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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

The Latest

IT organizations are preparing for 2026 with increased expectations around modernization, cloud maturity, and data readiness. At the same time, many teams continue to operate with limited staffing and are trying to maintain complex environments with small internal groups. These conditions are creating a distinct set of priorities for the year ahead. The DataStrike 2026 Data Infrastructure Survey Report, based on responses from nearly 280 IT leaders across industries, points to five trends that are shaping data infrastructure planning for 2026 ...

Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...

Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...

Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...

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

The Latest

IT organizations are preparing for 2026 with increased expectations around modernization, cloud maturity, and data readiness. At the same time, many teams continue to operate with limited staffing and are trying to maintain complex environments with small internal groups. These conditions are creating a distinct set of priorities for the year ahead. The DataStrike 2026 Data Infrastructure Survey Report, based on responses from nearly 280 IT leaders across industries, points to five trends that are shaping data infrastructure planning for 2026 ...

Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...

Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...

Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...