AI Analysis

Performance 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

Use the Performance Analysis to quickly identify whether failures were due to scaling limitations, slow database queries, or high server load.

Test Script Suggestions

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

Example Script Improvement

# 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}")

If your test results seem inconsistent, the AI might suggest adjusting your spawn rate to create a more gradual load increase.

Bottleneck Detection

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

Pay special attention to endpoints with high variance between P50 and P95 response times, as these often indicate database query issues or inefficient caching.

The bottleneck detection can help you prioritize optimization efforts by focusing on the components that will provide the greatest performance improvements.

Why Use AI Analysis?

LoadForge’s AI saves time by:

Automatically analyzing performance data.

Highlighting critical issues immediately.

Suggesting targeted improvements for both test scripts and server performance.

Providing insights tailored to your site’s architecture.

By leveraging AI-powered insights, you can fine-tune your load tests and optimize your application’s performance with minimal manual effort.

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Essentials

Hosts

Performance

Tests

Test Scripting

Runs & Results

Integrations

Cloud

Why Use AI Analysis?

​Why Use AI Analysis?

Why Use AI Analysis?