> ## Documentation Index
> Fetch the complete documentation index at: https://docs.loadforge.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Worker Failures

> Learn how to resolve partial worker failures with LoadForge.

# Worker Failures

If you see an error about a **partial or total worker failure**, it means that at least one worker **failed during your test run**.

LoadForge has detected this failure, which typically occurs due to the test configuration or an excessive number of users overloading the worker servers. The quickest solution is to **increase the number of workers** to distribute the load more effectively.

<Note>
  **Tip:** Increase your test's **"Workers to Launch"** setting and re-run the test to see if it stabilizes.
</Note>

## Common Causes of Worker Failures

Worker failures are almost always caused by **overloaded test workers**. The capacity of a worker depends on the **complexity of the test and response times of the target application**.

A typical worker can handle:

* **Up to \~10,000 requests per second** in a well-optimized test scenario.
* **Up to \~40,000 requests per second** using the [FastHTTP client](/docs/examples/fasthttp-performance).

However, worker overload is more likely in the following cases:

* **Frequent errors in responses**: High failure rates consume additional processing power.
* **Slow server response times**: The longer a server takes to respond, the more active requests a worker must maintain.
* **Complex test scenarios**: Multiple user actions, authentication steps, and API calls increase CPU and memory usage per worker.

## How to Resolve Worker Failures

If you experience worker failures, try the following solutions:

1. **Increase the Number of Workers**
   * Add more workers under **"Workers to Launch"** to distribute the load.

2. **Reduce the Number of Virtual Users per Worker**
   * Instead of pushing a single worker to its limit, spread users across multiple workers.

3. **Check Your Server Response Times**
   * Use LoadForge's **Response Time Metrics** to identify slow endpoints.
   * Look for requests taking **10,000ms or more** to respond, as these can cause worker failures.
   * Optimize database queries, caching strategies, or API response times.

4. **Set Timeouts in Your Locustfile**
   * If the backend is too slow to respond, workers may hang indefinitely. To prevent this, set timeouts in your Locust test script.

Example timeout setting in Locust:

```python theme={null}
from locust import HttpUser, task, between

class MyUser(HttpUser):
    wait_time = between(5, 9)

    @task
    def test_request(self):
        self.client.get("/your-endpoint", timeout=10)
```

This ensures that if the server **takes longer than 10 seconds** to respond, the request fails instead of blocking the worker.

5. **Simplify Your Test Scenario**
   * If your test includes complex user interactions, consider **breaking it into smaller tests**.

6. **Use the FastHTTP Client (For High-Throughput Needs)**
   * If your test involves simple requests (e.g., static files, APIs), consider using **FastHTTP** for higher efficiency.

By fine-tuning your test configuration and setting **timeouts for slow responses**, you can **prevent worker failures** and ensure reliable load testing results.