If You Are Looking to Invest in Advanced Analytics for IT, Exactly What Should You Be Shopping For? Part 2: Environments

Dennis Drogseth

EMA published the AIA buyer's guide — directed at helping IT invest in Advanced IT Analytics(AIA), what the industry more commonly calls "Operational Analytics." We created what we called "Shopping Cart Criteria" based on our prior research on AIA adoptions over the past three years. We divided the sixteen shopping cart criteria into three parts: Cost advantage, Environments and Scenarios.

Start with Part 1: Cost Advantage

In this blog, I will address environments. Environments, as indicated by the list below, indicate "where" the AIA solutions we investigated can be applied. All 13 solutions supported cloud for performance, core infrastructure, and application performance and availability. Mainframe had the support of six of our respondents, and IoT and cloud for change and capacity were not yet prime areas of focus for most of the vendors in our guide.

■ Cloud for Performance Management

■ Cloud for Change/Capacity/Cost Optimization

■ Core Infrastructure (Network/Data Center)

■ Legacy/Mainframe

■ Application Performance and Availability Management

■ Internet of Things (IoT)

Cloud for Performance Management

Here we addressed cloud in all its forms, including public cloud, virtualization, microservices and containers, and hybrid cloud environments — with a focus on performance management of IT services and their associated infrastructure. We saw fairly pervasive support for AWS, Azure, Docker and containers, and microservices. Present but less prevalent was support for Google Cloud, IBM Bluemix, Rackspace and Fujitsu Cloud. We also saw integrations with Pivotal Cloud Foundry in support of DevOps initiatives.

Cloud for Change/Capacity/Cost Optimization

Capacity and cost decisions are often joined at the hip in dealing with planning deployment choices across public and private cloud. These decisions can also significantly impact performance. And in fact, in last year's AIA research, optimizing cloud resources generally ranked higher than pure-play performance management in AIA requirements. This unique but critical area was addressed proactively by several of the vendors in this report, especially those with integrations for capacity analytics, and in two cases even cloud-related pricing models.

Core Infrastructure (Network/Data Center)

All of the solutions represented in this report were directed to some degree at cross-domain operational needs. But the approach they took varied dramatically. In evaluating ratings associated with this criterion, we looked for breadth of coverage, relevant stakeholder support, and breadth of capabilities for assessing issues with infrastructure performance both in itself, and in the context of service delivery. 

Legacy/Mainframe

Mainframes in various form factors have hardly disappeared, and many of the world's most critical IT business services are still dependent on mainframe availability and performance. In evaluating this criterion, we looked at the established architectural support for mainframes, as well as the history of the vendor in mainframe support, and its currency in keeping up with new mainframe design and features. 

Application Performance and Availability Management

If IT is a business, then theoretically it has "products." And unquestionably the single most prominent products of IT are its application business services. In evaluating this criterion, we looked at breadth and depth of support for a wide range of application types, insight into application-to-application and application-to-infrastructure interdependencies, advanced levels of transaction awareness, and handshakes to support DevOps and business impact.

Internet of Things (IoT)

IoT is an emerging area, and one that many solutions in this report are architecturally designed to support — even if, in most cases, IoT has not yet been a priority in deployments. In evaluating this criterion, we looked at three things: architectural feasibility to support IoT data inputs, proof points of IoT use cases from actual deployments, and proactive support for IoT with unique out-of-the box functionality.

In my next blog I address our seven "scenarios" ranging from DevOps and SecOps to business impact and business alignment.

Read Part 3: Scenarios

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If You Are Looking to Invest in Advanced Analytics for IT, Exactly What Should You Be Shopping For? Part 2: Environments

Dennis Drogseth

EMA published the AIA buyer's guide — directed at helping IT invest in Advanced IT Analytics(AIA), what the industry more commonly calls "Operational Analytics." We created what we called "Shopping Cart Criteria" based on our prior research on AIA adoptions over the past three years. We divided the sixteen shopping cart criteria into three parts: Cost advantage, Environments and Scenarios.

Start with Part 1: Cost Advantage

In this blog, I will address environments. Environments, as indicated by the list below, indicate "where" the AIA solutions we investigated can be applied. All 13 solutions supported cloud for performance, core infrastructure, and application performance and availability. Mainframe had the support of six of our respondents, and IoT and cloud for change and capacity were not yet prime areas of focus for most of the vendors in our guide.

■ Cloud for Performance Management

■ Cloud for Change/Capacity/Cost Optimization

■ Core Infrastructure (Network/Data Center)

■ Legacy/Mainframe

■ Application Performance and Availability Management

■ Internet of Things (IoT)

Cloud for Performance Management

Here we addressed cloud in all its forms, including public cloud, virtualization, microservices and containers, and hybrid cloud environments — with a focus on performance management of IT services and their associated infrastructure. We saw fairly pervasive support for AWS, Azure, Docker and containers, and microservices. Present but less prevalent was support for Google Cloud, IBM Bluemix, Rackspace and Fujitsu Cloud. We also saw integrations with Pivotal Cloud Foundry in support of DevOps initiatives.

