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If You Are Looking to Invest in Advanced Analytics for IT, Exactly What Should You Be Shopping For? Part 3: Scenarios

Dennis Drogseth

This is the sixth in my series of blogs inspired by EMA's AIA buyer's guide — directed at helping IT invest in Advanced IT Analytics (AIA), what the industry more commonly calls "Operational Analytics." The goal was to create a "Consumer's Report" approach. And to do that we took it one step further. We created what we called "Shopping Cart Criteria" based on our prior research on AIA adoptions over the past three years.

My last two blogs looked at Cost Advantage parameters and Environments.

Start with Part 1: Cost Advantage

Start with Part 2: Environments

Cost Advantage included:

■ Time to Value

■ Administration and Support

■ Toolset Consolidation

Environments included:

■ 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)

In this blog, I examine scenario-related shopping cart objectives for AIA.

At EMA, we evaluated seven unique scenarios relevant to AIA adoptions. Our scenarios included agile/DevOps, Integrated security, change impact awareness, capacity optimization, business impact, business alignment and unifying IT.

Agile/DevOps

DevOps is a key area of opportunity.

We found that some vendors had made DevOps a clear and proven focus, whereas for others it was more a direction of future interest. But DevOps is a key area of opportunity. In prior research we saw that 69 percent of our respondents were looking to link their AIA investments to DevOps requirements.

In evaluating this scenario, we looked at discreet requirements in terms of agile/DevOps needs including support for both development professionals and quality assurance and testing (QA Test). To do this we considered overall APM strengths, application change impact awareness, and proof points in terms of actual deployment scenarios. We also targeted analytic insight into digital experience management across the full application lifecycle.

Integrated Security

Integrated security was another scenario where almost all the vendors provided basic functionality, but only a few had made it a primary focus. However, based on recent EMA research in both analytics and SecOps, integrated security is a very high-growth opportunity, with surprisingly strong priorities among both operations and security stakeholders for shared data, shared analytics and shared insights.

In evaluating this criterion, we looked for bidirectional security-related toolset integrations for analysis and visualization relevant to SecOps requirements. We also considered appropriate stakeholder support, and proof points in terms of actual deployments.

Change Impact Awareness

It is well known that performance management and change impact awareness go hand in hand. To be "outstanding" in this area, however, requires many fundamentals. Among them are:

■ analytic awareness of changes in performance-related metrics

■ insight into dependencies to see how and where abnormalities are most likely to impact a critical business service

■ insights into change management procedures and histories so that timely correlations can be proactively understood between change histories and performance and availability metrics

In determining a rating for change impact awareness, we also considered integrations with IT service management (ITSM) sources, CMDBs, CMSs, and ADDM capabilities.

Capacity Optimization

We reserved this scenario for those vendors that went a step beyond change impact awareness. In other words, no vendor could excel here without at least being "strong" in change impact awareness. Capacity Optimization featured those vendors with significant integrations with capacity analytics and automation to make all the requisite connections between performance, change, capacity, and, ideally, cost. In multiple research initiatives, we've seen capacity and even cost analytics stand out as a leading priority for AIA — especially when it comes to optimizing the move to cloud.

Business Impact

In the age of digital transformation, little could be more important than energizing the handshake between IT service delivery and business outcomes. In evaluating this criterion, we considered basic strengths in transactional performance and support for business stakeholders. The highest ratings required data and analytics integrating business and IT sources, as well as common dashboard visualizations of business outcomes such as revenue, business process optimization and conversions from competitive websites.

Business Alignment

Business impact factors into business alignment, but data sharing for optimal business alignment also requires reports and visualization that promote IT-to-business dialog along multiple fronts in a current and dynamic way. In evaluating this scenario, we looked at well-defined stakeholder support for business as well as IT stakeholders, well-evolved dashboarding and workflows, and at least some strengths in unifying IT.

Unifying IT

Unifying IT, much like toolset consolidation, is something of a Holy Grail in value when it comes to investing in AIA. Advanced IT analytics can enable a common layer of efficiency that helps to promote better processes, dialog, data sharing, and automation across virtually all of IT — not just operations. Integrations and stakeholder support were paramount for this scenario, as was social IT and mobile support. For proof points, we looked for real-world examples where a wide range of IT stakeholders were in fact beginning to work differently and more effectively together.

