2017 Application Performance Management Predictions - Part 3

APMdigest's 2017 Application Performance Management Predictions is a forecast by the top minds in APM today. Industry experts — from analysts and consultants to users and the top vendors — offer thoughtful, insightful, and often controversial predictions on how APM and related technologies will evolve and impact business in 2017. Part 3 covers the many aspects of IT services, including monitoring, incident management, end user experience and DevOps.

Start with 2017 Application Performance Management Predictions - Part 1

Start with 2017 Application Performance Management Predictions - Part 2

22. THE UNIFICATION OF MONITORING

In 2017 we will see leading APM solutions begin to increase capabilities in both the depth in which they can capture data and the velocity in which they can handle time series metrics. Today's solutions are fragmented between APM, metrics, logs, and infrastructure capture which creates visibility issues. Unification will be a key driver to free up engineering resources in most organizations utilizing monitoring.
Jonah Kowall
VP of Market Development and Insights, AppDynamics

IT departments will push for consolidated monitoring tools that include uptime monitoring, load monitoring, response time monitoring, and end-to-end application visibility in a single tool. They are frustrated with fragmented tool landscapes with different tools for every vendor and platform and with the finger-pointing that ensues. They will insist on unified tools that can detect application issues and that can easily trace the source of the problem down to the actual root cause in the underlying infrastructure.
Kimberley Parsons Trommler
Product Evangelist, Paessler AG

23. INCIDENT MANAGEMENT EXPANDS ROLE

The role of an incident management tool will shift from just being incident management, to also focusing on alerting, fixing and documenting issues. The impact of this will be that organizations understand more about their systems over time.
Jason Hand
DevOps Evangelist, VictorOps

Read Jason Hand's blog: DevOps for Crisis Communication: Five Steps to Prevent a Crisis from Becoming a Disaster

24. GOAL: CONTINUOUS AVAILABILITY

In today's world, having a disaster, with full failure, and then recovering from that disaster just doesn't cut it. Instead, 2017 will be the year organizations demand that IT deliver continuous availability. With continuous availability, you need to run operations across multiple systems, in multiple locations, simultaneously. Pieces of the system may fail, but system as a whole will not. Ensuring that applications will continue to run even if underlying components fail, including database servers, requires new architectures, and 2017 will see those architectures dominate.
Justin Barney
CEO, ScaleArc

25. GOAL: REDUCED TRANSACTION TIMES

Application performance, including scalability and transactional performance, is becoming more important as user expectations, even for internally facing applications, grow higher. No one wants to wait for 8 seconds and instead expects less than 1 second. CEO's are pushing their internal teams to drive down transaction times, which improve productivity across their companies.
Kevin Surace
CEO, Appvance

26. GOAL: SECURE USER EXPERIENCE

As more workloads migrate to cloud environments and new development techniques such as microservices and containerization take hold, more companies will recognize the strategic and financial benefits of implementing a unified approach to application performance and secure user experience (UX). Discrete monitoring technologies will continue to converge and leverage machine learning and advanced analytics to speed early detection of behavioral anomalies and facilitate rapid incident response. This is the direction of the The Secure UX Enterprise.
Gabe Lowy
Technology Analyst and Founder of TechTonics Advisors

Read Gabe Lowy's Blog: The Secure UX Enterprise

27. FOCUS ON THE QUALITY OF END USER EXPERIENCE

2017 is the year of application end user Quality of Experience (QoE). New tools, cloud architectures and strategies will mature beyond exploiting cloud for agility to a focus application development and delivery on delighting audiences.
Rob Malnati
VP of Marketing and Business Development, Cedexis

In my opinion, the digital transformation we've seen companies go through in the past years will continue at the same pace if not faster. IT will remain under the same pressure to deliver more value to market faster, always at a lower cost. What's new, is that this cannot be done at the expense of the quality of service any longer. Buggy mobile apps, slow web applications are not tolerated any longer. In the years to come, businesses will be forced to adopt a digital-customer-centric approach to IT Service and Application Performance Management, less focused on the health of the IT stack. Therefore we should continue seeing an increased adoption of the new generation APM and UEM solutions across all industries and verticals.
Vincent Geffray
Senior Director of Product Marketing, IT Alerting and IoT, Everbridge

28. APM TAKES ON DEVOPS

In 2017, APM solutions will need to focus on DevOps toolchain integration and be more dynamic than the microservice-based applications which are being managed. With these highly dynamic applications, 2017 will drive the need for cognitive analytics to be integrated with APM.
Randy George
IBM Distinguished Engineer - APM Architecture, IBM

29. LOW-CODE AND NO-CODE

The rise of low-code and no-code systems will allow APM to be integrated with system updates so that issues are not only flagged, but also resolved automatically. Performance metrics will start to focus on aspects of user experience such as response time, rather than technical indicators such as CPU utilization.
Colin Earl
CEO, Agiloft

30. OPTIMIZED MAINFRAME CODE

The mainframe is typically perceived as a transactional workhorse, but given the sheer number of transactions and users supported, slight tweaks in mainframe code can result in huge performance improvements for millions of users. With the advance of new solutions and tools it has become easier than ever to optimize previously untouchable mainframe code and improve user performance for transactional applications. We think this is an undiscovered opportunity mainframe stakeholders will be leveraging in 2017.
Spencer Hallman
Product Manager, Compuware

Read 2017 Application Performance Management Predictions - Part 4.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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 ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

2017 Application Performance Management Predictions - Part 3

APMdigest's 2017 Application Performance Management Predictions is a forecast by the top minds in APM today. Industry experts — from analysts and consultants to users and the top vendors — offer thoughtful, insightful, and often controversial predictions on how APM and related technologies will evolve and impact business in 2017. Part 3 covers the many aspects of IT services, including monitoring, incident management, end user experience and DevOps.

