Shift Left, Eliminating Waste, and Implementation of DevOps
Performance testing software helps check an application’s behaviour under different scenarios that are reflective of production usage. It helps us evaluate and establish the software application’s speed, scalability, and stability. With most of the projects being delivered in sprints compared to the traditional waterfall methodology, it is imperative that performance testing is conducted iteratively. In this way, it’s possible to focus on testing smaller increments of functionality within short iterations.
SourceFuse provides end-to-end performance testing solutions to help our clients launch future-proof applications with high responsiveness, availability, and scalability. Our teams have adapted to deliver performance testing services efficiently while implementing the following techniques:
- Test earlier and faster with open source and third-party tool integration
- Performance testing as part of Continuous Deployment and DevOps models
- Comprehensive analysis and recommendations for performance improvements
- Optimize and eliminate waste to save effort and cost
- Production monitoring and alerts for continuous improvements
‘Test earlier and faster’ incorporates performance testing activities earlier in the Software Development Life Cycle (SDLC). This typically takes place during the development or testing phases as part of each sprint or iteration, providing immediate feedback on the impact of code changes or new features on system performance. The goal is to identify and address performance-related issues early in the development process.
A typical implementation of this is how we have leveraged the new performance features offered by Postman to performance test the API’s in the QA Environment only. With minimal training needed by the manual QA teams already using Postman, we can conduct basic performance testing to get early insights on the API performance in Dev/QA environments with minimalistic load. With manual QA setting up well-defined collections, the performance team is able to leverage these test suites and export them to JMeter for testing in Stage Environments. This removes the need to create new API suites, thereby ‘optimizing and eliminating waste’.
‘Continuous Deployment and DevOps’ through Jenkins also helped to achieve ‘test earlier and faster’ by executing the regression suites for applications in a daily or scheduled pattern. With every code deployment, we are able to compare the performance of the application. Wherever possible the scripts are reused and tests can be executed in Dev, QA and Stage environments to get early feedback. On a release basis, relevant performance flows are added to the regression tests to ensure new baselines are set.
Collaborating with DevOps can help to scale the lower environments similar to Prod environments and then scale down once the run is completed, reducing the infra costs and manual effort. The process helps maintain the pace of development and ensures that performance requirements are met by the time the product is released.
‘Optimizing and eliminating waste’ can also be achieved by utilizing the Jmeter – Selenium integration. To reduce the effort spent in developing the UI scripts in JMeter, the existing functional automations scripts are referenced and modified accordingly. This helps even the junior resources to quickly pick up the scripting without extensive training.
‘Production monitoring and alerts’ have been simplified by creating dashboard templates that can be easily rolled out for new applications with minimal updates. Dashboards are created for application monitors as well as synthetic monitors and availability statistics are tracked for applications in production. Monitoring application post-release performance helps to promptly address any issues and continuously improve the product.
In Summary
Our approach to performance testing is tailored to match the requirements of each client and project. But unique to every project is a rigorous profile of tests designed to apply load and identify bottlenecks ensuring that we deliver on the following values:
- Customer Satisfaction
Increase business revenue by ensuring the system can process transactions within the requisite timeframe
- Application Performance Improvement
Enhanced experience and quality delivered to the end user
- Increased Reliability
Reduce increased software maintenance costs due to early bug identification
- Capacity Management
Reduce additional operational overhead for handling system issues due to performance problems
- Glitch Resolution
Ensure any glitch is resolved before it reaches the customer
- Enhance Scalability & Stability
Identify future bottlenecks by simulation over a prototype
