Received 27.01.2026, Revised 22.05.2026, Accepted 25.06.2026 Published 03.08.2026

Methodology for automating enterprise business processes based on API integration

Dmytro Zahorulko*

student675@ukr.net



In the context of rapid digitalisation and a high level of heterogeneity of contemporary corporate ecosystems, the problem of fragmentation of the information space, and the emergence of isolated data warehouses becomes a critical barrier to business efficiency. The purpose of the study was to develop and substantiate a comprehensive methodology for automating business processes of an enterprise based on the application programming interface – integration of the application programming interface, combining the choice of optimal architectural patterns with mechanisms for secure data exchange. To achieve this goal, the researchers applied system analysis of architectural styles, prototyping of software gateways in Python, and computer modelling of load scenarios in an isolated virtual environment using Docker containers and the Locust tool. The study involved a comparative analysis of the Representational State Transfer, Simple Object Access Protocol, and Graph Query Language protocols in terms of performance and network load, which revealed significant traffic overhead and delays of up to 185 ms when using outdated standards. A hybrid integration methodology was proposed that combines the Representation State Transfer architecture for mobile clients and Graph Query Language for web interfaces, which reduced the amount of transmitted data by 73% and reduced the system response time to 65 ms. A secure data exchange algorithm has been developed based on the use of an intermediate layer (middleware) and a security gateway (API Gateway), which implement two-level request validation and centralised access control to neutralise the risks of unauthorised interference. The expediency of using the "Strangler Fig" migration pattern was substantiated, which allowed for a gradual transition from monolithic enterprise resource planning systems to microservice architecture through a specialised Python gateway without stopping operational activities. It has been experimentally proven that the introduction of asynchronous message queues allows the system to maintain stable operation within 320 ms even at peak loads of up to 5,000 requests per second, in contrast to monolithic solutions that demonstrate exponential performance degradation

heterogeneous IT environments; REST; GraphQL; security gateways; Strangler Fig migration pattern; middleware; network latency minimisation
35-43
Zahorulko, D. (2026). Methodology for automating enterprise business processes based on API integration. Information Technologies and Computer Engineering, 23(2), 35-43. https://doi.org/10.31649/vitce/2.2026.35

References

  1. Aldea, C.L., & Bocu, R. (2025). Authentication challenges and solutions in microservice architectures. Applied Sciences, 15(22), article number 12088. doi: 10.3390/app152212088.
  2. Alaghbari, K.A., Lim, H.-S., Saad, M.H.M., & Yong, Y.S. (2023). Deep autoencoder-based integrated model for anomaly detection and efficient feature extraction in IoT networks. IoT, 4(3), 345-365. doi: 10.3390/iot4030016.
  3. Bajrami, E., Memeti, A., Idrizi, F., & Memeti, E. (2024). Comparative analysis of SOAP and REST APIs: Systematic review and performance evaluation with Python. Journal of Natural Sciences and Mathematics of UT-JNSM, 9(17-18), 228-243. doi: 10.62792/ut.jnsm.v9.i17-18.p2818.
  4. Bogner, J. (2020). On the evolvability assurance of microservices: Metrics, scenarios, and patterns. (Doctoral thesis, Vrije Universiteit Amsterdam, Amsterdam, Netherlands). doi: 10.18419/opus-10950.
  5. Chandra Mouli, R. (2022). Implementation of DevSecOps for a microservices-based application with service mesh. Gaithersburg: National Institute of Standards and Technology. doi: 10.6028/NIST.SP.800-204C.
  6. El Kafhali, S., El Mir, I., & Hanini, M. (2022). Security threats, defense mechanisms, challenges, and future directions in cloud computing. Archives of Computational Methods in Engineering, 29, 223-246. doi: 10.1007/s11831-021-09573-y.
  7. Fava, F.B., Leite, L.F.L., Da Silve, L.F.A., Da Silva Amalfi Costa, P.R., Nogueira, A.G.D., & Lopes, A.F.G. (2024). Assessing the performance of docker in docker containers for microservice-based architectures. In 32nd Euromicro international conference on parallel, distributed and network-based processing (pp. 137-142). New York: IEEE. doi: 10.1109/PDP62718.2024.00026.
  8. Joyce, J.V., Edna, K.R.J., Sherubha, P., & Arivazhagi. (2024). Link-based Xcorr normalization and attention mechanism for predicting the threats over the network model. Journal of Cybersecurity and Information Management, 13(2), 96-108. doi: 10.54216/JCIM.130208.
  9. Matias, M., Ferreira, E., Mateus-Coelho, N., Ribeiro, O., & Ferreira, L. (2024). Evaluating effectiveness and security in microservices architecture. Procedia Computer Science, 237, 626-636. doi: 10.1016/j.procs.2024.05.148.
  10. Mandala, N.R. (2022). Data integration in heterogeneous systems. ESP Journal of Engineering & Technology Advancements, 2(4), 148-155. doi: 10.56472/25832646/JETA-V2I4P122.
  11. Newman, S. (2021). Building microservices: Designing fine-grained systems. Santa Rosa: O’Reilly Media.
  12. Niswar, M., Safruddin, R.A., Bustamin, A., & Aswad, I. (2024). Performance evaluation of microservices communication with REST, GraphQL, and gRPC. International Journal of Electronics and Telecommunications, 70(2), 429-436. doi: 10.24425/ijet.2024.149562.
  13. Kozlovska, M., & Piskozub, A. (2024). Development of effective web security measures for networks through penetration testing using the OWASP framework. Ukrainian Information Security Research Journal, 26(1), 101-110. doi: 10.18372/2410-7840.26.18833.
  14. Szewczyk, M., & Skublewska-Paszkowska, M. (2025). Performance comparison of development frameworks in selected environments in REST API architecture. Journal of Computer Sciences Institute, 35, 121-128. doi: 10.35784/jcsi.7041.
  15. Lercher, A., Glock, J., Macho, C., & Pinzger, M. (2024). Microservice API evolution in practice: A study on strategies and challenges. Journal of Systems and Software, 215, article number 112110. doi: 10.1016/j.jss.2024.112110.
  16. Tereshchenko, O.I., Koretska, V.O., Trytina, N.A., & Oleneva, K.M. (2024). Development of a toolkit to simplify the construction of microservice applications. Telecommunications and Information Technologies, 1(82), 45-55. doi: 10.31673/2412-4338.2024.014555.
  17. Ford, N., Richards, M., Sadalage, P., & Dehghani, Z. (2021). Software architecture: The hard parts. Modern trade-off analyses for distributed architectures. Santa Rosa: O’Reilly Media.
  18. Li, C.-Y., Ma, S.-P., & Lu, T.-W. (2020). Microservice migration using strangler fig pattern: A case study on the green button system. In 2020 international computer symposium (pp. 519-524). New York: IEEE. doi: 10.1109/ICS51289.2020.00107.
  19. Pryhoda, A.Ya. (2024). Software migration from monolithic architecture to microservices architecture as a way of protecting CRM systems. Ukrainian Journal of Information Tecnology, 6(2), 90-97. doi: 10.23939/ujit2024.02.090.
  20. Waseem, M., Liang, P., & Shahin, M. (2020). A systematic mapping study on microservices architecture in DevOps. Journal of Systems and Software, 170, article number 110798. doi: 10.1016/j.jss.2020.110798.