\chapter{Conclusion and Future Research Directions}
\label{conclusions}

\section{Summary of Key Findings and Contributions}

This thesis has undertaken a comprehensive exploration of scalability and fault tolerance within the domain of microservice architectures. The analysis reveals that achieving these critical system qualities is not an incidental outcome of adopting microservices but requires a deliberate, multi-faceted architectural approach. Key findings underscore that robust microservice systems are built upon a foundation of well-chosen design patterns, enabling technologies, and proactive resilience engineering practices.

The shift from monolithic to microservice architectures offers inherent advantages for targeted scalability and improved fault isolation. However, the distributed nature of microservices introduces new complexities, including challenges in inter-service communication, data management, and operational overhead. This research has systematically examined strategies to address these challenges. For scalability, patterns such as horizontal scaling, load balancing, API gateways and asynchronous processing via message queues have been identified as crucial. For fault tolerance, patterns including circuit breakers advantages intelligent retries with backoff are essential for building resilient systems.

The role of enabling technologies cannot be overstated. Containerization with Docker and orchestration with Kubernetes (including its diverse autoscaling mechanisms like HPA) provide the platform for dynamic resource management. Furthermore, comprehensive observability—through monitoring and logging emerges as the bedrock upon which effective scaling and fault diagnosis are built. Proactive resilience practices represent a paradigm shift towards anticipating and mitigating failures before they impact users.

The primary contribution of this thesis is the design, end-to-end implementation, and empirical validation of a holistic architectural framework for microservices. This framework was brought to life through a concrete e-commerce application built with .NET and deployed on Kubernetes, demonstrating how to effectively integrate a suite of modern cloud-native technologies.

Specifically, this work established a blueprint for:
\begin{itemize}

\item Independent Scalability: Leveraging Kubernetes and the Horizontal Pod Autoscaler, we proved how services can scale automatically based on real-time CPU demand.
\item Layered Fault Tolerance: Resilience was woven into the architecture at multiple levels—from application-level Retry and Circuit Breaker patterns using Polly to infrastructure-level self-healing via Kubernetes and guaranteed message delivery through RabbitMQ.
\item Decoupled Communication: Asynchronous messaging was employed to decouple the Order, Inventory, and Payment services, enhancing both resilience and scalability.
\item Comprehensive Observability: A full monitoring stack using Prometheus and Grafana was integrated, providing crucial, real-time visibility into system performance and resource utilization under load.

\end{itemize}

Crucially, this thesis moved beyond theoretical design by subjecting the system to rigorous load testing with Locust. The results provided empirical evidence that the InventoryService is stable, performant, and CPU-bound under sustained load, validating that the configured auto-scaling policies would be triggered under real-world conditions.

Ultimately, this thesis argues and demonstrates that scalability and fault tolerance are deeply symbiotic. The successful integration of the specific patterns and technologies presented here—where observability informs scaling, and resilience patterns protect services during that scaling—is key to developing microservice applications that are not only adaptable to dynamic demands but are verifiably durable in the face of inevitable failures.

\section{Limitations of the Study}

It is imperative to recognize certain limitations inherent in this study. The rapid pace of innovation in microservices and their associated technologies means that some of the specific tools and performance metrics presented herein may have a limited shelf life. Furthermore, the empirical validation was conducted on a specific e-commerce platform within a controlled setting; consequently, the generalizability of these findings to other domains or application types is not guaranteed. Finally, the scope of this thesis was intentionally focused on scalability and fault tolerance, thereby excluding an in-depth analysis of other vital microservice considerations such as security, data consistency, and the developer experience, which remain fruitful avenues for future research.


\section{Future Research Directions}

The dynamic and complex nature of microservice architectures presents numerous opportunities for future research. Several promising avenues include:

\begin{itemize}
    \item AI and Machine Learning for Intelligent System Management \cite{walia2025leveraging} \cite{makungu2023fault}
    \item Advanced Chaos Engineering and Resilience Verification \cite{gremlin2023chaos}
    \item Serverless Architectures and Function-as-a-Service (FaaS)
    \item Dynamic Microservice Architectures \cite{baboi2019dynamic} \cite{ibrahim2022scalable}
    
\end{itemize}

Addressing these research areas will contribute to the continued evolution of microservice architectures, enabling the development of even more scalable, resilient, and intelligent distributed systems.