Top Factors That Impact Application Performance 2016 - Part 5

In 2013, APMdigest published a list called 15 Top Factors That Impact Application Performance. Even today, this is one of the most popular pieces of content on the site. And for good reason – the whole concept of Application Performance Management (APM) starts with identifying the factors that impact application performance, and then doing something about it. However, in the fast moving world of IT, many aspects of application performance have changed in the 3 years since the list was published. And many new experts have come on the scene. So APMdigest is updating the list for 2016, and you will be surprised how much it has changed.

Start with Top Factors That Impact Application Performance 2016 - Part 1

Start with Top Factors That Impact Application Performance 2016 - Part 2

Start with Top Factors That Impact Application Performance 2016 - Part 3

Start with Top Factors That Impact Application Performance 2016 - Part 4

Part 5 is the final installment of the list of top factors that impact application performance.

27. CODE INTEGRATION

As application topologies become more and more distributed, the need for seamless code integration between applications in new releases has become a significant factor in application performance. This is especially true in the case of expanding IT departments when new employees are not always familiar with the application topologies and dependencies in an organization.
Lanir Shacham
Founder & CEO, Correlsense

28. PACE OF INNOVATION

Developers are reacting to unrelenting pressure from the business to implement more business functionality in less time, at a lower cost (of development) and to then evolve that code more frequently. These pressures have caused there to be a tremendous amount of innovation in process areas like Agile and DevOps, and in new languages (PHP, Python, Ruby, Node-JS) that collectively improve developer productivity. But all of these process and technology improvements abstract the developer from the performance characteristics of their code. Docker is just the latest example of this. So the number one factor that impacts application performance is that the pace of innovation in the application stacks in response to business pressures makes measuring and ensuring application performance more difficult. This is THE challenge that the APM vendors must address
Bernd Harzog
CEO, OpsDataStore

29. LACK OF TESTING

Not testing performance early in development and not testing it later in production. Today's tools make it easier to "shift-left" moving performance testing into the development cycle so that all new code can have not only unit, smoke, and functional tests, but also performance tests that will detect performance regressions and defects before the code becomes part of the project. Allowing code that performs poorly into a project increases the cost to address this defect later. Adding performance testing as a ‘shift-right' into production ensures that the production system truly can scale and perform well when demand is higher than a development or pre-prod test would simulate. Testing in production also allows testing third-party components as a part of an integrated performance load test. You don't want a third-party feature to be the blocking item that can't perform at scale.
Tom Chavez
Sr. Evangelist, SOASTA

The biggest factor that impacts application performance is a lack of experience, which includes knowledge. Performance (meaning transactional performance and scalability) gets plenty of lip service, but how many people really test for performance at every build? Think about a scalable and fast architecture from day 1, from the messaging platform to the backend to the use of Angular to the load balancers: Everything has an impact. A culture of testing at every build, and setting clear SLA's drives true performance. There is no way around it.
Kevin Surace
CEO, Appvance

30. INEFFICIENT COMMUNICATION

Over the past decade, IT Organizations have heavily invested in APM and UEM solutions to become aware of potential performance issues even before consumers of the service felt the pain. New generation APM tools go even further with infrastructure discovery, analytics and deep code analysis to refine and speed up the diagnosis process when something goes wrong. This is all good, but it must be recognized however, that these same organizations tend to spoil all these efficiency gains because of immature communication processes. I believe that no matter how fast IT becomes aware of an application performance issue, today, the top factor that impacts application performance and customer experience is really the ability or inability for the IT organization to respond quickly enough and prevent the issue from getting bigger and the performance from deteriorating even more.
Vincent Geffray
Senior Director of Product Marketing, IT Alerting & IoT, Everbridge

31. CHANGE

Numerous factors can impact application performance - a mistake in design, application defects, insufficient capacity and many others. However, for each of such factors to impact the application, a change should happen. Application, infrastructure, data, workload or capacity – something should change for performance to deteriorate. Hence, the top factor that impacts application performance is a change. To ensure maximum performance it is critical to know "what's changed?” and be able to detect early changes that are causing negative impact. Today, most application performance management tools still mainly focus on application transaction performance and availability. Leading vendors started to explore application logs looking for additional information about application behavior. Change is a key missing piece required to manage application performance. Change detection, change correlation with performance events, and risk assessment of changes are critical capabilities IT Operations needs to become truly proactive in maintaining optimal application performance.
Sasha Gilenson
CEO, Evolven

32. UNKNOWN UNKNOWNS

From reading APM reviews on IT Central Station, I see that it is a common theme that an "unknown unknown" is what most concerns IT and DevOps managers. Examples of these "unknown unknowns" that impact app performance include factors such as the way an application responds to an unanticipated application behavior (e.g. "80% of users are coming from mobile devices!"), user behavior (e.g. "We didn't expect users to keep hitting that button.") and/or load (e.g. "Traffic spike of 600% during the summer!?").
Russell Rothstein
Founder and CEO, IT Central Station

Check out APM reviews on IT Central Station

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Top Factors That Impact Application Performance 2016 - Part 5

In 2013, APMdigest published a list called 15 Top Factors That Impact Application Performance. Even today, this is one of the most popular pieces of content on the site. And for good reason – the whole concept of Application Performance Management (APM) starts with identifying the factors that impact application performance, and then doing something about it. However, in the fast moving world of IT, many aspects of application performance have changed in the 3 years since the list was published. And many new experts have come on the scene. So APMdigest is updating the list for 2016, and you will be surprised how much it has changed.

