tests — load

Module: tests-load Cohesion: 0.80 Members: 0

tests — load

This document describes the tests/load/multi-agent-load.test.ts module, which provides a framework for simulating and evaluating the performance characteristics of a multi-agent system under various load conditions.

1. Introduction

The multi-agent-load.test.ts module is a dedicated suite for conducting load tests on a simulated multi-agent system. Its primary goal is to assess the system's performance, stability, and resource utilization when processing a high volume of concurrent requests. This module helps identify potential bottlenecks, verify concurrency handling, and ensure consistent response times and memory usage.

The tests are designed to be flexible, allowing developers to define different load profiles (concurrency, total requests) and evaluate key metrics such as:

2. Core Concepts: Simulated Agent Processing

At the heart of this load testing framework is the simulation of individual agent work. Since these are load tests and not integration tests, they do not call actual application APIs. Instead, they mimic the behavior of an agent processing a request.

simulateAgentProcessing(id: number)

This asynchronous function simulates the work an agent would perform.

3. Load Test Execution Flow

The runLoadTest function orchestrates the entire load test, managing concurrency and collecting performance metrics.

High-Level Flow

graph TD
    A[runLoadTest] --> B{Loop totalRequests by concurrency};
    B --> C[runBatch];
    C --> D[simulateAgentProcessing (concurrently)];
    D --> E[Collect results];
    E --> F[Calculate LoadTestResult];

runLoadTest(concurrency: number, totalRequests: number)

This is the main function for executing a load test scenario.

  1. Initialization: It initializes an empty array results to store individual response times, and counters for successful and failed requests. It also records the startTime of the test.
  2. Batch Processing: It iterates through the totalRequests in chunks defined by the concurrency parameter. For each chunk, it calls runBatch.
  3. Concurrency Management: The runBatch helper function is responsible for creating and awaiting a batch of simulateAgentProcessing promises concurrently using Promise.all.

  1. Metric Calculation: After all batches are processed, runLoadTest calculates various performance metrics:

  1. Result Return: It returns a LoadTestResult object containing all calculated metrics.

runBatch(batchStart: number, batchSize: number)

This internal helper function is called by runLoadTest to execute a specific number of simulated agent processes concurrently. It creates an array of promises by calling simulateAgentProcessing for each request in the batch and then uses Promise.all to wait for all of them to complete.

4. Key Components

interface LoadTestResult

Defines the structure of the object returned by runLoadTest, encapsulating all the performance metrics gathered during a test run. 

interface LoadTestResult {
  totalRequests: number;
  successfulRequests: number;
  failedRequests: number;
  avgResponseTime: number;
  maxResponseTime: number;
  minResponseTime: number;
  requestsPerSecond: number;
}

simulateAgentProcessing(id: number): Promise<{ id: number; time: number }>

As described above, this function simulates a single unit of work with a variable delay.

runLoadTest(concurrency: number, totalRequests: number): Promise

The primary function for initiating and managing a load test, returning comprehensive performance statistics.

runBatch(batchStart: number, batchSize: number): Promise

An internal utility function used by runLoadTest to execute a group of simulateAgentProcessing calls concurrently.

5. Test Suites and Assertions

The module uses Jest's describe and it blocks to define various load test scenarios and assert expected outcomes.

Multi-Agent Load Tests

This suite focuses on the performance and stability of the simulated system under increasing load.

Concurrent Agent Processing

Throughput Tests

Response Time Distribution

Memory and Resource Tests

This suite specifically targets potential memory leaks, which are critical for long-running systems.

should not leak memory during repeated operations

6. How to Extend and Contribute

To add new load test scenarios or modify existing ones:

  1. Define a new it block: Within an existing describe block or a new one, create a new test case using it('should describe your scenario', async () => { ... });.
  2. Call runLoadTest: Invoke await runLoadTest(concurrency: number, totalRequests: number) with your desired load parameters.
  3. Add Assertions: Use expect(result.metric).toBe... to assert against the LoadTestResult object. Consider asserting:

  1. Adjust Timeout: If your test involves a large number of requests or high delays, increase the Jest timeout for the test using it('...', async () => { ... }, timeoutMs);.
  2. Refine simulateAgentProcessing: If the simulation needs to be more complex (e.g., simulating I/O, CPU-bound tasks, or external service calls), modify simulateAgentProcessing to reflect those behaviors.

This module provides a robust and flexible foundation for understanding the performance characteristics of a multi-agent system, even in a simulated environment.