case study

Intelligent Test Case Creation Mechanism

Technology

Business Impacts

Reduced time to market by leveraging exhaustive set of workflows

Increased operational efficiency by reducing manual efforts

Cost optimization by means of auto-scaling

Customer Key Facts

  • Location : USA
  • Industry : Technology

Problem  Context

The client is one of the largest private technology companies with more than 300 software products and a customer base of 14 million users in the market.

Prior to launch or update, each product first undergoes rigorous manual testing with ~200K cases covered. This requires large manpower and endless hours of manual effort.

Its customers, however, customize and integrate these products based on their business requirements which leads to unforeseen errors.

The client, therefore, wanted to create a cost-effective framework to track predominant customer workflows and create an exhaustive set of test cases.

Challenges

  • This use case was based on a novel idea with no prior research to fall upon with highly sensitive customer data and potentially support data from over million customers.
  • The solution was required to be application-agnostic, adaptable, and scalable to any of the client’s products.
  • Lack of in-house expertise in leveraging Cloud capabilities throughout the automation process.

Technologies Used

Amazon EMR

Amazon EMR

Amazon Route 53

Amazon Route 53

Amazon Aurora

Amazon Aurora

Amazon S3

Amazon S3

Amazon EKS

Amazon EKS

AWS KMS

AWS KMS

Amazon SQS

Amazon SQS

Amazon SNS

Amazon SNS

Solution

As the client expected large amounts of data to be collected daily, distributed processing was required to deliver results in a reasonable timeframe. Hence, EMR was chosen to process the data in a distributed manner.

Quantiphi leveraged Spark to process the data in parallel over multiple EMR clusters and convert JSON files into a processable format.

Our experts also securely created the EMR cluster to prevent it from being directly accessed from the internet. They also encrypted the data that persisted in S3 buckets. IAM roles were created with the principle of least privilege to access AWS resources.

Results

Built an effective test automation system  to auto-generate test plans and test cases  based on the usage patterns to test the web applications in a bug-free product environments

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