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Revamping Test Automation for Sprinklr: A Case Study
Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
- Application Infrastructure & Middleware - Middleware, SDKs & Libraries
Applicable Industries
- Buildings
- Construction & Infrastructure
Applicable Functions
- Maintenance
- Quality Assurance
Use Cases
- Experimentation Automation
- Leasing Finance Automation
Services
- System Integration
- Testing & Certification
The Challenge
Sprinklr, a tech platform designed to assist large brands in creating and managing social campaigns, was facing significant challenges with their testing processes. The existing test suite, developed by another company, was unstable and unreliable. Each test run resulted in a different number of randomly failed tests, making it impossible for the team to rely on the tests for release decisions. The tests were time-consuming, often taking several hours to complete. The architecture of the test suite was not scalable and was difficult to maintain for a large number of tests. Furthermore, the tests could not be integrated with other testing and DevOps tools. The challenge was to build a formal QA process, stabilize automated tests, increase their speed, redesign the architecture to support integration with third-party tools, and keep test documentation up to date.
The Customer
Sprinklr
About The Customer
Sprinklr is a technology platform that helps large brands create and manage social campaigns. They were struggling with an unstable and unreliable test suite that was developed by another company. The tests were time-consuming and could not be integrated with other testing and DevOps tools. The architecture of the test suite was not scalable and was difficult to maintain for a large number of tests. The team was unable to rely on the tests for release decisions. They needed a solution that would stabilize their automated tests, increase their speed, and allow for integration with third-party tools.
The Solution
DeviQA took on the challenge and designed the architecture of the test framework from scratch. They developed over 2,000 auto-tests and built a test suite that ran these tests using 16 threads on multiple machines, significantly speeding up the testing process. They also improved test speeds by adding the prerequisite testing data directly to the database. A team of seven people performed full cycle testing of the project, significantly improving the quality of the product. The automated tests were integrated with Jenkins, TestRail, and Jira to create a complete test ecosystem. Performance testing was also implemented using JMeter, with the suite and all scenarios created from scratch. Remote monitors were set up on the server side and configured to catch metrics. The automated and performance tests were integrated into a Continuous Integration process, enabling the team to detect and solve issues promptly.
Operational Impact
Quantitative Benefit
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