Load Test Assertions

Detailed explanation

Load test assertions are crucial for determining whether a system meets its performance requirements under anticipated load conditions. They act as checkpoints during a load test, verifying that specific criteria are met, such as response times, error rates, and resource utilization. Without assertions, a load test simply generates traffic without providing meaningful insights into the system's behavior. These assertions are the key to transforming raw performance data into actionable information.

Assertions can be categorized based on what they validate:

• Response Time Assertions: These verify that the system responds within acceptable timeframes. For example, an assertion might check that the average response time for a specific API endpoint remains below 500ms under a load of 1000 concurrent users.
• Status Code Assertions: These validate that the system returns the correct HTTP status codes for different requests. For instance, an assertion could ensure that a successful POST request returns a 201 Created status code, while an invalid request returns a 400 Bad Request status code.
• Data Validation Assertions: These verify the correctness of the data returned by the system. This might involve checking that a specific field in a JSON response contains the expected value or that a database query returns the correct number of records.
• Error Rate Assertions: These monitor the number of errors encountered during the load test. An assertion might specify that the error rate should not exceed 1% under the peak load.
• Resource Utilization Assertions: These track the consumption of system resources, such as CPU, memory, and disk I/O. An assertion could check that CPU utilization remains below 80% during the load test.

Practical Implementation

Most load testing tools provide mechanisms for defining and executing assertions. Let's consider how assertions can be implemented using popular tools:

JMeter:

JMeter offers various assertion elements that can be added to test plans. Common assertions include:

• Response Assertion: Allows you to validate the response code, response message, response headers, or response body against a specified pattern (e.g., regular expression).
• Duration Assertion: Checks that the response time does not exceed a specified threshold.
• Size Assertion: Verifies that the response size falls within a specified range.
• JSON Assertion: Validates the structure and content of JSON responses.

Here's an example of a Response Assertion in JMeter that checks for a 200 OK status code:

1. Right-click on the HTTP Request sampler.
2. Add -> Assertions -> Response Assertion.
3. In the "Apply to" section, select "Main sample only."
4. In the "Field to Test" section, select "Response Code."
5. In the "Patterns to Test" section, add "200."
6. Select "Equals" as the pattern matching rule.

Gatling:

Gatling uses a Scala-based DSL for defining load tests, including assertions. Assertions are defined using the check method.

Here's an example of a Gatling assertion that verifies the response time for a specific request:

import io.gatling.core.Predef._
import io.gatling.http.Predef._
import scala.concurrent.duration._
 
class MySimulation extends Simulation {
 
  val httpProtocol = http
    .baseUrl("http://example.com")
 
  val scn = scenario("My Scenario")
    .exec(http("My Request")
      .get("/api/resource")
      .check(status.is(200),
             responseTimeInMillis.lt(500))) // Assertion: Status code is 200 and response time is less than 500ms
 
  setUp(scn.inject(atOnceUsers(100))).protocols(httpProtocol)
}

This code snippet defines a scenario that sends a GET request to /api/resource and asserts that the status code is 200 and the response time is less than 500 milliseconds.

k6:

k6 uses JavaScript for defining load tests and assertions. Assertions are performed using the check function.

Here's an example of a k6 assertion that verifies the response time and status code:

import http from 'k6/http';
import { check } from 'k6';
 
export default function () {
  const res = http.get('http://example.com/api/resource');
  check(res, {
    'status is 200': (r) => r.status === 200,
    'response time < 500ms': (r) => r.timings.duration < 500,
  });
}

This code sends a GET request to /api/resource and asserts that the status code is 200 and the response time is less than 500 milliseconds.

Best Practices

• Define Assertions Early: Identify critical performance metrics and define assertions before starting the load test. This ensures that you collect the necessary data and can quickly identify performance bottlenecks.
• Use a Variety of Assertions: Don't rely solely on response time assertions. Incorporate assertions that validate status codes, data correctness, and resource utilization to gain a comprehensive understanding of the system's behavior.
• Set Realistic Thresholds: Base assertion thresholds on performance requirements and service level agreements (SLAs). Avoid setting overly strict thresholds that trigger false positives or overly lenient thresholds that mask real performance issues.
• Monitor Assertion Results: Continuously monitor assertion results during the load test. This allows you to identify performance problems in real-time and adjust the test parameters as needed.
• Automate Assertion Evaluation: Integrate assertion evaluation into the continuous integration/continuous delivery (CI/CD) pipeline. This ensures that performance regressions are detected early in the development lifecycle.
• Use Descriptive Assertion Names: Give your assertions meaningful names that clearly indicate what they are validating. This makes it easier to interpret the results and troubleshoot failures.
• Consider Correlation: In some cases, you may need to correlate data between requests to perform assertions. For example, you might need to extract a session ID from the response of one request and use it in a subsequent request.

Common Tools

• Apache JMeter: A popular open-source load testing tool with a wide range of assertion elements.
• Gatling: A powerful open-source load testing tool with a Scala-based DSL for defining assertions.
• k6: A modern load testing tool with a JavaScript API for defining assertions.
• LoadView: A cloud-based load testing platform with built-in assertion capabilities.
• BlazeMeter: A cloud-based load testing platform that supports JMeter, Gatling, and other load testing tools.

By carefully defining and implementing load test assertions, you can ensure that your system meets its performance requirements and delivers a positive user experience under load.

Further reading

• JMeter Assertions
• Gatling Checks
• k6 Checks
• Load Testing Best Practices