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Understand Your Infrastructure's Usage and Load Characteristics for Online Success

Sven Hammar

Cyber Monday is here and it is instrumental to keep your e-commerce platform in perfect health. Key areas to keep an eye on are usage and load characteristics — they are gauges for interpreting how much work an online platform performs, and how well it performs under stress.

Understanding how your digital infrastructure performs is not as simple as assessing your car’s odometer to measure distance traveled, or its speedometer to measure the maximum speed. Usage and load characteristics provide insight into the performance of the platform in real-world use cases, like analyzing that metaphorical car’s journey from point A to point B.

Understanding what kind of usage and load capacity your service concurrently supports, as well as changes to those factors in the future, is a vital part of providing an excellent online user experience. Cloud computing and scaling services are great assets because you have almost unlimited server resources to handle traffic spikes and growth; however, your service may suffer if you are not configured to use it.

On the other side, you do not want to be paying for more power than you need. Use your interpretation of usage and load characteristics to know your limits, check up on the user experience, and evaluate poor performance issues.

Usage: How Much Are You Utilizing?

Usage characteristics are a practical way to measure how much server power you need to run your web or mobile platform. Your usage characteristics are going to break down into CPU, memory, storage, pageviews and network load statistics which can be measured over time or by time increments. The usage data sheds light on how much information your platform is moving to end users, as well as when it moves.

Usage can also tell you how many users are accessing your service at a specific time and compare that against usage statistics to see how hard they are pushing the system. An example usage characteristic would be your web application moving 100GB of data within a month and 10,000 pageviews per hour.

Load: Can You Take the Heat?

Load characteristics can tell you how well your platform performs depending on how many end users are accessing the service concurrently, as well as the maximum amount of work the service can handle before it starts to experience performance problems. Whereas usage testing identifies how much information moves, load testing examines how efficiently the service moves that information.

Load testing, whether performed during development or on a live, fully functioning application, is like test-driving the user experience to make sure everything runs smoothly on a larger scale.

Using load testing analytics, you can identify capacity shortcomings and single out bottleneck points where the platform or server instances can be improved. Load testing gauges how well a platform holds up in terms of service capacity, long-term high use endurance conditions, and demand spikes. It is great for identifying problems with latency as well — something usage data does not provide any insight into. An example load characteristic is the latency between users when a typical number is simultaneously using the service.

Combining Both for Hosting Capacity and Programming Efficiency Analysis

Looking at your web service’s usage and load characteristics helps answer the question of whether your platform needs to make programming efficiency improvements and adjust hosting resources.

If your service passes the test with little headroom, it is an indication that future growth will disrupt service quality. The performance data helps businesses avoid being victims of their own success. Unpredictable load and rapid use expansion can cause the service to falter if the hosting services are not prepared.

For example, when Pinterest first launched, they used a gated account approval method at first for gradually allowing new users to access the service. This prevented them from overloading the application and creating a poor user experience.

Take advantage of the information that usage and load characteristics provide, adjusting service capabilities and your auto scaling settings to address problems with real-world service use. Do not become a victim of your own online success!

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Understand Your Infrastructure's Usage and Load Characteristics for Online Success

Sven Hammar

Cyber Monday is here and it is instrumental to keep your e-commerce platform in perfect health. Key areas to keep an eye on are usage and load characteristics — they are gauges for interpreting how much work an online platform performs, and how well it performs under stress.

Understanding how your digital infrastructure performs is not as simple as assessing your car’s odometer to measure distance traveled, or its speedometer to measure the maximum speed. Usage and load characteristics provide insight into the performance of the platform in real-world use cases, like analyzing that metaphorical car’s journey from point A to point B.

Understanding what kind of usage and load capacity your service concurrently supports, as well as changes to those factors in the future, is a vital part of providing an excellent online user experience. Cloud computing and scaling services are great assets because you have almost unlimited server resources to handle traffic spikes and growth; however, your service may suffer if you are not configured to use it.

On the other side, you do not want to be paying for more power than you need. Use your interpretation of usage and load characteristics to know your limits, check up on the user experience, and evaluate poor performance issues.

Usage: How Much Are You Utilizing?