Start with 2017 Application Performance Management Predictions - Part 1

Start with 2017 Application Performance Management Predictions - Part 2

22. THE UNIFICATION OF MONITORING

In 2017 we will see leading APM solutions begin to increase capabilities in both the depth in which they can capture data and the velocity in which they can handle time series metrics. Today's solutions are fragmented between APM, metrics, logs, and infrastructure capture which creates visibility issues. Unification will be a key driver to free up engineering resources in most organizations utilizing monitoring.
Jonah Kowall
VP of Market Development and Insights, AppDynamics

IT departments will push for consolidated monitoring tools that include uptime monitoring, load monitoring, response time monitoring, and end-to-end application visibility in a single tool. They are frustrated with fragmented tool landscapes with different tools for every vendor and platform and with the finger-pointing that ensues. They will insist on unified tools that can detect application issues and that can easily trace the source of the problem down to the actual root cause in the underlying infrastructure.
Kimberley Parsons Trommler
Product Evangelist, Paessler AG

23. INCIDENT MANAGEMENT EXPANDS ROLE

The role of an incident management tool will shift from just being incident management, to also focusing on alerting, fixing and documenting issues. The impact of this will be that organizations understand more about their systems over time.
Jason Hand
DevOps Evangelist, VictorOps

Read Jason Hand's blog: DevOps for Crisis Communication: Five Steps to Prevent a Crisis from Becoming a Disaster

24. GOAL: CONTINUOUS AVAILABILITY

In today's world, having a disaster, with full failure, and then recovering from that disaster just doesn't cut it. Instead, 2017 will be the year organizations demand that IT deliver continuous availability. With continuous availability, you need to run operations across multiple systems, in multiple locations, simultaneously. Pieces of the system may fail, but system as a whole will not. Ensuring that applications will continue to run even if underlying components fail, including database servers, requires new architectures, and 2017 will see those architectures dominate.
Justin Barney
CEO, ScaleArc

25. GOAL: REDUCED TRANSACTION TIMES

Application performance, including scalability and transactional performance, is becoming more important as user expectations, even for internally facing applications, grow higher. No one wants to wait for 8 seconds and instead expects less than 1 second. CEO's are pushing their internal teams to drive down transaction times, which improve productivity across their companies.
Kevin Surace
CEO, Appvance

26. GOAL: SECURE USER EXPERIENCE

As more workloads migrate to cloud environments and new development techniques such as microservices and containerization take hold, more companies will recognize the strategic and financial benefits of implementing a unified approach to application performance and secure user experience (UX). Discrete monitoring technologies will continue to converge and leverage machine learning and advanced analytics to speed early detection of behavioral anomalies and facilitate rapid incident response. This is the direction of the The Secure UX Enterprise.
Gabe Lowy
Technology Analyst and Founder of TechTonics Advisors

Read Gabe Lowy's Blog: The Secure UX Enterprise

27. FOCUS ON THE QUALITY OF END USER EXPERIENCE

2017 is the year of application end user Quality of Experience (QoE). New tools, cloud architectures and strategies will mature beyond exploiting cloud for agility to a focus application development and delivery on delighting audiences.
Rob Malnati
VP of Marketing and Business Development, Cedexis

In my opinion, the digital transformation we've seen companies go through in the past years will continue at the same pace if not faster. IT will remain under the same pressure to deliver more value to market faster, always at a lower cost. What's new, is that this cannot be done at the expense of the quality of service any longer. Buggy mobile apps, slow web applications are not tolerated any longer. In the years to come, businesses will be forced to adopt a digital-customer-centric approach to IT Service and Application Performance Management, less focused on the health of the IT stack. Therefore we should continue seeing an increased adoption of the new generation APM and UEM solutions across all industries and verticals.
Vincent Geffray
Senior Director of Product Marketing, IT Alerting and IoT, Everbridge

28. APM TAKES ON DEVOPS

In 2017, APM solutions will need to focus on DevOps toolchain integration and be more dynamic than the microservice-based applications which are being managed. With these highly dynamic applications, 2017 will drive the need for cognitive analytics to be integrated with APM.
Randy George
IBM Distinguished Engineer - APM Architecture, IBM

29. LOW-CODE AND NO-CODE

The rise of low-code and no-code systems will allow APM to be integrated with system updates so that issues are not only flagged, but also resolved automatically. Performance metrics will start to focus on aspects of user experience such as response time, rather than technical indicators such as CPU utilization.
Colin Earl
CEO, Agiloft

30. OPTIMIZED MAINFRAME CODE

The mainframe is typically perceived as a transactional workhorse, but given the sheer number of transactions and users supported, slight tweaks in mainframe code can result in huge performance improvements for millions of users. With the advance of new solutions and tools it has become easier than ever to optimize previously untouchable mainframe code and improve user performance for transactional applications. We think this is an undiscovered opportunity mainframe stakeholders will be leveraging in 2017.
Spencer Hallman
Product Manager, Compuware

Read 2017 Application Performance Management Predictions - Part 4.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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 ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...