S
SaloniAgrawal12
Introduction
Azure Load Testing is a cloud-based service that lets you test the performance and scalability of your web applications and APIs. You can create and run load tests, analyze and compare the results, and define test fail criteria based on metrics like response time, error percentage, and throughput.
Response time is the time your application takes to respond to a user request. It depends on factors like network latency, server load, and application logic. To measure the performance of your application, you need to look at the response time distribution across different percentiles, which show how many requests are completed within a certain time limit. For example, the 90th percentile response time means that 90% of the requests are completed within that time, and the remaining 10% take longer.
What's new in Azure Load Testing?
Until now, Azure Load Testing only supported three percentiles for response time analysis: Min, Max, Average, Median(50th), 90th, 95th, and 99th. These percentiles are common in the industry, but they may not match your SLA requirements. For instance, you may want to track the response time at the 75th percentile, which is a standard for web performance, or the 99.9th percentile, which is a stricter measure of the tail latency.
That's why we are happy to announce that Azure Load Testing now supports more percentiles for response time analysis. You can configure the percentiles you want for response time metrics in Azure Load Testing and meet your SLA goals. You can choose from these percentiles:
You can use these percentiles in different ways to analyze and compare your test results. For example, you can:
Configuring percentiles in Azure Load Testing is easy and intuitive. You can do it in two ways:
Using the Azure portal, you can configure the percentiles for response time metrics in the test criteria and the test results pages. In the test criteria page, you can select the aggregate function for the response time metric from the drop-down list that includes all the percentiles as shown below.
In the test results page, you can filter the sampler statistics UI and the response time graphs by the percentiles you want using the filters.
Using the YAML file, you can configure the percentiles for response time when running tests from your CI/CD pipelines. You can find more details on how to configure the YAML in our documentation.
Next Steps
If you haven't tried Azure Load Testing yet, you can create a resource and start testing your application today. If you are already using Azure Load Testing, you can configure the percentiles for your new tests and see the difference. Don't miss this chance to optimize your application performance and deliver a great user experience.
Thank you for choosing Azure Load Testing!
Continue reading...
Azure Load Testing is a cloud-based service that lets you test the performance and scalability of your web applications and APIs. You can create and run load tests, analyze and compare the results, and define test fail criteria based on metrics like response time, error percentage, and throughput.
Response time is the time your application takes to respond to a user request. It depends on factors like network latency, server load, and application logic. To measure the performance of your application, you need to look at the response time distribution across different percentiles, which show how many requests are completed within a certain time limit. For example, the 90th percentile response time means that 90% of the requests are completed within that time, and the remaining 10% take longer.
What's new in Azure Load Testing?
Until now, Azure Load Testing only supported three percentiles for response time analysis: Min, Max, Average, Median(50th), 90th, 95th, and 99th. These percentiles are common in the industry, but they may not match your SLA requirements. For instance, you may want to track the response time at the 75th percentile, which is a standard for web performance, or the 99.9th percentile, which is a stricter measure of the tail latency.
That's why we are happy to announce that Azure Load Testing now supports more percentiles for response time analysis. You can configure the percentiles you want for response time metrics in Azure Load Testing and meet your SLA goals. You can choose from these percentiles:
- Min
- Max
- Average
- Median (50th)
- 75th
- 90th
- 95th
- 96th
- 97th
- 98th
- 99th
- 99.9th
- 99.99th
You can use these percentiles in different ways to analyze and compare your test results. For example, you can:
- Define test fail criteria based on the percentiles you want for response time metrics.
- Filter the ‘Sampler Statistics’ UI by the percentiles you want for response time metrics.
- Filter the response time graphs by the percentiles you want for response time metrics.
Configuring percentiles in Azure Load Testing is easy and intuitive. You can do it in two ways:
- Using the Azure portal
- Using the YAML file
Using the Azure portal, you can configure the percentiles for response time metrics in the test criteria and the test results pages. In the test criteria page, you can select the aggregate function for the response time metric from the drop-down list that includes all the percentiles as shown below.
In the test results page, you can filter the sampler statistics UI and the response time graphs by the percentiles you want using the filters.
Using the YAML file, you can configure the percentiles for response time when running tests from your CI/CD pipelines. You can find more details on how to configure the YAML in our documentation.
Next Steps
If you haven't tried Azure Load Testing yet, you can create a resource and start testing your application today. If you are already using Azure Load Testing, you can configure the percentiles for your new tests and see the difference. Don't miss this chance to optimize your application performance and deliver a great user experience.
Thank you for choosing Azure Load Testing!
Continue reading...