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

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Immutable by Design: Reinventing Business Continuity and Disaster Recovery

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 ...

Embracing Cost-Effective Observability Through an OpenTelemetry Approach

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 ...

Why Employees Hate Security (And What Businesses Can Do About It)

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 ...

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

MEAN TIME TO INSIGHT Podcast - Episode 13: Hybrid Multi-Cloud Networking Strategy

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

Transforming Network Remediation with a Closed-Loop Approach

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 ...

IT Leaders Are Leveraging AI Agents to Unlock Autonomous Transformation in 2025

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 ...

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5 Steps to Enhancing Network Observability for Your NOC

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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