Error Rate of Jmeter Execution Report

Question

I execute jmeter script via Blazemeter and I got 2% error. Is it a acceptable rate?

In detail report I observed 1353 request are failed. I just run the script for one user. In that case non of the request doesn't fail. So is that failures are due to performance issue?

Following is summary of the report. Kindly help me to anlyse this.

Answer 1

Most probably your application simply cannot handle the load of 50 concurrent users. With regards to "acceptable" - we don't know. If you're load testing a fan page of your local hip hop star - even 90% error rate will be acceptable. If you're testing an algorithm which will be deployed on a Mars rover and will have to work without errors and modifications for 20 years - it is not.

Normally maximum response time, minimum throughput, acceptable number of errors, etc. are defined in SLA or NFR. If you don't have those and performing some form of stress testing of your application and want to figure out the root cause of the performance bottleneck - take the next steps:

1. Check your application log file(s), they should have some information regarding the failure

2. Check status message and code in .jtl results file. Sometimes it also makes sense to "tell" JMeter to save response data for failed samplers by adding the next lines to user.properties file:

   jmeter.save.saveservice.output_format=xml
   jmeter.save.saveservice.response_data.on_error=true
   

3. Make sure you add the load gradually, this way you will be able to correlate increasing error rate with increasing number of users and will be able to determine exact point of time when first error occurred
4. Get used to monitoring whether your application under test has enough headroom to operate in terms of CPU, RAM, Network, Disk, etc. It can be done using JMeter PerfMon Plugin
5. If you have ability to read and understand the code in the language your application is written in - it would be beneficial if you could run your test with profiler tool telemetry enabled, this is probably the most efficient way to identify the performance problem in your application.