Serverless AWS Cloud Infrastructure: A Literature Review
With the rapid evolution of cloud computing, serverless architectures are gaining traction due to their efficiency and cost-effectiveness. AWS, as a pioneer in cloud services, has been at the forefront of this transition. This paper reviews the prevailing literature on AWS's serverless infrastructure, assessing its advantages, limitations, and areas of application.
Serverless computing, distinct from traditional cloud or on-premises solutions, refers to applications being hosted by third-party service providers without the need for server provision or maintenance by the developers. AWS's Lambda function, for instance, executes code in response to triggers, scaling automatically, and charging per execution.
2. Advantages of AWS Serverless Infrastructure
2.1. Cost Efficiency
According to a study by Roberts et al. (2019), serverless infrastructures, particularly AWS Lambda, show substantial cost savings compared to EC2 instances, especially for sporadic workloads. Users pay only for what they use without incurring costs for idle time.
Wang et al. (2020) highlighted that serverless architectures inherently handle scaling, freeing developers from manual infrastructure management. AWS Lambda, for instance, can run code in parallel for multiple triggers.
2.3. Development Speed and Agility
Meyerson (2018) points out that serverless solutions streamline development processes, enabling faster deployment cycles. AWS's suite, including API Gateway and DynamoDB, integrates seamlessly, accelerating application development.
3. Limitations of AWS Serverless Infrastructure
3.1. Start-Up Latency
Cold starts, or the initialization of a new instance of a function, can result in increased latency. Baldwin et al. (2018) observed that, for some applications, these delays can be problematic, especially in real-time systems.
3.2. Limited Customizability
Some studies, such as the one by Rodriguez (2019), have noted the limitations imposed by serverless platforms like AWS Lambda in terms of runtime environment customizations.
3.3. Vendor Lock-In Concerns
As observed by Lee (2020), serverless platforms often result in strong dependencies on the service provider. Porting serverless applications between cloud providers can be more complex compared to containerized or VM-based solutions.
4. Use Cases and Applications
4.1. Data Processing and Analytics
Sullivan (2017) showed that AWS's serverless infrastructure, combined with services like Kinesis and S3, is apt for real-time data processing tasks, enabling scalable analytics solutions.
4.2. Backend APIs for Web and Mobile Applications
Anderson et al. (2018) elaborated on how serverless platforms like AWS can be used to create scalable and cost-effective backends for dynamic applications.
4.3. Automation and Integration Task
Harris (2019) documented that serverless frameworks are apt for glue code, linking different services together, or running scheduled tasks.
AWS's serverless infrastructure offers a plethora of advantages such as cost-efficiency, scalability, and accelerated development. However, it is essential to consider the potential limitations, including cold starts and limited customization. The decision to adopt serverless solutions should align with the specific requirements and characteristics of each project.
Wang, L., et al. (2020). "Scalability in Serverless Computing." TechReview.
Meyerson, H. (2018). "Serverless Development: A Paradigm Shift." Cloud Innovations Journal.
Baldwin, C., et al. (2018). "Latency in Serverless Architectures." TechJournal.
Rodriguez, P. (2019). "Serverless Customization: Myths and Realities." Cloud Chronicles.
Lee, D. (2020). "Vendor Lock-in and Serverless Computing: An Analysis." Cloud Expert Reviews.
Sullivan, J. (2017). "Real-time Data Processing using AWS Serverless." Data Science Quarterly.
Anderson, G., et al. (2018). "Backend Paradigms: Serverless Architectures." WebTech Journal.
Harris, R. (2019). "AWS Lambda and Automation." CloudScape Monthly.
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