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SERVERLESS BILLING AUTOMATION SYSTEM
10.12.2025 19:13
[1. Information systems and technologies]
Author: Vitalii Merdak, master student, Ivano‑Frankivsk National Technical University of Oil and Gas, Department of Software Engineering, Ivano‑Frankivsk, Ukraine; Roman Vovk, Candidate of Technical Sciences, Associate Professor, Ivano-Frankivsk National Technical University of Oil and Gas, Department of Software Engineering, Ivano-Frankivsk, Ukraine
ORCID: 0000-0003-0681-4534 Roman Vovk
Automating the invoicing process is a key task in modern accounting. Manual preparation of invoices is time-consuming and prone to human errors. This study presents an REST API project using a modern technology stack and serverless architecture [1] to optimize invoice generation. The goal is to demonstrate how serverless computing can streamline billing tasks while reducing operational costs.
The project is built on ASP.NET Core 8.0 [2] with FastEndpoints for rapid REST API development. Entity Framework Core [3] and PostgreSQL handle database interactions. Testing is implemented with xUnit, while Docker is used for containerization. FluentValidation ensures data integrity.
A key feature is the serverless architecture on AWS [4]: Lambda functions handle incoming requests, Amazon S3 stores generated PDF invoices, SQS queues manage asynchronous task distribution, and RDS Postgres serves as the relational database. This approach [5] allows paying only for resource usage since invoices are generated periodically (once or a few times per month), eliminating the need to maintain a constantly running server and reducing maintenance overhead.
The database includes the following entities:
• User — independent entity.
• Employee — has many Workdays and Invoices, belongs to one Department and one Project.
• Department — has many Employees.
• Project — has many Employees.
• Workday — belongs to one Employee.
• Invoice — belongs to one Employee.
These relationships allow efficient tracking of employee work, linking invoices to specific projects, and ensuring scalable database design.
Data Flow (fig. 1):
• The frontend sends a request to the Web API Lambda.
• The Lambda writes data to the RDS Postgres database.
• The Lambda sends an invoice_id message to the Worker SQS Queue.
• The Worker SQS Queue triggers the Worker Lambda, which generates a PDF and uploads it to S3.
• Worker Lambda updates the invoiceUrl in the database.
• Worker Lambda sends a message with the generated_invoice_id to the Emailer SQS Queue.
• The Emailer Lambda retrieves the invoice from S3 and sends it to the employee's email.
• The Web API Lambda requests a pre-signed URL from S3 for the invoice.
Fig. 1. AWS infrastructure and data flow
This asynchronous flow ensures efficient task distribution, reduces system load, and allows rapid scaling when multiple invoices need generation.
Advantages of Serverless Architecture
• Pay-per-use: Resources are charged only when invoices are generated, lowering operational costs.
• No server maintenance: No need to manage OS updates or server configuration.
• Scalability: Lambda functions automatically scale based on request volume.
• Asynchronous processing: SQS queues allow background processing without blocking the system.
• Secure storage: Invoices are stored in S3 with access controlled via pre-signed URLs.
The developed system ensures high scalability by automatically increasing the capacity of Lambda functions during peak loads, while asynchronous processing via SQS queues enhances its overall fault tolerance. Thus, the system offers a flexible, reliable, and cost-effective alternative to traditional infrastructure solutions. This approach can serve as an efficient foundation for implementing modern corporate information systems that require dynamic and economical resource management.
References
1. Newman S. Building Microservices: Designing Fine-Grained Systems. O'Reilly Media, 2015.
2. Microsoft Docs. ASP.NET Core 8.0. URL: https://learn.microsoft.com/en-us/aspnet/core/ (date of access: 01.02.2025).
3. Microsoft Docs. Entity Framework Core. URL: https://learn.microsoft.com/en-us/ef/core/ (date of access: 02.02.2025).
4. Amazon Web Services. AWS Lambda, S3, SQS. URL: https://aws.amazon.com/ (date of access: 03.03.2025).
5. Fowler M. Patterns of Enterprise Application Architecture. Addison-Wesley, 2002.
Ця робота ліцензується відповідно до Creative Commons Attribution 4.0 International License
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