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30 Ways APM Should Evolve - Part 1

At the end of every year, APMdigest takes a look into the future by asking experts to predict the changes that will occur within the Application Performance Management (APM) industry in the coming new year. With this new list, we are looking even farther into the future, to the evolution of APM.

This list is not so much about predictions – rather it is comprised of expert opinions on how APM should evolve. It is more like an evolutionary wish list for APM.

In preparing this list, APMdigest asked the top minds in the industry what they feel is the most important way APM tools must evolve. The recommendations on this list provide a rare look into the long-term future of APM technology.

The 2016 APM Predictions List was the longest predictions list ever featured on APMdigest – reflecting a rapidly growing, changing and increasingly complex IT environment that presents more challenges than ever before – and this list is equally epic, with 30 categories of recommendations to be posted over the next 6 days.

As usual for APMdigest lists like this, some of the recommendations could fit into multiple categories. We had to create general category headings to give the list structure, but the real value to be gained from the list is the thoughtful and introspective visions of the future offered by each expert.

1. DISCOVERING AND MONITORING DYNAMIC ENVIRONMENTS

The biggest threat to existing APM technology is the increasing dynamism of the environment. While we've had virtual infrastructures for well over a decade, the rate of change still seemed manageable. With the advent of containers and microservices plus the adoption of DevOps CI/CD practices, however, there is the potential for an entirely new scale of environmental flux if the behavior observed within large cloud companies gives us any early insights. We need to rethink not only how to discover these increasingly ephemeral assets, but also to effectively monitor them – without overloading the infrastructure (or breaking the enterprise budget).
Cameron Haight
Research VP, IT Operations, Gartner

Web-scale applications have created a massively complex challenge for modern software operations. Complexity emerging from cloud architectures, containerized microservices, open source frameworks, and data-centric applications makes it a challenge for any engineering team to monitor their systems. APM needs to evolve from simple metric collection and plotting graphs to intelligent monitoring that automatically discovers all the dynamic components of web-scale apps (open source frameworks included), provides a visual topology, and leverages data-science for intelligent analysis and anomaly detection.
Alan Ngai
CTO, OpsClarity

2. CONVERGENCE OF MONITORING

APM consists of three main factions which must all evolve and come together for a complete solution. They are Wire Data Analytics, Synthetic Transactions, and Agent Code Instrumentation. To gain visibility at the edge and report on the End User Experience you must develop a strategy on the best way to bring together the 3 monitoring factions.
Larry Dragich
Director of Customer Experience Management at the Auto Club Group and Founder of the APM Strategies Group on LinkedIn.

3. ACTIONABLE INSIGHT

APM must evolve from being descriptive to prescriptive. Let's face it, there is an overwhelming amount of data collected by APM solutions today. But adding more data to the haystack doesn't make it easier to find a needle. What's needed is the analytics to sift through the data and provide actionable insights with prescriptive solutions. This way, you not only understand the impacts of a performance or user experience issue, but are provided guidance to understand when, where and how to act to solve or even prevent it.
Aruna Ravichandran
VP, DevOps Product and Solutions Marketing, CA Technologies

Technology is disrupting all industries and it is happening at a breakneck speed. New business models and customer experience are supported by a mix of "technology pillars" like cloud and mobile, as well as accelerators like IoT and Artificial Intelligence. The network is what ties everything together and carries the data. As such, IT teams must manage growing service delivery complexity, design for large-scale traffic with visibility everywhere today as well as support for zetabytes of data in the future, and build for speed and agility to enable informed real-time decisions in both agile and highly automated environments. To meet these business assurance challenges, APM solutions must provide actionable insights into the connections between people, machines, data, and processes so as to optimize agility, assure service delivery, mitigate risk and provide a feedback loop to operations, development, and business functions. If done right, there are huge business benefits: happy customers and revenue growth.
Ron Lifton
Senior Enterprise Solutions Manager, NetScout

4. INSIGHT ACROSS ON-PREMISE AND CLOUD

IT environments are becoming extremely complicated with an increasing number using some combination of on-prem and cloud resources. As enterprise cloud adoption rises, hybrid cloud applications are expanding. For example, UI applications could be running on dynamic, engaging public clouds that interface with tested on-premises business logic and databases. An Application Performance Management tool that can provide analytical insights across ALL application dependencies and give one integrated view is critical in ensuring enterprise IT and application DevOps teams operate at the same sustained fast pace.
Arun Biligiri
APM Offering Management Leader, IBM

5. IT OPERATIONS MANAGEMENT

Application Performance Monitoring solutions must evolve as businesses traverse their own journeys with digital transformation. In a socially and mobile enabled world, the consumer has taken control and every experience and every interaction matters. These interactions will be more and more with Internet of Things (IoT) devices leading to many new classes of things to monitor and will require tracking of highly complex interactions as well as collection and analysis of massive amounts of data. APM solutions must evolve from stand-alone solutions to a complete IT Operations Management suite and integrate with these Big Data challenges to avoid evolutionary dead end.
Daniel Schrijver
Senior Principal Product Marketing Director, Oracle

Read 30 Ways APM Should Evolve - Part 2, covering the evolution of the relationship between APM and analytics.

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 ...

