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.

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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

Manufacturing Organizations Doubled AI Investment Yet Only 37% Fully Prepared to Operationalize AI

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Optimizing Decisions with Edge-First Cognitive Intelligence

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

The New Perimeter Is the User: Why Identity Is the Real Network Edge

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

When AI Infrastructure Stops Behaving Like Infrastructure

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Enterprise Resilience: Understanding the Shift from Static to Dynamic

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile Users Expect Perfection in 2026

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

AI Confidence Is High. Readiness Is Not. What the Data Tells Us - and Why It Matters

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI, Realistic Expectations and the Future of IT Operations in 2026

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

Trust, But Verify: Building Confidence in AI Through Human Oversight

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

Data Centers Plan to Reduce Reliance on Grid

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...