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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Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

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Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

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If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

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Agentic Operations Begin with Governed Middleware Access

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

The Network Data Problem Slowing Down Enterprise AIOps

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

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Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

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