Hot Topics

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

If You Are Looking to Invest in Advanced Analytics for IT, Exactly What Should You Be Shopping For? Part 3: Scenarios

Dennis Drogseth

This is the sixth in my series of blogs inspired by EMA's AIA buyer's guide — directed at helping IT invest in Advanced IT Analytics (AIA), what the industry more commonly calls "Operational Analytics." The goal was to create a "Consumer's Report" approach. And to do that we took it one step further. We created what we called "Shopping Cart Criteria" based on our prior research on AIA adoptions over the past three years.

My last two blogs looked at Cost Advantage parameters and Environments.

Start with Part 1: Cost Advantage

Start with Part 2: Environments

Cost Advantage included:

■ Time to Value

■ Administration and Support

■ Toolset Consolidation

Environments included:

■ 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)

In this blog, I examine scenario-related shopping cart objectives for AIA.

At EMA, we evaluated seven unique scenarios relevant to AIA adoptions. Our scenarios included agile/DevOps, Integrated security, change impact awareness, capacity optimization, business impact, business alignment and unifying IT.

Agile/DevOps

DevOps is a key area of opportunity.

We found that some vendors had made DevOps a clear and proven focus, whereas for others it was more a direction of future interest. But DevOps is a key area of opportunity. In prior research we saw that 69 percent of our respondents were looking to link their AIA investments to DevOps requirements.

In evaluating this scenario, we looked at discreet requirements in terms of agile/DevOps needs including support for both development professionals and quality assurance and testing (QA Test). To do this we considered overall APM strengths, application change impact awareness, and proof points in terms of actual deployment scenarios. We also targeted analytic insight into digital experience management across the full application lifecycle.

Integrated Security

Integrated security was another scenario where almost all the vendors provided basic functionality, but only a few had made it a primary focus. However, based on recent EMA research in both analytics and SecOps, integrated security is a very high-growth opportunity, with surprisingly strong priorities among both operations and security stakeholders for shared data, shared analytics and shared insights.

In evaluating this criterion, we looked for bidirectional security-related toolset integrations for analysis and visualization relevant to SecOps requirements. We also considered appropriate stakeholder support, and proof points in terms of actual deployments.

Change Impact Awareness

It is well known that performance management and change impact awareness go hand in hand. To be "outstanding" in this area, however, requires many fundamentals. Among them are:

■ analytic awareness of changes in performance-related metrics

■ insight into dependencies to see how and where abnormalities are most likely to impact a critical business service

■ insights into change management procedures and histories so that timely correlations can be proactively understood between change histories and performance and availability metrics

In determining a rating for change impact awareness, we also considered integrations with IT service management (ITSM) sources, CMDBs, CMSs, and ADDM capabilities.

Capacity Optimization

We reserved this scenario for those vendors that went a step beyond change impact awareness. In other words, no vendor could excel here without at least being "strong" in change impact awareness. Capacity Optimization featured those vendors with significant integrations with capacity analytics and automation to make all the requisite connections between performance, change, capacity, and, ideally, cost. In multiple research initiatives, we've seen capacity and even cost analytics stand out as a leading priority for AIA — especially when it comes to optimizing the move to cloud.

Business Impact

In the age of digital transformation, little could be more important than energizing the handshake between IT service delivery and business outcomes. In evaluating this criterion, we considered basic strengths in transactional performance and support for business stakeholders. The highest ratings required data and analytics integrating business and IT sources, as well as common dashboard visualizations of business outcomes such as revenue, business process optimization and conversions from competitive websites.

Business Alignment

Business impact factors into business alignment, but data sharing for optimal business alignment also requires reports and visualization that promote IT-to-business dialog along multiple fronts in a current and dynamic way. In evaluating this scenario, we looked at well-defined stakeholder support for business as well as IT stakeholders, well-evolved dashboarding and workflows, and at least some strengths in unifying IT.

Unifying IT

Unifying IT, much like toolset consolidation, is something of a Holy Grail in value when it comes to investing in AIA. Advanced IT analytics can enable a common layer of efficiency that helps to promote better processes, dialog, data sharing, and automation across virtually all of IT — not just operations. Integrations and stakeholder support were paramount for this scenario, as was social IT and mobile support. For proof points, we looked for real-world examples where a wide range of IT stakeholders were in fact beginning to work differently and more effectively together.

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...