AI Analysis

This component provides a high-level summary of key findings from your test run, including:

• Key Issues: Notable slow endpoints, high error rates, or other problem areas
• Response Time Insights: Breakdown of performance trends, including slowest P95 and P99 times
• Recommendations: Suggested optimizations based on detected inefficiencies
• Error Analysis: Common errors (5xx, timeouts, etc.), their frequency, and possible causes

This component provides AI-powered recommendations for refining your Locustfile test script, including:

• Adjusting wait times to better simulate real users
• Adding multiple request types to make load tests more realistic
• Tweaking spawn rates to avoid unrealistic traffic spikes
• Enhancing validation to check response status codes and data integrity

# Before: Simple test with fixed wait time
@task
def index_page(self):
    self.client.get("/")

# After: Enhanced test with variable wait and validation
@task
def index_page(self):
    with self.client.get("/", catch_response=True) as response:
        if response.status_code != 200:
            response.failure(f"Got status {response.status_code}")

This component identifies likely sources of slowdowns based on:

• Your website’s tech stack (e.g., PHP, Node.js, Python, database type)
• Server infrastructure (e.g., Nginx, Apache, cloud-based hosting)
• Common scaling issues related to API calls, caching strategies, or database queries