30 Ways APM Should Evolve - Part 1

At the end of every year, APMdigest takes a look into the future by asking experts to predict the changes that will occur within the Application Performance Management (APM) industry in the coming new year. With this new list, we are looking even farther into the future, to the evolution of APM.

This list is not so much about predictions – rather it is comprised of expert opinions on how APM should evolve. It is more like an evolutionary wish list for APM.

In preparing this list, APMdigest asked the top minds in the industry what they feel is the most important way APM tools must evolve. The recommendations on this list provide a rare look into the long-term future of APM technology.

The 2016 APM Predictions List was the longest predictions list ever featured on APMdigest – reflecting a rapidly growing, changing and increasingly complex IT environment that presents more challenges than ever before – and this list is equally epic, with 30 categories of recommendations to be posted over the next 6 days.

As usual for APMdigest lists like this, some of the recommendations could fit into multiple categories. We had to create general category headings to give the list structure, but the real value to be gained from the list is the thoughtful and introspective visions of the future offered by each expert.

1. DISCOVERING AND MONITORING DYNAMIC ENVIRONMENTS

The biggest threat to existing APM technology is the increasing dynamism of the environment. While we've had virtual infrastructures for well over a decade, the rate of change still seemed manageable. With the advent of containers and microservices plus the adoption of DevOps CI/CD practices, however, there is the potential for an entirely new scale of environmental flux if the behavior observed within large cloud companies gives us any early insights. We need to rethink not only how to discover these increasingly ephemeral assets, but also to effectively monitor them – without overloading the infrastructure (or breaking the enterprise budget).
Cameron Haight
Research VP, IT Operations, Gartner

Web-scale applications have created a massively complex challenge for modern software operations. Complexity emerging from cloud architectures, containerized microservices, open source frameworks, and data-centric applications makes it a challenge for any engineering team to monitor their systems. APM needs to evolve from simple metric collection and plotting graphs to intelligent monitoring that automatically discovers all the dynamic components of web-scale apps (open source frameworks included), provides a visual topology, and leverages data-science for intelligent analysis and anomaly detection.
Alan Ngai
CTO, OpsClarity

2. CONVERGENCE OF MONITORING

APM consists of three main factions which must all evolve and come together for a complete solution. They are Wire Data Analytics, Synthetic Transactions, and Agent Code Instrumentation. To gain visibility at the edge and report on the End User Experience you must develop a strategy on the best way to bring together the 3 monitoring factions.
Larry Dragich
Director of Customer Experience Management at the Auto Club Group and Founder of the APM Strategies Group on LinkedIn.

3. ACTIONABLE INSIGHT

APM must evolve from being descriptive to prescriptive. Let's face it, there is an overwhelming amount of data collected by APM solutions today. But adding more data to the haystack doesn't make it easier to find a needle. What's needed is the analytics to sift through the data and provide actionable insights with prescriptive solutions. This way, you not only understand the impacts of a performance or user experience issue, but are provided guidance to understand when, where and how to act to solve or even prevent it.
Aruna Ravichandran
VP, DevOps Product and Solutions Marketing, CA Technologies

Technology is disrupting all industries and it is happening at a breakneck speed. New business models and customer experience are supported by a mix of "technology pillars" like cloud and mobile, as well as accelerators like IoT and Artificial Intelligence. The network is what ties everything together and carries the data. As such, IT teams must manage growing service delivery complexity, design for large-scale traffic with visibility everywhere today as well as support for zetabytes of data in the future, and build for speed and agility to enable informed real-time decisions in both agile and highly automated environments. To meet these business assurance challenges, APM solutions must provide actionable insights into the connections between people, machines, data, and processes so as to optimize agility, assure service delivery, mitigate risk and provide a feedback loop to operations, development, and business functions. If done right, there are huge business benefits: happy customers and revenue growth.
Ron Lifton
Senior Enterprise Solutions Manager, NetScout

4. INSIGHT ACROSS ON-PREMISE AND CLOUD

IT environments are becoming extremely complicated with an increasing number using some combination of on-prem and cloud resources. As enterprise cloud adoption rises, hybrid cloud applications are expanding. For example, UI applications could be running on dynamic, engaging public clouds that interface with tested on-premises business logic and databases. An Application Performance Management tool that can provide analytical insights across ALL application dependencies and give one integrated view is critical in ensuring enterprise IT and application DevOps teams operate at the same sustained fast pace.
Arun Biligiri
APM Offering Management Leader, IBM

5. IT OPERATIONS MANAGEMENT

Application Performance Monitoring solutions must evolve as businesses traverse their own journeys with digital transformation. In a socially and mobile enabled world, the consumer has taken control and every experience and every interaction matters. These interactions will be more and more with Internet of Things (IoT) devices leading to many new classes of things to monitor and will require tracking of highly complex interactions as well as collection and analysis of massive amounts of data. APM solutions must evolve from stand-alone solutions to a complete IT Operations Management suite and integrate with these Big Data challenges to avoid evolutionary dead end.
Daniel Schrijver
Senior Principal Product Marketing Director, Oracle

Read 30 Ways APM Should Evolve - Part 2, covering the evolution of the relationship between APM and analytics.

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 ...