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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 Two: Literature Review

2.1 Serverless Computing Overview
2.2 Function-as-a-Service Overview
2.3 Data Streaming Pipelines
2.4 Serverless Computing for Data Streaming Pipelines
2.5 Function-as-a-Service for Data Streaming Pipelines
2.6 Challenges in Implementing Serverless Computing for Data Streaming Pipelines
2.7 Case Studies of Serverless Computing and Function-as-a-Service for Data Streaming Pipelines
2.8 Best Practices for Implementing Serverless Computing in Data Streaming Pipelines
2.9 Future Trends in Serverless Computing and Function-as-a-Service for Data Streaming Pipelines
2.10 Summary of Literature Review

Chapter Three: Research Methodology

3.1 Research Design
3.2 Data Collection Methods
3.3 Sampling Techniques
3.4 Data Analysis Methods
3.5 Ethical Considerations
3.6 Pilot Study
3.7 Data Validation Techniques
3.8 Limitations of Research Methodology

Chapter Four: Discussion of Findings

4.1 Implementation of Serverless Computing in Data Streaming Pipelines
4.2 Benefits of Function-as-a-Service for Data Streaming Pipelines
4.3 Performance Evaluation of Serverless Computing in Data Streaming Pipelines
4.4 Integration of Serverless Computing and Function-as-a-Service in Data Streaming Pipelines
4.5 Comparison with Traditional Data Processing Architectures
4.6 Scalability and Cost Considerations
4.7 Security and Privacy Issues
4.8 Future Research Directions

Chapter Five: Conclusion and Summary

5.1 Summary of Findings
5.2 Conclusion
5.3 Contributions to the Field
5.4 Implications for Practice
5.5 Recommendations for Future Research

Thesis Overview on Serverless Computing and Function-as-a-Service for Data Streaming Pipelines

Serverless computing and Function-as-a-Service (FaaS) are emerging paradigms that offer a new way of building and deploying applications without worrying about managing the underlying infrastructure. Data streaming pipelines are critical components in modern data processing systems, enabling real-time processing of large volumes of data. This thesis explores the use of serverless computing and FaaS in implementing data streaming pipelines and assesses their suitability, performance, and scalability for such applications.

The introduction provides a background of the study, problem statement, objectives, scope, limitations, and significance of the study. It also outlines the structure of the thesis and defines key terms used throughout the document. The literature review discusses the concepts of serverless computing, FaaS, data streaming pipelines, challenges, case studies, best practices, and future trends in these areas.

The research methodology details the design, data collection methods, sampling techniques, analysis methods, ethical considerations, pilot study, and validation techniques employed in the study. The discussion of findings section presents the implementation of serverless computing and FaaS in data streaming pipelines, benefits, performance evaluation, integration, comparisons, scalability, cost considerations, and security issues.

The conclusion and summary chapter summarizes the findings, provides conclusions, highlights contributions to the field, implications for practice, and recommendations for future research in the domain of serverless computing and FaaS for data streaming pipelines. By examining these technologies and their application in data streaming pipelines, this thesis aims to contribute to the understanding and advancement of modern data processing architectures for real-time analytics and decision-making.

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