's Dennis Drogseth on the AI+ITOPS Podcast


Administration and Deployment

In the area of deployment and administration, EMA found that on average AIOps vendors indicated between 1-1.5 full-time employees (FTE) were required for ongoing administration in an enterprise with about 10,000 employees. This didn’t include initial deployment or any significant extension in breadth of coverage or functionality.

In 31 interviews, these estimates were generally borne out. Three vendors at the high end estimated between 2.5 and 3 FTEs, whereas the three vendors at the low end estimated between less than 0.5 FTEs.

Heuristics

The great majority of AIOps platforms have heuristics that can "learn" their environments dynamically, without added administrative intervention. On average, they can do this in a little more than one week for 5,000 managed entities.

EMA then asked vendors to weight their AI/ML heuristics on a scale from 0-2, with 2 being a featured heuristic value, 1 being present, and 0 being absent. The top 10 heuristics getting a 2 weighting were:

1. Correlators

2. Anomaly detection

3. Machine learning and baselining for event pattern recognition

4. Topology-based analytics

5. Prescriptive analytics

6. Predictive algorithms

7. Comparators

8. Streaming analytics

9. Optimization algorithms

10. Object-based modeling

Data Assimilation

On average, AIOps vendors could assimilate between 1 million and 10 million metrics within five minutes. When we asked about what data types were in play, we saw:

1. Events (performance related)

2. Time Series

3. Log files

4. Events/ Time Series (security related)

5. Transaction (application performance)

6. Configuration/topology

7. Unstructured data

8. Agent data (systems)

9. Byte code instrumentation

10. Comma delimited files /CSV files

Third-party toolset integration

Significantly, all 17 vendors have some level of third-party toolset integration out of the box, or in parallel, none claim to do "all their own monitoring." In fact, the average AIOps platform has supported integrations for more than 50 different third-party toolsets, with four vendors indicating 100 or more.

These integrations can have powerful political and practical advantages, easing stakeholder reluctance by eliminating the need to break away from their existing tools completely. Additional values include toolset consolidation as IT organizations begin to observe redundancies while also realizing which toolsets are most valuable.

The most common toolset integrations were application performance monitoring (APM) tools tied with CMDBs or extended configuration management systems. Service desk integration for trouble ticketing followed and third-party event management systems came in fourth. Automation integrations were also key, with IT process automation (runbook), and workflow across IT in the lead.

A few use-case views

We had three use-case scenarios. And for each use case we examined a number of factors ranging from domain reach, stakeholders supported, real-time data currency, and heuristics to enable not only awareness of anomalies, but predictive and prescriptive recommendations. Vendors were positioned separately on a per-use-case basis.

When we asked about the top benefits for incident, availability and performance management all vendors led with the following six items, which were also born out in deployment interviews:

■ Faster time to repair problems

■ Proactive ability to prevent problems

■ Improved OpEx efficiencies within IT

■ Less time spent writing rules

■ Real-time insights and historical trends on IT services

■ Reduction/consolidation, minimalization of tools

When we asked what changes each vendor could trace for change impact and capacity optimization, we got the following top five:

■ System configuration service impact analysis

■ Application release changes

■ Service impact analysis (in general)

■ Virtualized infrastructure service impact analysis

■ Containers and microservices service impact analysis

For business impact and IT-to-business alignment, we asked about relevant data sources and saw these as the top five:

■ Enterprise operations data

■ IT warehouse for advanced trending

■ Business application owner data

■ Executive dashboard

■ Security/audit compliance systems

To wrap up

This is just a taste of the data that emerged from our AIOps Radar research. The report contains considerably more detail, while still being a condensation of 105 data-rich slides.

Doing this has been an adventure for me, for EMA as a whole, and I believe for the vendors involved, as well. I do hope you can check out the report and see for yourself as to why.

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AIOps Across 17 Vendors: What the Data Shows

Dennis Drogseth

One of the benefits of doing the EMA Radar Report: AIOps- A Guide for Investing in Innovation was getting data from all 17 vendors on critical areas ranging from deployment and adoption challenges, to cost and pricing, to architectural and functionality insights across everything from heuristics, to automation, and data assimilation.

