Automated Biometrics NFT in Continuous Testing and Monitoring

As users are moving towards digitally enabled services, Biometrics option will be widely used across the
originations which will raise a question in terms of Non Functional capability of this feature in any user
channels (Mobile/Web) and how do we ensure, its performance efficient when wide range of users are using it, particularly with Mobile App rather just ensuring the security as user experience is also a significant aspect in terms of building good reputation and having better business growth. 

The key challenge is, how to assess/validate and simulate the complex human real-time interactions with the finger print/face recognition, and also how the dynamic login challenge can be generated and mapped against each user in runtime during load testing is unknown and complex mechanism to know the performance of biometrics and it’s system capacity, and due to the nature of biometrics working mechanism it was difficult to test the real-life journey from app perspective during runtime as both public key and login challenge should be created and mapped for each unique test users and same has to be passed into biometrics services before that gets expired and validated for successful biometrics login. It’s again needs to be integrated in the process of continuous testing and monitoring in DevOps model will be another challenge for faster time to market.

The load simulation on Biometrics use cases can be done via any load testing tool, but we can make use of Neoload effectively for simulating actual backend services of biometrics by integrating Java script and Java algorithms to generate dynamic keys, login challenges and mapping them against each user to validate the unique authenticity which enables that rare biometrics use case also performance tested and allows developers/performance engineers fine tune it further. Also, the same test suites setup can be integrated with DevOps model using Jenkins and Dynatrace/Any APM tool will help us in enabling continuous monitoring for faster time to fix if any performance bottlenecks arises.

Implementation Approach:

• Develop java based algorithm and functions as per solution design for generating public/private keys and login challenge for each users
• Capture Biometrics backend microservices using Neoload
• Develop Neoload script and write customized JavaScript to invoke java algorithms and functions to get public/private keys and login challenge
• Integrate Java, Neoload and JavaScript together for seamless testing with real-world load test scenario to assess the performance of Biometrics and it’s infrastructure
• Integrate the test suite with Jenkins Jobs and Biometrics services with Dynatrace/APM tools for
  continuous testing and monitoring respectively