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Introduction

Serverless computing is a cloud computing paradigm that allows developers to build and run applications without the need to manage the underlying infrastructure. In serverless computing, the cloud provider dynamically manages the allocation of machine resources based on the actual usage of the application. This enables developers to focus on writing code and building applications, without worrying about server provisioning, scaling, or maintenance.

Real-time data processing is a critical requirement for many modern applications, especially those that deal with streaming data or require immediate responses to user actions. Traditional server-based approaches to real-time data processing can be complex and expensive to manage, making serverless computing an attractive alternative for real-time data processing applications.

This thesis aims to explore the potential of serverless computing for real-time data processing, investigating its benefits, challenges, and best practices. The research will involve a comprehensive review of the existing literature, a detailed analysis of relevant technologies, and empirical studies to evaluate the performance and scalability of serverless solutions for real-time data processing.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter 2: Literature Review
2.1 Overview of Serverless Computing
2.2 Real-time Data Processing
2.3 Serverless Architectures for Real-time Data Processing
2.4 Challenges in Serverless Computing for Real-time Data Processing
2.5 Best Practices in Serverless Computing for Real-time Data Processing
2.6 Comparison of Serverless Platforms for Real-time Data Processing
2.7 Case Studies of Serverless Implementations for Real-time Data Processing
2.8 Security and Privacy Considerations in Serverless Real-time Data Processing
2.9 Scalability and Performance in Serverless Real-time Data Processing
2.10 Future Trends in Serverless Computing for Real-time Data Processing

Chapter 3: Research Methodology
3.1 Research Approach
3.2 Data Collection Methods
3.3 Data Analysis Techniques
3.4 Experimental Design
3.5 Evaluation Metrics
3.6 Tool Selection
3.7 System Architecture
3.8 Performance Evaluation

Chapter 4: Discussion of Findings
4.1 Overview of Findings
4.2 Performance Evaluation Results
4.3 Scalability Analysis
4.4 Comparison of Serverless Platforms
4.5 Best Practices and Recommendations
4.6 Limitations and Challenges
4.7 Future Research Directions
4.8 Implications for Real-world Applications

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusions
5.3 Contributions to Knowledge
5.4 Practical Implications
5.5 Recommendations for Future Research
5.6 Closing Remarks

Thesis Overview on Serverless Computing for Real-time Data Processing

Serverless computing is a revolutionary approach to cloud computing that offers developers the ability to build and run applications without the burden of managing server infrastructure. Real-time data processing, on the other hand, is a critical requirement for many modern applications that deal with streaming data or require immediate responses to user actions. The combination of serverless computing and real-time data processing offers a promising solution for developing scalable, efficient, and cost-effective applications.

This thesis aims to explore the potential of serverless computing for real-time data processing, investigating its benefits, challenges, and best practices. The research will involve a comprehensive review of the existing literature, a detailed analysis of relevant technologies, and empirical studies to evaluate the performance and scalability of serverless solutions for real-time data processing. The findings of this research will contribute to the body of knowledge on serverless computing and real-time data processing, providing insights and recommendations for developers, researchers, and organizations interested in leveraging these technologies for their applications.

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