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.

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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.

Related Links

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How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

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Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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