The global serverless computing market is experiencing unprecedented growth, driven by the increasing demand for scalable, cost-efficient, and agile cloud solutions across a variety of industries. Serverless computing, also known as Function-as-a-Service (FaaS), enables developers to build and deploy applications without managing the underlying infrastructure, allowing organizations to focus on core business activities rather than server maintenance. As digital transformation accelerates worldwide, serverless platforms are being increasingly adopted for their ability to streamline development workflows, enhance operational efficiency, and reduce costs. Enterprises across sectors such as finance, healthcare, retail, manufacturing, and information technology are leveraging serverless frameworks to enable faster innovation, reduce time-to-market, and accommodate unpredictable workloads with ease. The core advantages of serverless computing is its event-driven execution model, where resources are dynamically allocated based on application demand. This eliminates the need for provisioning and managing servers, resulting in lower operational overhead and improved scalability. Leading cloud service providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) are heavily investing in serverless technologies and expanding their service offerings with advanced features such as automatic scaling, integrated monitoring, multi-language support, and seamless i

ntegration with DevOps tools. The proliferation of microservices architecture and the rise of containerization are further fueling the adoption of serverless models, as organizations seek modular and reusable codebases to enhance application resilience and flexibility. According to the research report “Global Serverless Computing Market Outlook, 2030” published by Bonafide Research, the Global Serverless Computing market is projected to reach market size of USD 51.23 Billion by 2030 increasing from USD 21.28 Billion in 2024, growing with 15.61% CAGR by 2025-30. Serverless computing enables businesses to deploy applications without provisioning or managing servers, reducing infrastructure costs and allowing developers to focus on writing and deploying code. This pay-per-use model is especially beneficial in dynamic workloads where scalability is critical, such as in e-commerce during peak traffic seasons or in data analytics requiring sudden processing bursts. In November 2022, ModelScope, an open-source Model-as-a-Service (MaaS) platform from Alibaba Cloud, was introduced with big pre-trained models and hundreds of AI models for researchers and developers worldwide. To further assist clients in achieving business innovation through cloud technologies, the cloud provider provided various serverless database products and enhanced its integrated data analytics and intelligent computing platform. For instance, Amazon’s AWS Lambda, Microsoft’s Azure Functions, and Google C

loud Functions have expanded support for more languages and integration tools, improving developer experience and broadening use-case applicability. These platforms are also investing in automation, edge computing capabilities, and enhanced security protocols to appeal to a wider enterprise audience. Additionally, the rise of DevOps and CI/CD (Continuous Integration/Continuous Deployment) pipelines has elevated serverless computing’s value, as it aligns perfectly with modern software development practices focused on speed and flexibility. Additionally, performance issues such as cold start delays when functions take time to initialize after periods of inactivity can impact user experience. The compute server type holds the largest share in the global serverless computing market primarily due to its foundational role in executing backend logic, event-driven tasks, and dynamic workloads that form the core of serverless architectures. In serverless computing, the compute layer is responsible for processing functions triggered by events or user actions whether that be API calls, database changes, or real-time data streams. This essential functionality positions compute services like AWS Lambda, Azure Functions, and Google Cloud Functions at the center of most serverless deployments. Their ability to execute code in a stateless environment, automatically scale in real-time, and bill users based on execution time and memory consumption makes them ideal for modern application develo

pment. The rising adoption of microservices and cloud-native development practices further accelerates the demand for compute serverless services. As enterprises break monolithic applications into smaller, independently deployable services, the need for a responsive, lightweight execution model grows. Compute-based serverless platforms perfectly meet this requirement by allowing developers to deploy individual functions that run only when needed, enhancing performance while reducing operational costs. This is especially important in high-traffic scenarios like e-commerce, streaming, or real-time analytics, where responsiveness and scalability are crucial. Additionally, compute serverless platforms support multiple programming languages and integrate seamlessly with other cloud services like storage, databases, APIs, and DevOps tools, expanding their appeal to developers and IT teams alike.The IT & telecom sector represents the largest end-user segment in the global serverless computing market due to its high digital maturity, continuous demand for innovation, and the need to manage massive volumes of data and dynamic user traffic. These industries have long been at the forefront of adopting cloud-native technologies to improve service delivery, optimize infrastructure costs, and enable rapid innovation cycles. Serverless computing, with its promise of scalability, cost-efficiency, and minimal infrastructure management, aligns perfectly with the operational needs and strategic

