Your site’s performance directly affects your company’s bottom line. You can lower shopping cart abandonment when your site has better performance. And better performance directly results in more conversions and lower bounce rates. Check out these statistics.
Continuously performance testing websites, apps and infrastructure throughout the development cycle is a growing practice in the software industry.
We’re helping lead that charge by making Load Impact the most DevOps- and continuous delivery-friendly performance testing solution on the market.
We’ve talked to thousands of software developers around the world (we’ve been around for 6+ years now) and most people who decide to integrate Load Impact into their continuous integration environment have a few different reasons, but they all lead back to the same two principles: Saving time, and saving money.
In the previous article in this series, we talked about getting prepared for your performance testing by:
- Creating user scenarios
- Configuring and running smoke tests
- Creating load tests
At this point, you’re onto the actual testing. You’re running load tests and finding actionable data in the results.
We’ve broken this phase down into six parts, but it’s important to remember that each part may require multiple iterations. But hey, multiple iterations of each step just means you’re continuously finding new features to optimize or new problems to fix, and that will only improve the user experience in the long run.
Here at Load Impact, we’re constantly developing new features to help make our load testing tool even more powerful and easy to use. Our latest feature, Server Metrics, now makes it possible for you to measure performance metrics from your own servers and integrate these metrics with the graphs generated from your Load Impact test. This makes it much easier for you to correlate data from your servers with test result data, while helping you identify the reasons behind possible performance problems in your site. We do this by installing agents on your servers in order to grab server metrics data, which we can later insert into the results graph.