Anusha Joodala

Performance Benchmarking of Serverless vs. Container-Based Banking Workloads

Abstract:

This presentation explores a comparative performance benchmarking study between serverless computing platforms such as AWS Lambda and Azure Functions, and container-based deployment models using Docker and Kubernetes for modern banking workloads. The research evaluates critical performance parameters including response time, throughput, scalability, operational cost, and security compliance in financial transaction systems.

The study demonstrates that serverless architectures are highly effective for low-volume and unpredictable workloads due to their automatic scalability, rapid provisioning, and reduced operational overhead. In contrast, containerized deployments provide greater operational predictability, resource control, and efficiency for sustained high-frequency banking operations such as fraud detection, payment processing, and real-time analytics.

A trade-off analysis highlights that both architectures offer unique advantages depending on workload intensity and traffic patterns, indicating that no single solution fits all banking scenarios. The research further examines security isolation and PCI-DSS compliance considerations across both deployment models. Based on the findings, a hybrid cloud implementation strategy is proposed to optimize performance, reduce infrastructure costs, and maintain regulatory compliance. The results provide evidence-based recommendations for financial institutions and cloud architects designing scalable, resilient, and cost-effective cloud-native banking infrastructures.

Keywords: Serverless Computing, Container Orchestration, Banking Workload Benchmarking, Cloud Performance Optimization, Scalability and Latency Analysis.

 

Profile:

Anusha Joodala is a Java AWS Developer and cloud technology professional with experience in enterprise application development, cloud modernization, database systems, and banking technology solutions. She currently works in the Payments division at JPMorgan Chase, contributing to cloud-based banking applications, modernization initiatives, production deployments, and enterprise technology enhancements.

She has previously worked in Business Intelligence, SQL development, ETL systems, reporting, analytics, and database administration across government and enterprise organizations. Her technical expertise includes Java, Spring Boot, AWS Cloud Services, Kubernetes, Docker, Microservices, Kafka, SQL Server, Oracle, and cloud-native architectures.

Anusha is also an active researcher and author with publications in cloud computing, intelligent systems, machine learning, and banking modernization. Her research interests include scalable cloud architectures, serverless computing, AI-driven automation, and performance optimization for enterprise financial systems.