goals of IT and telecom companies. In the IT industry, organizations are increasingly leveraging serverless computing to support agile development practices, such as DevOps and CI/CD pipelines. These frameworks depend on the ability to deploy, scale, and update applications quickly and frequently capabilities that serverless architectures natively support. Functions-as-a-Service (FaaS) allows developers to run microservices and perform event-driven processing without maintaining servers, enabling IT firms to shorten development cycles, improve software quality, and react swiftly to market changes. For the telecom sector, serverless computing plays a vital role in managing backend operations, real-time data processing, network traffic monitoring, and mobile application functionality. With the rise of 5G, IoT, and edge computing, telecom providers are under pressure to deliver ultra-low-latency services and manage unpredictable spikes in usage.Function-as-a-Service (FaaS) is the largest server model type in the global serverless computing market primarily because it is the core model enabling true serverless architecture. FaaS allows developers to run individual pieces of code called functions in response to events without managing any underlying server infrastructure. This simplicity, efficiency, and flexibility make FaaS the preferred model for organizations aiming to accelerate innovation, optimize costs, and build scalable, event-driven applications. Leading platforms like

AWS Lambda, Azure Functions, and Google Cloud Functions have further popularized FaaS by offering robust ecosystems and seamless integrations with a wide range of services. The dominance of FaaS is largely due to its alignment with the modern application development paradigm, which emphasizes microservices, modularity, and rapid deployment. In a FaaS model, each function performs a specific task and can be independently deployed, triggered, and scaled based on demand. This granularity allows teams to build and update services faster, test individual components more efficiently, and respond to customer needs with greater agility. It is particularly effective in use cases such as data processing, real-time file conversion, webhooks, chatbots, backend services for mobile/web apps, and IoT workflows. Unlike traditional cloud models where users pay for allocated server capacity regardless of usage, FaaS operates on a pay-per-execution basis. This billing model is ideal for unpredictable workloads and intermittent tasks, as it significantly reduces costs for idle infrastructure. The automatic scaling and self-healing capabilities of FaaS platforms also reduce the need for manual intervention, freeing up IT resources and streamlining operations.Large enterprises are the largest adopters of serverless computing in the global market due to their expansive IT infrastructure, high-volume operations, and continuous need for digital innovation and cost optimization. These organizations o

ften handle complex workloads, maintain multiple customer-facing platforms, and require scalable backend solutions that can handle variable traffic and data-intensive operations. Serverless computing particularly in the Function-as-a-Service (FaaS) model provides these enterprises with the flexibility to build, deploy, and scale applications without managing physical servers or virtual machines, resulting in faster time-to-market and reduced operational overhead. With vast resources, they can experiment with and implement serverless architectures across various departments and business units. Serverless platforms help them decouple applications into microservices, enabling better performance, continuous delivery, and enhanced fault tolerance. This architectural shift is especially valuable for large corporations in finance, telecom, healthcare, and retail sectors, where digital transformation is critical to remaining competitive. Moreover, large enterprises benefit significantly from the cost model of serverless computing. In traditional cloud or on-premise environments, organizations pay for reserved infrastructure even when it's idle. In contrast, serverless platforms charge based on actual usage, which can result in considerable savings at scale. Additionally, serverless services eliminate the need for infrastructure provisioning, patching, and scaling, allowing enterprise IT teams to focus more on strategic innovation and less on maintenance.The public cloud deployment mo

del holds the largest share in the global serverless computing market due to its unmatched scalability, accessibility, cost-effectiveness, and extensive support from leading cloud service providers. In a serverless environment, the public cloud serves as the most efficient infrastructure platform where users can run code without provisioning or managing servers. Cloud giants such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) offer powerful serverless services like AWS Lambda, Azure Functions, and Google Cloud Functions exclusively through public cloud infrastructures, making this model the go-to option for businesses of all sizes and across industries. Enterprises can deploy applications quickly and globally without needing to invest in physical hardware or data centers. Public cloud platforms handle all aspects of infrastructure management, including auto-scaling, patching, and availability, allowing developers to focus solely on writing and deploying code. This reduces both the time-to-market and total cost of ownership, which is particularly beneficial for startups and SMEs, while still being valuable for large enterprises managing high-scale workloads. Moreover, the public cloud supports a broad array of integrations and development tools, enabling seamless workflows in modern DevOps and agile environments. It allows for greater interoperability across services such as storage, databases, analytics, and AI/ML tools all of which are essenti

al for building robust serverless applications. Public cloud providers also ensure continuous innovation and updates, offering features such as event triggers, container-based function execution, observability tools, and multi-language support, all of which enhance the serverless development experience.