The Global Function as a Service Market size is expected to reach $72.52 billion by 2031, rising at a market growth of 25.6% CAGR during the forecast period.
The adoption of telemedicine, electronic health records (EHRs), AI-based diagnostics, and real-time patient monitoring has accelerated the shift toward serverless computing in healthcare. FaaS solutions are helping healthcare providers, pharmaceutical companies, and research institutions manage large-scale data analytics, machine learning models for disease prediction, and HIPAA-compliant cloud storage. Additionally, the healthcare & life sciences segment witnessed 12% revenue share in the market in 2023. Furthermore, the incorporation of the IoT within the healthcare sector for remote patient monitoring has significantly heightened the demand for serverless architectures, which facilitate the efficient processing and analysis of real-time health data.
The rise of edge AI and IoT-driven applications has further accelerated the adoption of serverless AI. As more connected devices and sensors generate vast amounts of real-time data, FaaS enables organizations to process AI-driven insights at the edge, reducing latency and improving response times. This benefits industries like healthcare, manufacturing, and autonomous vehicles, where real-time data processing is critical for decision-making. Furthermore, the cost-efficiency of serverless computing is a major driver of its widespread adoption. Since FaaS follows a pay-as-you-go pricing model, businesses only pay for the execution time of functions rather than maintaining costly idle server instances. This makes it particularly appealing to startups, enterprises, and organizations looking to optimize IT budgets. Cloud providers such as AWS Lambda, Azure Functions, and Google Cloud Functions offer robust FaaS solutions that seamlessly integrate with existing cloud ecosystems, making it easier for businesses to adopt serverless computing. Hence, these factors will aid in the expansion of the market.
However, the distributed and event-driven nature of serverless functions can further contribute to performance inefficiencies. Since FaaS often relies on multiple services communicating over a network, network latency, dependency resolution, and data transfer times can collectively impact overall execution speed. Developers need to carefully design and optimize function execution workflows to minimize delays, such as using warm functions, caching strategies, and keeping function sizes lightweight. However, these optimizations require additional development efforts and expertise, making adoption more challenging for enterprises seeking seamless scalability without compromising speed. Hence, these limitations may impede the expansion of the market.
The adoption of telemedicine, electronic health records (EHRs), AI-based diagnostics, and real-time patient monitoring has accelerated the shift toward serverless computing in healthcare. FaaS solutions are helping healthcare providers, pharmaceutical companies, and research institutions manage large-scale data analytics, machine learning models for disease prediction, and HIPAA-compliant cloud storage. Additionally, the healthcare & life sciences segment witnessed 12% revenue share in the market in 2023. Furthermore, the incorporation of the IoT within the healthcare sector for remote patient monitoring has significantly heightened the demand for serverless architectures, which facilitate the efficient processing and analysis of real-time health data.
The rise of edge AI and IoT-driven applications has further accelerated the adoption of serverless AI. As more connected devices and sensors generate vast amounts of real-time data, FaaS enables organizations to process AI-driven insights at the edge, reducing latency and improving response times. This benefits industries like healthcare, manufacturing, and autonomous vehicles, where real-time data processing is critical for decision-making. Furthermore, the cost-efficiency of serverless computing is a major driver of its widespread adoption. Since FaaS follows a pay-as-you-go pricing model, businesses only pay for the execution time of functions rather than maintaining costly idle server instances. This makes it particularly appealing to startups, enterprises, and organizations looking to optimize IT budgets. Cloud providers such as AWS Lambda, Azure Functions, and Google Cloud Functions offer robust FaaS solutions that seamlessly integrate with existing cloud ecosystems, making it easier for businesses to adopt serverless computing. Hence, these factors will aid in the expansion of the market.
However, the distributed and event-driven nature of serverless functions can further contribute to performance inefficiencies. Since FaaS often relies on multiple services communicating over a network, network latency, dependency resolution, and data transfer times can collectively impact overall execution speed. Developers need to carefully design and optimize function execution workflows to minimize delays, such as using warm functions, caching strategies, and keeping function sizes lightweight. However, these optimizations require additional development efforts and expertise, making adoption more challenging for enterprises seeking seamless scalability without compromising speed. Hence, these limitations may impede the expansion of the market.
