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The 5 Most Common Application Bottlenecks

Sven Hammar

Application bottlenecks can lead an otherwise functional computer or server to slow down to a crawl. The term "bottleneck" refers to both an overloaded network and the state of a computing device in which one component is unable to keep pace with the rest of the system, thus slowing overall performance.
 
Addressing bottleneck issues usually results in returning the system to operable performance levels; however, fixing bottleneck issues requires first identifying the underperforming component. These five bottleneck causes are among the most common:
 

1. CPU Utilization

 
According to Microsoft, "processor bottlenecks occur when the processor is so busy that it cannot respond to requests for time." Simply put, the central processing unit (CPU) is overloaded and unable to perform tasks in a timely manner.
 
CPU bottleneck shows up in two forms: a processor running at over 80 percent capacity for an extended period of time, and an overly long processor queue. CPU utilization bottlenecks often stem from insufficient system memory and continual interruption from input/output devices. Resolving these issues involves increasing CPU power, adding more random access memory (RAM), and improving software coding efficiency.
 

2. Memory Utilization

 
A memory bottleneck implies that the system does not have sufficient or fast enough RAM. This situation cuts the speed at which the RAM can serve information to the CPU, which slows overall operations. In cases where the system doesn’t have enough memory, the computer will start offloading storage to a significantly slower hard disc drive (HDD) or solid state drive (SSD) to keep things running. Alternatively, if the RAM cannot serve data to the CPU fast enough, the device will experience both slowdown and low CPU usage rates.
 
Resolving the issue typically involves installing higher capacity and/or faster RAM. In cases where the existing RAM is too slow, it needs to be replaced, whereas capacity bottlenecks can be dealt with simply by adding more memory. In other cases, the problem may stem from a programming error called a "memory leak," which means a program is not releasing memory for system use again when done using it. Resolving this issue requires a program fix.
 

3. Network Utilization

 
Network bottlenecks occur when the communication between two devices lacks the necessary bandwidth or processing power to complete a task quickly. According to Microsoft, network bottlenecks occur when there’s an overloaded server, an overburdened network communication device, and when the network itself loses integrity. Resolving network utilization issues typically involves upgrading or adding servers, as well as upgrading network hardware like routers, hubs, and access points.

4. Software Limitation

 
Sometimes bottleneck-related performance dips originate from the software itself. In some cases, programs can be built to handle only a finite number of tasks at once so the program won’t utilize any additional CPU or RAM assets even when available.
 
The most common cases of application problems are transactions that load the database and/or different system resources: static content, authentication, connections pools etc in way that is not optimized. I many cases configurations of application environments such as web server etc are done with default settings that respond poorly versus peak load traffic.
 

5. Disk Usage

 
The slowest component inside a computer or server is typically the long-term storage, which includes HDDs and SSDs, and is often an unavoidable bottleneck. Even the fastest long-term storage solutions have physical speed limits, making this bottleneck cause one of the more difficult ones to troubleshoot. In many cases, disk usage speed can improve by reducing fragmentation issues and increasing data caching rates in RAM. On a physical level, address insufficient bandwidth by switching to faster storage devices and expanding RAID (a data storage virtualization technology) configurations.
 
Load testing and monitoring tools are excellent at identifying bottleneck problems that hinder performance. Use these tools to optimize your business’s online platforms.

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The 5 Most Common Application Bottlenecks

Sven Hammar

Application bottlenecks can lead an otherwise functional computer or server to slow down to a crawl. The term "bottleneck" refers to both an overloaded network and the state of a computing device in which one component is unable to keep pace with the rest of the system, thus slowing overall performance.
 
Addressing bottleneck issues usually results in returning the system to operable performance levels; however, fixing bottleneck issues requires first identifying the underperforming component. These five bottleneck causes are among the most common:
 

1. CPU Utilization

 
According to Microsoft, "processor bottlenecks occur when the processor is so busy that it cannot respond to requests for time." Simply put, the central processing unit (CPU) is overloaded and unable to perform tasks in a timely manner.
 
CPU bottleneck shows up in two forms: a processor running at over 80 percent capacity for an extended period of time, and an overly long processor queue. CPU utilization bottlenecks often stem from insufficient system memory and continual interruption from input/output devices. Resolving these issues involves increasing CPU power, adding more random access memory (RAM), and improving software coding efficiency.
 

2. Memory Utilization

 
A memory bottleneck implies that the system does not have sufficient or fast enough RAM. This situation cuts the speed at which the RAM can serve information to the CPU, which slows overall operations. In cases where the system doesn’t have enough memory, the computer will start offloading storage to a significantly slower hard disc drive (HDD) or solid state drive (SSD) to keep things running. Alternatively, if the RAM cannot serve data to the CPU fast enough, the device will experience both slowdown and low CPU usage rates.
 
Resolving the issue typically involves installing higher capacity and/or faster RAM. In cases where the existing RAM is too slow, it needs to be replaced, whereas capacity bottlenecks can be dealt with simply by adding more memory. In other cases, the problem may stem from a programming error called a "memory leak," which means a program is not releasing memory for system use again when done using it. Resolving this issue requires a program fix.
 

3. Network Utilization

 
Network bottlenecks occur when the communication between two devices lacks the necessary bandwidth or processing power to complete a task quickly. According to Microsoft, network bottlenecks occur when there’s an overloaded server, an overburdened network communication device, and when the network itself loses integrity. Resolving network utilization issues typically involves upgrading or adding servers, as well as upgrading network hardware like routers, hubs, and access points.

4. Software Limitation

 
Sometimes bottleneck-related performance dips originate from the software itself. In some cases, programs can be built to handle only a finite number of tasks at once so the program won’t utilize any additional CPU or RAM assets even when available.
 
The most common cases of application problems are transactions that load the database and/or different system resources: static content, authentication, connections pools etc in way that is not optimized. I many cases configurations of application environments such as web server etc are done with default settings that respond poorly versus peak load traffic.
 

5. Disk Usage

 
The slowest component inside a computer or server is typically the long-term storage, which includes HDDs and SSDs, and is often an unavoidable bottleneck. Even the fastest long-term storage solutions have physical speed limits, making this bottleneck cause one of the more difficult ones to troubleshoot. In many cases, disk usage speed can improve by reducing fragmentation issues and increasing data caching rates in RAM. On a physical level, address insufficient bandwidth by switching to faster storage devices and expanding RAID (a data storage virtualization technology) configurations.
 
Load testing and monitoring tools are excellent at identifying bottleneck problems that hinder performance. Use these tools to optimize your business’s online platforms.

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Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...