The power of in-sprint automation

A large securities firm sped up time-to-market with end-to-end test automation on the cloud.


A leading securities trading firm.


Build a cloud-based automation framework to test client’s trading platform.

Tools and technologies

C#, Ranorex, TestRail, Simulators and Selenium.

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The client had a legacy trading platform that had a stack of 33 applications built on various technologies and architectures. Testing new features and additions was a challenge. A simple change in one feature would warrant verification of the entire application.

Extensive regression testing and verification were needed to ensure that changes in one feature do not affect functionality elsewhere. This was a cumbersome process with some 30,000 test cases being checked and executed manually by more than 20 people. The client also had multiple squads working on different apps and functionalities that it was a challenge to ensure that changes made by one squad did not impact the overall functionality of the platform. The brief for Iris was to design and deploy a common cloud-based test automation framework to enable faster launch of new features.


Using its cloud-based ready-to-deploy test automation framework, Iris sped up deployment of new features. The Amazon Web Services based solution featured continuous testing of products on a common framework layer. It enabled capacity planning of spinned cloud instances and need-based shutdowns.

Iris executed the project using acceptance test driven development (ATDD), a methodology that involves collaboration between customers, business and development teams. What was unique about the approach? Typically, automation is introduced towards the end of a development cycle. In most projects, developers bring in automation in Sprint 4 for features developed in Sprint 1, 2 and 3. As a result, return on investment isn’t maximized. Iris introduced ‘in-sprint’ automation, enabling 90% test automation with every sprint. This resulted in more efficient testing and cost savings.


The new ability for complete capacity planning through the use of infrastructure-as-code for spinning up cloud instances helped the client achieve end-to-end automation of regression/ functional test cases. The specific gains for the client were as follows:

  • 90% faster execution in each sprint cycle
  • 80% faster script development
  • 100% configurable for on-demand execution on AWS
  • 70% reduction in cloud infrastructure
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