Driving and Restraining Factors
Drivers
- Rising Adoption of Serverless Computing
- Expansion of IoT and Edge Computing
- Growth of AI and Machine Learning Applications
Restraints
- Substantial Latency and Performance Issues
- High Execution Costs for Long-running Workloads
Opportunities
- Growing Popularity of Event-Driven Architectures
- Increasing Deployment of Microservices-Based Applications
Challenges
- Security and Compliance Concerns
- Lack of Standardization Across Different Cloud Providers
Type Outlook
Based on type, the market is bifurcated into developer-centric and operator-centric. The operator-centric FaaS segment procured 37% revenue share in the market in 2023. Organizations adopting hybrid and multi-cloud strategies require solutions that provide greater control over function execution, monitoring, and security compliance, making operator-centric FaaS an essential component of their cloud architecture. The growing complexity of IT operations, the demand for better resource utilization, and enhanced security and compliance are key drivers in this segment. Enterprises looking for improved fault tolerance, performance monitoring, and cost optimization integrate operator-centric FaaS solutions into their cloud ecosystems, leveraging technologies like OpenFaaS, Knative, and Apache OpenWhisk.Deployment Outlook
On the basis of deployment, the market is classified into public cloud, private cloud, and hybrid cloud. The private cloud segment recorded 31% revenue share in the market in 2023. Industries such as banking, healthcare, government, and defense prefer private cloud FaaS solutions as they offer greater control over data security, access management, and compliance with regulatory frameworks like GDPR, HIPAA, and PCI DSS. Organizations that manage sensitive consumer information or proprietary data frequently choose on-premise or private cloud FaaS implementations. This approach facilitates enhanced performance, reduced latency, and effective risk mitigation.Enterprise Size Outlook
By enterprise size, the market is divided into large enterprises and small & medium-sized enterprises. The large enterprises segment witnessed 54% revenue share in the market in 2023. Large organizations across industries such as BFSI, healthcare, retail, telecom, and manufacturing leverage FaaS to enhance operational efficiency, streamline application development, and manage fluctuating workloads efficiently. With the growing demand for AI, big data analytics, IoT, and automation, enterprises increasingly adopt serverless computing to optimize cloud resource utilization while reducing infrastructure management complexities. Additionally, multi-cloud and hybrid cloud strategies have driven enterprise adoption of FaaS, enabling businesses to build scalable, event-driven applications while maintaining security and compliance standards.
End-use Outlook
Based on end-use, the market is segmented into IT & telecom, BFSI, retail & consumer goods, healthcare & life sciences, government & defense, transportation & logistics, manufacturing, and others. The BFSI segment procured 20% revenue share in the market in 2023. The industry's growing reliance on cloud-based financial services, digital banking, and real-time transaction processing drives the segment. With the rapid adoption of AI-powered fraud detection, risk management, and automated trading systems, financial institutions increasingly leverage serverless architectures to efficiently handle high-volume data processing and customer interactions. Additionally, the rising demand for secure, scalable, and cost-effective cloud solutions in BFSI has fueled the adoption of FaaS for payment gateways, fraud analytics, and regulatory compliance monitoring.Regional Outlook
Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment garnered 37% revenue share in the market in 2023. The growing use of serverless computing by businesses, especially in the BFSI, IT & telecom, healthcare, and e-commerce sectors, is responsible for the region's supremacy. Additionally, the rise of DevOps, microservices architecture, and edge computing has fueled FaaS adoption across various industries. Moreover, the shift towards hybrid and multi-cloud strategies and government initiatives supporting cloud computing has further strengthened the demand for FaaS solutions. The expanding startup ecosystem and increasing venture capital investments in cloud-based innovations have also played a crucial role in market growth.Recent Strategies Deployed in the Market
- Jan-2025: Google LLC and ServiceNow expanded their partnership to integrate AI-powered workflows, CRM, and ITSM solutions with Google Cloud Marketplace and Distributed Cloud. The collaboration enhances enterprise automation, data integration with BigQuery, and AI-driven decision-making, benefiting businesses across various industries.
- Nov-2024: Google LLC and NTT DATA expand its partnership to accelerate AI and data analytics adoption in APAC. A dedicated business unit will drive cloud solutions, industry-specific innovations, and workforce upskilling, aiming for a 10x cloud business growth in three years.
- Sep-2024: Amazon Web Services, Inc. and Oracle came into partnership to announced Oracle Database@AWS, enabling access to Oracle Autonomous Database and Oracle Exadata Database Service on AWS. This partnership simplifies cloud migration, enhances security, and provides seamless integration with AWS services, benefiting enterprises across industries with improved scalability and performance.
- Jun-2024: IBM Corporation and Telefónica Tech came into collaboration to develop AI, analytics, and data management solutions, launching SHARK.X, a hybrid multi-cloud platform. They will create a use case office, offer training, and accelerate digital transformation for businesses and public administration.
- May-2024: IBM Corporation and Salesforce expanded their partnership to enhance AI and data capabilities by integrating Watsonx AI with Einstein 1. The collaboration enables bidirectional data integration, flexible LLMs, and AI-driven automation, improving customer workflows and supporting responsible AI development.
List of Key Companies Profiled
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Google LLC (Alphabet Inc.)
- Oracle Corporation
- IBM Corporation
- Microsoft Corporation
- SAP SE
- Dynatrace, Inc.
- Infosys Limited
- Alibaba Cloud (Alibaba Group Holding Limited)
- Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
Market Report Segmentation
By Type
- Developer-Centric
- Operator-Centric
By Enterprise Size
- Large Enterprises
- Small & Medium-sized Enterprises
By Deployment
- Public Cloud
- Private Cloud
- Hybrid Cloud
By End-use
- BFSI
- IT & Telecom
- Retail & Consumer Goods
- Healthcare & Life Sciences
- Manufacturing
- Government & Defense
- Transportation & Logistics
- Other End-use
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. Global Function as a Service Market by Type
Chapter 6. Global Function as a Service Market by Enterprise Size
Chapter 7. Global Function as a Service Market by Deployment
Chapter 8. Global Function as a Service Market by End-use
Chapter 9. Global Function as a Service Market by Region
Chapter 10. Company Profiles
Companies Mentioned
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Google LLC (Alphabet Inc.)
- Oracle Corporation
- IBM Corporation
- Microsoft Corporation
- SAP SE
- Dynatrace, Inc.
- Infosys Limited
- Alibaba Cloud (Alibaba Group Holding Limited)
- Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
Methodology
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