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Next Steps for ITOA - Part 5

APMdigest asked experts across the industry — including analysts, consultants and vendors — for their opinions on the next steps for ITOA. These next steps include where the experts believe ITOA is headed, as well as where they think it should be headed. Part 5 offers some interesting final thoughts.

Start with Next Steps for ITOA - Part 1

Start with Next Steps for ITOA - Part 2

Start with Next Steps for ITOA - Part 3

Start with Next Steps for ITOA - Part 4

REACTIVE TO PROACTIVE

ITOA will help evolve tomorrow's IT organization from a reactive speeds and feeds provider focused on capacity availability into a proactive data-driven fulfillment engine delivering stability, agility and innovation ahead of business needs.
Trace3 Research 360 View Trend Report: IT Operations Monitoring & Analytics (ITOMA)

HOLISTIC APPROACH

The next step in the evolution of IT Operations Analytics is establishing a more holistic approach that considers the performance of people AND machines. Metrics tied to machines and tools are now table stakes for ITOA. However, in the future, organizations will need to look at the system as a whole, which includes the humans involved. In order to have a complete understanding of ITOps health, IT organizations must have a comprehensive view of how their people are interacting with machines, data and other people, and establish metrics accordingly to this whole rather than just the parts.
Eric Sigler
Head of DevOps, PagerDuty

OPEN SOURCE

Organizations are collecting massive amounts of live data streams, which on its own can feel like a major accomplishment. But the key question is: so what? If they have no way to analyze billions of data points from servers, machines, containers and applications in millisecond response time, none of that work matters. By adopting newer and more flexible open source products with machine learning capabilities tailored to time series use cases, organizations will be better equipped to use all of their data to help them operate better, detect infrastructure problems, cybersecurity, or fraud, and solve critical business issues.
Jeff Yoshimura
VP Worldwide Marketing, Elastic

MULTI-VENDOR COLLABORATION

The next natural step for ITOA is for the machines to leverage the analytics to make reasoned decisions and take actions based on the information collected. Analytics leads to heuristics – when machine intelligence is able to interpret the data based on business defined policies and standards. Once the machine can make recommendations, the next evolutionary step is for the machine to act on those recommendations. The orchestration and automation of IT environments is evolving. Tools and standards such as Openstack are being developed to enable the automated management and orchestration of IT architectures. Expect more multi-vendor collaboration to build architectures that can be integrated into a single management and orchestration environment over the next couple years, but do not expect full integration and a mature, automated, self-analyzing, and self-healing network ecosystem for years to come.
Frank Yue
Director of Application Delivery Solutions, Radware

SECURITY

As threats continue to increase in frequency and sophistication, enterprises will need to look to IT Operations Analytics as a tactic to identify and proactively address anomalies before security threats fully materialize. With the rise of connected devices and the Internet of Things and emerging technologies like Artificial Intelligence, organizations are increasingly moving toward analytics and automation as a tactic to supercharge cybersecurity.
Ananda Rajagopal
VP, Product Management, Gigamon

COST OPTIMIZATION

Performance management focused on the speed and reliability of user interactions will always be very important. But performance management must also focus on efficiency of code execution, with an eye towards cost optimization for underlying CPU resources. As the mainframe continues to be the platform of choice for mission-critical transactional applications, slight code tweaks can yield performance boosts for thousands of users. However, with mainframe licensing costs (MLCs) comprising approximately 30 percent of mainframe budgets – and withh these costs continuing to rise – it is equally critical to be more pro-active about service level management of the workload so R4HA peaks can be minimized, keeping costs in check and wasted expenses down. We expect IT Operations Analytics - particularly for mainframe user organizations - to expand in focus, optimizing not just the user experience but costs as well.
Spencer Hallman
Product Manager, Compuware

ANALYTICS AVAILABLE TO ALL

Predictive analytics in application performance management offers a powerful way to improve customer experience. By deploying correlation and mathematical modeling techniques, it analyzes relationships between multiple data points to accurately predict future application behavioral trends, and data anomalies which would affect end-users. Presently predictive analytics is available and affordable for large business with money and resources, however that is going to change in the near future. With emerging technologies and new and easy ways of presenting information to end-users, vendors will differentiate themselves by offering simpler and more affordable ways to deploy predictive analytics in their APM solutions, making it available to all.
Pritika Ramani
Product Analyst, ManageEngine

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 ...