Start with Top Factors That Impact Application Performance 2016 - Part 1

Start with Top Factors That Impact Application Performance 2016 - Part 2

Start with Top Factors That Impact Application Performance 2016 - Part 3

Start with Top Factors That Impact Application Performance 2016 - Part 4

Part 5 is the final installment of the list of top factors that impact application performance.

27. CODE INTEGRATION

As application topologies become more and more distributed, the need for seamless code integration between applications in new releases has become a significant factor in application performance. This is especially true in the case of expanding IT departments when new employees are not always familiar with the application topologies and dependencies in an organization.
Lanir Shacham
Founder & CEO, Correlsense

28. PACE OF INNOVATION

Developers are reacting to unrelenting pressure from the business to implement more business functionality in less time, at a lower cost (of development) and to then evolve that code more frequently. These pressures have caused there to be a tremendous amount of innovation in process areas like Agile and DevOps, and in new languages (PHP, Python, Ruby, Node-JS) that collectively improve developer productivity. But all of these process and technology improvements abstract the developer from the performance characteristics of their code. Docker is just the latest example of this. So the number one factor that impacts application performance is that the pace of innovation in the application stacks in response to business pressures makes measuring and ensuring application performance more difficult. This is THE challenge that the APM vendors must address
Bernd Harzog
CEO, OpsDataStore

29. LACK OF TESTING

Not testing performance early in development and not testing it later in production. Today's tools make it easier to "shift-left" moving performance testing into the development cycle so that all new code can have not only unit, smoke, and functional tests, but also performance tests that will detect performance regressions and defects before the code becomes part of the project. Allowing code that performs poorly into a project increases the cost to address this defect later. Adding performance testing as a ‘shift-right' into production ensures that the production system truly can scale and perform well when demand is higher than a development or pre-prod test would simulate. Testing in production also allows testing third-party components as a part of an integrated performance load test. You don't want a third-party feature to be the blocking item that can't perform at scale.
Tom Chavez
Sr. Evangelist, SOASTA

The biggest factor that impacts application performance is a lack of experience, which includes knowledge. Performance (meaning transactional performance and scalability) gets plenty of lip service, but how many people really test for performance at every build? Think about a scalable and fast architecture from day 1, from the messaging platform to the backend to the use of Angular to the load balancers: Everything has an impact. A culture of testing at every build, and setting clear SLA's drives true performance. There is no way around it.
Kevin Surace
CEO, Appvance

30. INEFFICIENT COMMUNICATION

Over the past decade, IT Organizations have heavily invested in APM and UEM solutions to become aware of potential performance issues even before consumers of the service felt the pain. New generation APM tools go even further with infrastructure discovery, analytics and deep code analysis to refine and speed up the diagnosis process when something goes wrong. This is all good, but it must be recognized however, that these same organizations tend to spoil all these efficiency gains because of immature communication processes. I believe that no matter how fast IT becomes aware of an application performance issue, today, the top factor that impacts application performance and customer experience is really the ability or inability for the IT organization to respond quickly enough and prevent the issue from getting bigger and the performance from deteriorating even more.
Vincent Geffray
Senior Director of Product Marketing, IT Alerting & IoT, Everbridge

31. CHANGE

Numerous factors can impact application performance - a mistake in design, application defects, insufficient capacity and many others. However, for each of such factors to impact the application, a change should happen. Application, infrastructure, data, workload or capacity – something should change for performance to deteriorate. Hence, the top factor that impacts application performance is a change. To ensure maximum performance it is critical to know "what's changed?” and be able to detect early changes that are causing negative impact. Today, most application performance management tools still mainly focus on application transaction performance and availability. Leading vendors started to explore application logs looking for additional information about application behavior. Change is a key missing piece required to manage application performance. Change detection, change correlation with performance events, and risk assessment of changes are critical capabilities IT Operations needs to become truly proactive in maintaining optimal application performance.
Sasha Gilenson
CEO, Evolven

32. UNKNOWN UNKNOWNS

From reading APM reviews on IT Central Station, I see that it is a common theme that an "unknown unknown" is what most concerns IT and DevOps managers. Examples of these "unknown unknowns" that impact app performance include factors such as the way an application responds to an unanticipated application behavior (e.g. "80% of users are coming from mobile devices!"), user behavior (e.g. "We didn't expect users to keep hitting that button.") and/or load (e.g. "Traffic spike of 600% during the summer!?").
Russell Rothstein
Founder and CEO, IT Central Station

Check out APM reviews on IT Central Station

Related Links

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Enterprise Edge AI Reaches Inflection Point

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

AI Is Hitting Operational Limits

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

Alert Fatigue Is No Longer a Morale Problem, It's a Reliability Risk and a System Failure

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

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I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Your Observability Stack Has a Telemetry Pipeline Problem

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

Operator to Orchestrator: 80% of IT Pros See Shift in Role as AI Permeates Workflows

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Gartner: 40% of Organizations Deploying AI Will Use AI Observability to Monitor Model Performance by 2028

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Almost Half of AI-Generated Code Fails in Production

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

AI Requires Design, Not Edicts

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

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