Crafting Realistic Workloads
Design sophisticated workload models that accurately reflect diverse user behavior and business processes.
Crafting Realistic Workloads is a free Load Testing & Performance Benchmarking (JMeter & k6) lesson on CoddyKit — lesson 1 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Load Testing & Performance Benchmarking (JMeter & k6) learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
The Art of Realistic Workloads
Welcome to "Crafting Realistic Workloads"! In performance testing, a workload model defines how virtual users interact with your system during a test.
It's crucial because a realistic model ensures your test results accurately predict how your system will perform under real-world conditions, helping you find actual bottlenecks.
Defining Your Virtual Users
Start by identifying your user personas. Who uses your application? (e.g., guest, registered user, administrator). Each persona might have different behaviors.
Then, map out their typical business processes or "user journeys." What steps do they take? (e.g., "Guest browses products," "Registered user adds to cart and checks out").
Balancing Actions and Operations
A transaction mix describes the proportion of different actions users perform. For example, 70% of users might browse, 20% search, and only 10% make a purchase.
This mix should reflect real-world usage patterns, often derived from analytics data or business requirements, to accurately simulate system load.
The Importance of Think Time
Think time (or pacing) is the pause a real user takes between actions. Without it, virtual users send requests as fast as possible, which is unrealistic and can overwhelm the system.
Adding realistic delays simulates human interaction, making your load test more accurate and preventing premature bottlenecks.
Shaping Your Load Profile
A load test typically has three phases: ramp-up, steady-state, and ramp-down.
- Ramp-up: Gradually increases the number of virtual users.
- Steady-state: Maintains a constant peak load for a duration.
- Ramp-down: Gradually decreases the number of virtual users.
These phases simulate how user load changes over time in the real world.
Dynamic Data for Unique Users
For a truly realistic workload, each virtual user should use unique, varied data. This prevents caching effects from skewing results and simulates diverse user inputs.
Instead of logging in with "user1" repeatedly, simulate multiple users like "user1", "user2", "user3", each with their own unique data set for actions.
Sourcing Real-World Insights
Where do you find the data to build your workload model?
- Web Analytics: Tools like Google Analytics provide user behavior patterns.
- Server Logs: Access logs reveal request frequencies and popular endpoints.
- Business Intelligence: Reports on sales, user activity, etc.
- Product Owners/Managers: Direct insights into expected user journeys and peak usage.
JMeter: Throughput Controller
In JMeter, the Throughput Controller is excellent for defining a transaction mix. It allows you to specify a percentage of executions for its child elements.
For example, you can have one controller for "Browse Products" with 70% throughput and another for "Checkout" with 10% throughput, reflecting your desired mix.
k6: Defining Multiple Scenarios
k6's scenarios block is powerful for modeling diverse user behaviors. You can define multiple scenarios, each with its own executor, VUs, and duration, to simulate complex workloads.
Here's an example simulating different user types with distinct load patterns:
import http from 'k6/http';
import { sleep } from 'k6';
export const options = {
scenarios: {
browserUser: {
executor: 'constant-vus',
vus: 10,
duration: '30s',
exec: 'browserUserFlow', // function to execute
tags: { type: 'browser' },
},
apiUser: {
executor: 'ramping-vus',
startVUs: 0,
stages: [
{ duration: '10s', target: 5 },
{ duration: '20s', target: 5 },
{ duration: '5s', target: 0 },
],
exec: 'apiUserFlow', // function to execute
tags: { type: 'api' },
},
},
};
export function browserUserFlow() {
http.get('https://test.k6.io/public/croco-products/');
sleep(5);
http.get('https://test.k6.io/news.php');
sleep(3);
}
export function apiUserFlow() {
http.get('https://test-api.k6.io/public/croco/1');
sleep(1);
}Realistic Workload Components
Which of the following are essential components when designing a realistic workload model for performance testing? (Select all that apply)
Recap: Crafting Realistic Loads
In this lesson, we explored the critical elements of crafting realistic workload models for performance testing.
- We covered defining user personas, business processes, and transaction mix.
- We emphasized the importance of pacing, concurrency patterns, and dynamic data.
- Finally, we looked at how to implement these models using tools like JMeter and k6.
A well-designed workload is the foundation for meaningful performance test results!
Frequently asked questions
Is the “Crafting Realistic Workloads” lesson free?
Yes — the full text of “Crafting Realistic Workloads” is free to read here on the web, and the Load Testing & Performance Benchmarking (JMeter & k6) course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Load Testing & Performance Benchmarking (JMeter & k6) course, upgrade to CoddyKit PRO.
What will I learn in “Crafting Realistic Workloads”?
Design sophisticated workload models that accurately reflect diverse user behavior and business processes. You practise Load Testing & Performance Benchmarking (JMeter & k6) with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Load Testing & Performance Benchmarking (JMeter & k6)?
No prior experience is required. Load Testing & Performance Benchmarking (JMeter & k6) on CoddyKit is structured for beginners through advanced learners; this is — lesson 1 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Crafting Realistic Workloads” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Load Testing & Performance Benchmarking (JMeter & k6) lesson?
Yes. Every Load Testing & Performance Benchmarking (JMeter & k6) lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Crafting Realistic Workloads
- Reporting to Stakeholders
- Scaling Performance Testing Efforts
- Building a Performance Testing Strategy