BEYOND THE MONOLITH: COMPREHENSIVE STRATEGIES FOR ARCHITECTING, SCALING, AND SUSTAINING RESILIENT DISTRIBUTED SYSTEMS
Keywords:
Distributed Systems, Microservices, Scalability, Fault Tolerance, Cloud Computing, Resilience, Database Optimization, Serverless Computing, Edge Computing, IoT Integration, AI-driven Optimization, Dynamic OrchestrationAbstract
The rapid evolution of distributed systems has transformed the way applications are architected, scaled, and sustained. This paper examines the transition from monolithic architectures to scalable and resilient distributed systems. It identifies key challenges such as fault tolerance, data consistency, and scalability bottlenecks, and proposes comprehensive strategies to address these issues. Leveraging advancements in microservices, serverless computing, and AI-driven optimization, this study outlines frameworks for building robust systems capable of meeting modern scalability and performance demands. The paper also highlights emerging trends, including edge computing and IoT integration, offering insights into future research directions.
References
Thakur, A., Chauhan, S., Tomar, I., Paul, V., & Gupta, D. (2024). Self-healing Nodes with Adaptive Data-Sharding. arXiv. https://arxiv.org/pdf/2405.00004.
Assad, M., Meiklejohn, C., Miller, H., & Krusche, S. (2024). Can My Microservice Tolerate an Unreliable Database? Resilience Testing with Fault Injection and Visualization. arXiv. https://arxiv.org/pdf/2404.01886.
Mohottige, T. I., Polyvyanyy, A., Buyya, R., Fidge, C., & Barros, A. (2024). Microservices-based Software Systems Reengineering: State-of-the-Art and Future Directions. arXiv. https://doi.org/10.48550/arXiv.2407.13915.
Exploring Microservices Design Patterns and Their Impact on Scalability. (2023). SSRN. https://papers.ssrn.com/sol3/Delivery.cfm/4984327.pdf?abstractid=4984327&type=2.
Evaluating The Impact Of Cloud-Based Microservices Architecture On Performance. (2023). arXiv. https://arxiv.org/pdf/2305.15438.
Vangala, R. R. (2023). Adaptive Resilience Framework: Dynamic Orchestration and Auto-Scaling of Microservices in Cloud-Native Systems. ResearchGate. https://www.researchgate.net/profile/Rajender-Reddy-Vangala/publication/378127572_ADAPTIVE_RESILIENCE_FRAMEWORK_A_COMPREHENSIVE_STUDY_ON_DYNAMIC_ORCHESTRATION_AND_AUTO-SCALING_OF_MICROSERVICES_IN_CLOUD-NATIVE_SYSTEMS.pdf.
Chen, A. C. H. (2023). Research on Efficiency Analysis of Microservices. arXiv. https://doi.org/10.48550/arXiv.2303.15490.
Karimi, M., & Abdollahzadeh Barfroush, A. (2023). Proposing a Dynamic Executive Microservices Architecture Model for AI Systems. arXiv. https://doi.org/10.48550/arXiv.2308.05833.
Koponen, T., & Manner, J. (2023). Database Management System Performance Comparisons: A Systematic Review. arXiv. https://doi.org/10.48550/arXiv.2301.01095.
Černý, T., Abdelfattah, A. S., Bushong, V., Al Maruf, A., & Taibi, D. (2022). Microservice Architecture Reconstruction and Visualization Techniques: A Review. arXiv. https://doi.org/10.48550/arXiv.2207.02988.
Chaos Engineering for Building Resilient Distributed Systems. (2020). IJSR. https://www.ijsr.net/archive/v9i3/SR24716231253.pdf.
Newman, S. (2021). Building Microservices: Designing Fine-Grained Systems (2nd ed.). O'Reilly Media. https://learning.oreilly.com/library/view/building-microservices-2nd/9781492034018/.
Wolff, E. (2020). Microservices: Flexible Software Architecture. Addison-Wesley. https://microservices-book.com.
Richardson, C. (2018). Microservices Patterns: With examples in Java. Manning Publications. https://www.manning.com/books/microservices-patterns.
Kleppmann, M. (2017). Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O'Reilly Media. https://dataintensive.net
Tanenbaum, A. S., & Van Steen, M. (2017). Distributed Systems: Principles and Paradigms (3rd ed.). Pearson. https://komputasi.wordpress.com/wp-content/uploads/2018/03/mvsteen-distributed-systems-3rd-preliminary-version-3-01pre-2017-170215.pdf