Feasibility study for Serverless Ticketing and Settlement eCommerce platform

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Learn how we helped to design and present a feasibility study of the reliable ticketing platform with the use of cloud computing services.

Executive Summary

Our team successfully designed and presented a feasibility study of the scalable, resilient, and reliable ticketing platform with the use of cloud computing and serverless architecture on Amazon Web Services.

Key Figures:

  • 2000% improvement on scalability (to 10 000 orders per second).
  • 227% improvement in latency (99.9% under 450 ms).
  • Business continuity during increased traffic periods improved by 24% (which now is 100% uptime).
  • 150% cost-effectiveness improvement in comparison to IaaS infrastructure.

About the Subject

Outpace the national market leader providing ticketing and settlement end-to-end solutions.

Challenges and Objectives

The presented project is a feasibility study that shows technical and business capabilities of implementing online ticketing platform as a serverless system. Everything to provide available, reliable, and cost-efficient e-commerce platform which survives even the biggest spikes of the traffic and secures business continuity.

Our goal was to design a software platform which will meet the business requirements regarding the high volume of transactions, users, and integration with multiple partners.

The biggest challenge for our team was to design the architecture with the lowest possible latency, as this metric is crucial in the checkout process. It is also the most significant factor of the abandoned transactions when the system tries to survive the biggest traffic spikes.

As we have not prepared a theoretical study, one of our additional goals was to deliver a minimum viable product (MVP), that will support our conclusions. Prepared proof of concept was carefully evaluated in the following areas:

  • Functional end-to-end tests.
  • Comprehensive performance tests - which included stress tests and endurance testing.
  • Verifying observability of every single transaction, with particular emphasis on the faulty ones.


Pattern Match has assembled a cost-efficient and scalable solution that can withstand the promoted interest in the particular event.


Thanks to the extensive testing, we could provide a clear answer, that such a solution will be performant, reliable, and cost-effective. The presented proof of concept unambiguously confirms the feasibility study.

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