Next Steps for ITOA - Part 5

APMdigest asked experts across the industry — including analysts, consultants and vendors — for their opinions on the next steps for ITOA. These next steps include where the experts believe ITOA is headed, as well as where they think it should be headed. Part 5 offers some interesting final thoughts.

Start with Next Steps for ITOA - Part 1

Start with Next Steps for ITOA - Part 2

Start with Next Steps for ITOA - Part 3

Start with Next Steps for ITOA - Part 4

REACTIVE TO PROACTIVE

ITOA will help evolve tomorrow's IT organization from a reactive speeds and feeds provider focused on capacity availability into a proactive data-driven fulfillment engine delivering stability, agility and innovation ahead of business needs.
Trace3 Research 360 View Trend Report: IT Operations Monitoring & Analytics (ITOMA)

HOLISTIC APPROACH

The next step in the evolution of IT Operations Analytics is establishing a more holistic approach that considers the performance of people AND machines. Metrics tied to machines and tools are now table stakes for ITOA. However, in the future, organizations will need to look at the system as a whole, which includes the humans involved. In order to have a complete understanding of ITOps health, IT organizations must have a comprehensive view of how their people are interacting with machines, data and other people, and establish metrics accordingly to this whole rather than just the parts.
Eric Sigler
Head of DevOps, PagerDuty

OPEN SOURCE

Organizations are collecting massive amounts of live data streams, which on its own can feel like a major accomplishment. But the key question is: so what? If they have no way to analyze billions of data points from servers, machines, containers and applications in millisecond response time, none of that work matters. By adopting newer and more flexible open source products with machine learning capabilities tailored to time series use cases, organizations will be better equipped to use all of their data to help them operate better, detect infrastructure problems, cybersecurity, or fraud, and solve critical business issues.
Jeff Yoshimura
VP Worldwide Marketing, Elastic

MULTI-VENDOR COLLABORATION

The next natural step for ITOA is for the machines to leverage the analytics to make reasoned decisions and take actions based on the information collected. Analytics leads to heuristics – when machine intelligence is able to interpret the data based on business defined policies and standards. Once the machine can make recommendations, the next evolutionary step is for the machine to act on those recommendations. The orchestration and automation of IT environments is evolving. Tools and standards such as Openstack are being developed to enable the automated management and orchestration of IT architectures. Expect more multi-vendor collaboration to build architectures that can be integrated into a single management and orchestration environment over the next couple years, but do not expect full integration and a mature, automated, self-analyzing, and self-healing network ecosystem for years to come.
Frank Yue
Director of Application Delivery Solutions, Radware

SECURITY

As threats continue to increase in frequency and sophistication, enterprises will need to look to IT Operations Analytics as a tactic to identify and proactively address anomalies before security threats fully materialize. With the rise of connected devices and the Internet of Things and emerging technologies like Artificial Intelligence, organizations are increasingly moving toward analytics and automation as a tactic to supercharge cybersecurity.
Ananda Rajagopal
VP, Product Management, Gigamon

COST OPTIMIZATION

Performance management focused on the speed and reliability of user interactions will always be very important. But performance management must also focus on efficiency of code execution, with an eye towards cost optimization for underlying CPU resources. As the mainframe continues to be the platform of choice for mission-critical transactional applications, slight code tweaks can yield performance boosts for thousands of users. However, with mainframe licensing costs (MLCs) comprising approximately 30 percent of mainframe budgets – and withh these costs continuing to rise – it is equally critical to be more pro-active about service level management of the workload so R4HA peaks can be minimized, keeping costs in check and wasted expenses down. We expect IT Operations Analytics - particularly for mainframe user organizations - to expand in focus, optimizing not just the user experience but costs as well.
Spencer Hallman
Product Manager, Compuware

ANALYTICS AVAILABLE TO ALL

Predictive analytics in application performance management offers a powerful way to improve customer experience. By deploying correlation and mathematical modeling techniques, it analyzes relationships between multiple data points to accurately predict future application behavioral trends, and data anomalies which would affect end-users. Presently predictive analytics is available and affordable for large business with money and resources, however that is going to change in the near future. With emerging technologies and new and easy ways of presenting information to end-users, vendors will differentiate themselves by offering simpler and more affordable ways to deploy predictive analytics in their APM solutions, making it available to all.
Pritika Ramani
Product Analyst, ManageEngine

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 ...