Banking & Financial Services

Quality engineering optimizes a DLT platform

Reliability, availability, scalability, observability, and resilience ensured; release cycles and testing time improve 75% and 80%.

Client
A leading provider of financial services digitization solutions
Goal
Reliability assurance for a digital ledger technology (DLT) platform
Tools and Technologies
Kotlin, Java, Http Client, AWS, Azure, GCP, G42, OCP, AKS, EKS, Docker, Kubernetes, Helm Chart, Terraform
Business Challenge

A leader in Blockchain-based digital financial services required assurance for non-GUI (Graphic User Interface), Command Line Interface (CLI), microservices and Representational State Transfer (REST) APIs for a Digital Ledger Technology (DLT) platform, as well as platform reliability assurance on Azure, AWS services (EKS, AKS) to ensure availability, scalability, observability, monitoring and resilience (disaster recovery). It also wanted to identify capacity recommendations and any performance bottlenecks (whether impacting throughput or individual transaction latency) and required comprehensive automation coverage for older and newer product versions and management of frequent deliveries of multiple DLT product versions on a monthly basis.

Solution
  • 130+ Dapps were developed and enhanced on the existing automation framework for terminal CLI and cluster utilities
  • Quality engineering was streamlined with real-time dashboarding via Grafana and Prometheus
  • Coverage for older and newer versions of the DLT platform was automated for smooth, frequent deliverables for confidence in releases
  • The test case management tool, Xray, was implemented for transparent automation coverage
  • Utilities were developed to execute a testing suite for AKS, EKS, local MAC/ Windows/ Linux cluster environments to run on a daily or as-needed basis
Outcomes
  • Automation shortened release cycles from 1x/month to 1x/week; leads testing time was reduced by 80%
  • Test automation coverage with 2,000 TCs was developed, with pass rate of 96% in daily runs
  • Compatibility was created across AWS-EKS, Azure-AKS, Mac, Windows, Linux and local cluster
  • Increased efficiency in deliverables was displayed, along with an annual $350K savings for TCMs
  • An average throughput of 25 complete workflows per second was sustained
  • Achieved a 95th percentile flow-completion time that should not exceed 10 seconds
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