Usage characteristics are a practical way to measure how much server power you need to run your web or mobile platform. Your usage characteristics are going to break down into CPU, memory, storage, pageviews and network load statistics which can be measured over time or by time increments. The usage data sheds light on how much information your platform is moving to end users, as well as when it moves.

Usage can also tell you how many users are accessing your service at a specific time and compare that against usage statistics to see how hard they are pushing the system. An example usage characteristic would be your web application moving 100GB of data within a month and 10,000 pageviews per hour.

Load: Can You Take the Heat?

Load characteristics can tell you how well your platform performs depending on how many end users are accessing the service concurrently, as well as the maximum amount of work the service can handle before it starts to experience performance problems. Whereas usage testing identifies how much information moves, load testing examines how efficiently the service moves that information.

Load testing, whether performed during development or on a live, fully functioning application, is like test-driving the user experience to make sure everything runs smoothly on a larger scale.

Using load testing analytics, you can identify capacity shortcomings and single out bottleneck points where the platform or server instances can be improved. Load testing gauges how well a platform holds up in terms of service capacity, long-term high use endurance conditions, and demand spikes. It is great for identifying problems with latency as well — something usage data does not provide any insight into. An example load characteristic is the latency between users when a typical number is simultaneously using the service.

Combining Both for Hosting Capacity and Programming Efficiency Analysis

Looking at your web service’s usage and load characteristics helps answer the question of whether your platform needs to make programming efficiency improvements and adjust hosting resources.

If your service passes the test with little headroom, it is an indication that future growth will disrupt service quality. The performance data helps businesses avoid being victims of their own success. Unpredictable load and rapid use expansion can cause the service to falter if the hosting services are not prepared.

For example, when Pinterest first launched, they used a gated account approval method at first for gradually allowing new users to access the service. This prevented them from overloading the application and creating a poor user experience.

Take advantage of the information that usage and load characteristics provide, adjusting service capabilities and your auto scaling settings to address problems with real-world service use. Do not become a victim of your own online success!

Hot Topics

The Latest

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...

Despite the frustrations, every engineer we spoke with ultimately affirmed the value and power of OpenTelemetry. The "sucks" moments are often the flip side of its greatest strengths ... Part 2 of this blog covers the powerful advantages and breakthroughs — the "OTel Rocks" moments ...

OpenTelemetry (OTel) arrived with a grand promise: a unified, vendor-neutral standard for observability data (traces, metrics, logs) that would free engineers from vendor lock-in and provide deeper insights into complex systems ... No powerful technology comes without its challenges, and OpenTelemetry is no exception. The engineers we spoke with were frank about the friction points they've encountered ...

Enterprises are turning to AI-powered software platforms to make IT management more intelligent and ensure their systems and technology meet business needs for efficiency, lowers costs and innovation, according to new research from Information Services Group ...

The power of Kubernetes lies in its ability to orchestrate containerized applications with unparalleled efficiency. Yet, this power comes at a cost: the dynamic, distributed, and ephemeral nature of its architecture creates a monitoring challenge akin to tracking a constantly shifting, interconnected network of fleeting entities ... Due to the dynamic and complex nature of Kubernetes, monitoring poses a substantial challenge for DevOps and platform engineers. Here are the primary obstacles ...

The perception of IT has undergone a remarkable transformation in recent years. What was once viewed primarily as a cost center has transformed into a pivotal force driving business innovation and market leadership ... As someone who has witnessed and helped drive this evolution, it's become clear to me that the most successful organizations share a common thread: they've mastered the art of leveraging IT advancements to achieve measurable business outcomes ...

More than half (51%) of companies are already leveraging AI agents, according to the PagerDuty Agentic AI Survey. Agentic AI adoption is poised to accelerate faster than generative AI (GenAI) while reshaping automation and decision-making across industries ...

Image
Pagerduty

 

Real privacy protection thanks to technology and processes is often portrayed as too hard and too costly to implement. So the most common strategy is to do as little as possible just to conform to formal requirements of current and incoming regulations. This is a missed opportunity ...

The expanding use of AI is driving enterprise interest in data operations (DataOps) to orchestrate data integration and processing and improve data quality and validity, according to a new report from Information Services Group (ISG) ...