A Comprehensive Survey on Serverless Computing: Challenges and Opportunities

Manuel Piantino^*
*Correspondence: Manuel Piantino, Department of Business Information Systems, Pantheon-Sorbonne University, 12 Pl. du Panthéon, 75231 Paris, France, Email:

Introduction

Serverless computing has emerged as a paradigm shift in cloud computing, offering a promising approach to deploy and manage applications without worrying about underlying infrastructure. This research article presents a comprehensive survey on serverless computing, highlighting its fundamental concepts, architectures, benefits, challenges, and opportunities. Through an extensive review of existing literature, this survey aims to provide insights into the current state of serverless computing, identify challenges faced by practitioners and researchers, and explore potential avenues for future research and innovation in this rapidly evolving domain.

Serverless computing, often referred to as Function-as-a-Service, is a cloud computing model where developers can deploy individual functions or units of code without managing the underlying infrastructure. In traditional cloud computing models like Infrastructure-as-a-Service and Platform-as-a-Service, developers are responsible for provisioning, scaling, and maintaining servers or containers to run their applications [1-3]. However, in serverless computing, the cloud provider dynamically manages the allocation of resources based on the demand for each function.

Functions are triggered by events such as HTTP requests, database changes, file uploads, or scheduled tasks. This event-driven architecture enables a highly responsive and scalable system. With serverless computing, users only pay for the compute resources consumed by their functions during execution. There are no charges for idle resources, making it a cost-effective option for sporadically used or unpredictable workloads. Cloud providers automatically scale the infrastructure up or down in response to changes in workload demand. This elastic scaling ensures that applications can handle fluctuaDescriptiontions in traffic without manual intervention.

Description

Functions in serverless architectures are stateless, meaning they do not maintain any persistent state between invocations. State management is typically handled by external services like databases or object storage. Developers are abstracted from the underlying infrastructure, including servers, virtual machines, and containers. They can focus on writing and deploying code without worrying about server provisioning, scaling, or maintenance. Serverless computing offers several benefits, including improved developer productivity, reduced operational overhead, scalability, and cost-effectiveness. However, it also presents challenges such as cold start latency, resource constraints, limited observability, security concerns, and vendor lock-in.

Overall, serverless computing represents a paradigm shift in cloud computing, enabling developers to build and deploy applications more efficiently while allowing cloud providers to manage the underlying infrastructure more dynamically and cost-effectively. The evolution and adoption trends of serverless computing have been significant, reflecting the increasing demand for scalable, cost-effective, and developer-friendly cloud computing solutions. Here's an overview of the evolution and adoption trends:

The concept of serverless computing began to emerge in the early 2010s with the introduction of Backend-as-a-Service providers like Firebase and Parse, which offered managed backend services for mobile and web applications. Amazon Web Services pioneered the serverless movement with the launch of AWS Lambda in 2014, marking the formal introduction of Function-as-a-Service to the cloud computing landscape. Other cloud providers such as Microsoft Azure and Google Cloud Platform followed suit by introducing their own serverless offerings, including Azure Functions and Google Cloud Functions [4,5].

Early adopters and innovative startups began experimenting with serverless computing for various use cases, including web applications, IoT (Internet of Things) devices, real-time data processing, and event-driven architectures. Serverless gained traction among developers due to its simplicity, scalability, and pay-per-use pricing model, which appealed to organizations seeking to reduce infrastructure costs and operational complexity.

As serverless technologies matured and gained broader industry acceptance, enterprises started adopting serverless computing for a wide range of applications and workloads. Major industries such as finance, healthcare, e-c ommerce, and media began leveraging serverless architectures to build scalable, resilient, and cost-efficient applications. Serverless frameworks and tools evolved to address the growing needs of enterprises, offering enhanced development, deployment, monitoring, and management capabilities. The serverless ecosystem expanded with the emergence of third-party services, libraries, and integrations that complemented cloud provider offerings, enabling developers to build more complex and feature-rich applications.

Organizations increasingly adopt hybrid and multi-cloud strategies, combining serverless offerings from different cloud providers to leverage the strengths of each platform and mitigate vendor lock-in. Serverless architectures are being extended beyond public cloud environments to support on-premises and edge computing use cases, enabling organizations to deploy functions closer to where data is generated or consumed. Interoperability standards and open-source initiatives aim to promote portability and compatibility between serverless platforms, facilitating seamless migration and deployment across diverse environments.

Conclusion

Serverless computing continues to evolve with advancements in areas such as performance optimization, security, observability, orchestration, and tooling. Emerging technologies like serverless containers, serverless databases, and serverless machine learning frameworks are expanding the scope of serverless computing and enabling new application scenarios. Adoption of serverless computing is expected to grow further as organizations embrace digital transformation initiatives, accelerate cloud migration efforts, and seek innovative solutions to address evolving business challenges and opportunities. Overall, the evolution and adoption trends of serverless computing underscore its transformative potential in reshaping the way applications are developed, deployed, and managed in the cloud-native era.

References

Serverless computing continues to evolve with advancements in areas such as performance optimization, security, observability, orchestration, and tooling. Emerging technologies like serverless containers, serverless databases, and serverless machine learning frameworks are expanding the scope of serverless computing and enabling new application scenarios. Adoption of serverless computing is expected to grow further as organizations embrace digital transformation initiatives, accelerate cloud migration efforts, and seek innovative solutions to address evolving business challenges and opportunities. Overall, the evolution and adoption trends of serverless computing underscore its transformative potential in reshaping the way applications are developed, deployed, and managed in the cloud-native era.