Cloud for Change/Capacity/Cost Optimization

Capacity and cost decisions are often joined at the hip in dealing with planning deployment choices across public and private cloud. These decisions can also significantly impact performance. And in fact, in last year's AIA research, optimizing cloud resources generally ranked higher than pure-play performance management in AIA requirements. This unique but critical area was addressed proactively by several of the vendors in this report, especially those with integrations for capacity analytics, and in two cases even cloud-related pricing models.

Core Infrastructure (Network/Data Center)

All of the solutions represented in this report were directed to some degree at cross-domain operational needs. But the approach they took varied dramatically. In evaluating ratings associated with this criterion, we looked for breadth of coverage, relevant stakeholder support, and breadth of capabilities for assessing issues with infrastructure performance both in itself, and in the context of service delivery. 

Legacy/Mainframe

Mainframes in various form factors have hardly disappeared, and many of the world's most critical IT business services are still dependent on mainframe availability and performance. In evaluating this criterion, we looked at the established architectural support for mainframes, as well as the history of the vendor in mainframe support, and its currency in keeping up with new mainframe design and features. 

Application Performance and Availability Management

If IT is a business, then theoretically it has "products." And unquestionably the single most prominent products of IT are its application business services. In evaluating this criterion, we looked at breadth and depth of support for a wide range of application types, insight into application-to-application and application-to-infrastructure interdependencies, advanced levels of transaction awareness, and handshakes to support DevOps and business impact.

Internet of Things (IoT)

IoT is an emerging area, and one that many solutions in this report are architecturally designed to support — even if, in most cases, IoT has not yet been a priority in deployments. In evaluating this criterion, we looked at three things: architectural feasibility to support IoT data inputs, proof points of IoT use cases from actual deployments, and proactive support for IoT with unique out-of-the box functionality.

In my next blog I address our seven "scenarios" ranging from DevOps and SecOps to business impact and business alignment.

Read Part 3: Scenarios

Related Links

Hot Topics

The Latest

UK Organizations Hit Observability Breaking Point

UK IT leaders are reaching a critical inflection point in how they manage observability, according to research from LogicMonitor. As infrastructure complexity grows and AI adoption accelerates, fragmented monitoring environments are driving organizations to rethink their operational strategies and consolidate tools ...

At the Edge, Performance Visibility Becomes a Reliability Requirement

For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

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AI can't fix broken data. CIOs who modernize revenue data governance unlock predictable growth-those who don't risk millions in failed AI investments. For decades, CIOs kept the lights on. Revenue was someone else's problem, owned by sales, led by the CRO, measured by finance. Those days are behind us ...

Beyond 2026: How 5G, Metaverse, and Edge AI Will Redefine Secure Remote Access

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

Why IT Has Become the Proving Ground for Enterprise AI

Ask where enterprise AI is making its most decisive impact, and the answer might surprise you: not marketing, not finance, not customer experience. It's IT. Across three years of industry research conducted by Digitate, one constant holds true is that IT is both the testing ground and the proving ground for enterprise AI. Last year, that position only strengthened ...

What 15 Years of Building Payment Systems Taught Me About Microservices That Nobody Talks About

A payment gateway fails at 2 AM. Thousands of transactions hang in limbo. Post-mortems reveal failures cascading across dozens of services, each technically sound in isolation. The diagnosis takes hours. The fix requires coordinated deployments across teams ...

AI Agents Are Everywhere ... The Hard Part Is Making Them Useful

Every enterprise technology conversation right now circles back to AI agents. And for once, the excitement isn't running too far ahead of reality. According to a Zapier survey of over 500 enterprise leaders, 72% of enterprises are already using or testing AI agents, and 84% plan to increase their investment over the next 12 months. Those numbers are big. But they also raise a question that doesn't get asked enough: what exactly are companies doing with these agents, and are they actually getting value from them? ...

Why Monitoring Is Becoming the Backbone of High Availability in Complex IT Environments

Many organizations still rely on reactive availability models, taking action only after an outage occurs. However, as applications become more complex, this approach often leads to delayed detection, prolonged disruption, and incomplete recovery. Monitoring is evolving from a basic operational function into a foundational capability for sustaining availability in modern environments ...

MEAN TIME TO INSIGHT Podcast - Episode 22: DNS Security

In MEAN TIME TO INSIGHT Episode 22, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses DNS Security ... 

Organizations Can Lose $1M+ Per Hour During Unplanned Disruptions

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