Listen to EMA's Dennis Drogseth on the AI+ITOPS Podcast


Administration and Deployment

In the area of deployment and administration, EMA found that on average AIOps vendors indicated between 1-1.5 full-time employees (FTE) were required for ongoing administration in an enterprise with about 10,000 employees. This didn’t include initial deployment or any significant extension in breadth of coverage or functionality.

In 31 interviews, these estimates were generally borne out. Three vendors at the high end estimated between 2.5 and 3 FTEs, whereas the three vendors at the low end estimated between less than 0.5 FTEs.

Heuristics

The great majority of AIOps platforms have heuristics that can "learn" their environments dynamically, without added administrative intervention. On average, they can do this in a little more than one week for 5,000 managed entities.

EMA then asked vendors to weight their AI/ML heuristics on a scale from 0-2, with 2 being a featured heuristic value, 1 being present, and 0 being absent. The top 10 heuristics getting a 2 weighting were:

1. Correlators

2. Anomaly detection

3. Machine learning and baselining for event pattern recognition

4. Topology-based analytics

5. Prescriptive analytics

6. Predictive algorithms

7. Comparators

8. Streaming analytics

9. Optimization algorithms

10. Object-based modeling

Data Assimilation

On average, AIOps vendors could assimilate between 1 million and 10 million metrics within five minutes. When we asked about what data types were in play, we saw:

1. Events (performance related)

2. Time Series

3. Log files

4. Events/ Time Series (security related)

5. Transaction (application performance)

6. Configuration/topology

7. Unstructured data

8. Agent data (systems)

9. Byte code instrumentation

10. Comma delimited files /CSV files

Third-party toolset integration

Significantly, all 17 vendors have some level of third-party toolset integration out of the box, or in parallel, none claim to do "all their own monitoring." In fact, the average AIOps platform has supported integrations for more than 50 different third-party toolsets, with four vendors indicating 100 or more.

These integrations can have powerful political and practical advantages, easing stakeholder reluctance by eliminating the need to break away from their existing tools completely. Additional values include toolset consolidation as IT organizations begin to observe redundancies while also realizing which toolsets are most valuable.

The most common toolset integrations were application performance monitoring (APM) tools tied with CMDBs or extended configuration management systems. Service desk integration for trouble ticketing followed and third-party event management systems came in fourth. Automation integrations were also key, with IT process automation (runbook), and workflow across IT in the lead.

A few use-case views

We had three use-case scenarios. And for each use case we examined a number of factors ranging from domain reach, stakeholders supported, real-time data currency, and heuristics to enable not only awareness of anomalies, but predictive and prescriptive recommendations. Vendors were positioned separately on a per-use-case basis.

When we asked about the top benefits for incident, availability and performance management all vendors led with the following six items, which were also born out in deployment interviews:

■ Faster time to repair problems

■ Proactive ability to prevent problems

■ Improved OpEx efficiencies within IT

■ Less time spent writing rules

■ Real-time insights and historical trends on IT services

■ Reduction/consolidation, minimalization of tools

When we asked what changes each vendor could trace for change impact and capacity optimization, we got the following top five:

■ System configuration service impact analysis

■ Application release changes

■ Service impact analysis (in general)

■ Virtualized infrastructure service impact analysis

■ Containers and microservices service impact analysis

For business impact and IT-to-business alignment, we asked about relevant data sources and saw these as the top five:

■ Enterprise operations data

■ IT warehouse for advanced trending

■ Business application owner data

■ Executive dashboard

■ Security/audit compliance systems

To wrap up

This is just a taste of the data that emerged from our AIOps Radar research. The report contains considerably more detail, while still being a condensation of 105 data-rich slides.

Doing this has been an adventure for me, for EMA as a whole, and I believe for the vendors involved, as well. I do hope you can check out the report and see for yourself as to why.

Hot Topics

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...