Quantum computing is rapidly reaching a point in which its application design and engineering aspects have to be seriously considered. However, quantum software engineering is still in its infancy with numerous challenges, especially in dealing with the diversity of quantum programming languages and noisy intermediate-scale quantum systems. To alleviate these challenges, we propose QFaaS, a novel Quantum Function-as-a-Service framework, which leverages the advantages of the serverless model and state-of-the-art techniques to advance practical quantum computing in the NISQ era. Our framework provides essential elements of a serverless quantum system to streamline service-oriented quantum application development in cloud environments, such as combining hybrid quantum-classical computation, automating the backend selection, and adapting quantum DevOps techniques. QFaaS offers the first full-stack and unified quantum serverless platform by integrating multiple well-known quantum software development kits (Qiskit, Q#, Cirq, and Braket), quantum simulators, and cloud providers (IBM Quantum and Amazon Braket). This paper proposes the concept of quantum functions, software life cycle, system design, operation workflows, and implementation of QFaaS. We also present two practical use cases and performance evaluations on today’s quantum computers and simulators to demonstrate our framework’s capability to ease the burden on traditional engineers to expedite the ongoing quantum software transition.
Quantum computing is rapidly reaching a point in which its application design and engineering aspects have to be seriously considered. However, quantum software engineering is still in its infancy with numerous challenges, especially in dealing with the diversity of quantum programming languages and noisy intermediate-scale quantum systems. To alleviate these challenges, we propose QFaaS, a novel Quantum Function-as-a-Service framework, which leverages the advantages of the serverless model and state-of-the-art techniques to advance practical quantum computing in the NISQ era. Our framework provides essential elements of a serverless quantum system to streamline service-oriented quantum application development in cloud environments, such as combining hybrid quantum-classical computation, automating the backend selection, and adapting quantum DevOps techniques. QFaaS offers the first full-stack and unified quantum serverless platform by integrating multiple well-known quantum software development kits (Qiskit, Q#, Cirq, and Braket), quantum simulators, and cloud providers (IBM Quantum and Amazon Braket). This paper proposes the concept of quantum functions, software life cycle, system design, operation workflows, and implementation of QFaaS. We also present two practical use cases and performance evaluations on today’s quantum computers and simulators to demonstrate our framework’s capability to ease the burden on traditional engineers to expedite the ongoing quantum software transition.
Quantum systems have started to emerge as a disruptive technology and enabling platforms - exploiting the principles of quantum mechanics - to achieve quantum supremacy in computing. Academic research, industrial projects (e.g., Amazon Braket), and consortiums like 'Quantum Flagship' are striving to develop practically capable and commercially viable quantum computing (QC) systems and technologies. Quantum Computing as a Service (QCaaS) is viewed as a solution attuned to the philosophy of service-orientation that can offer QC resources and platforms, as utility computing, to individuals and organisations who do not own quantum computers. To understand the quantum service development life cycle and pinpoint emerging trends, we used evidence-based software engineering approach to conduct a systematic mapping study (SMS) of research that enables or enhances QCaaS. The SMS process retrieved a total of 55 studies, and based on their qualitative assessment we selected 9 of them to investigate (i) the functional aspects, design models, patterns, programming languages, deployment platforms, and (ii) trends of emerging research on QCaaS. The results indicate three modelling notations and a catalogue of five design patterns to architect QCaaS, whereas Python (native code or frameworks) and Amazon Braket are the predominant solutions to implement and deploy QCaaS solutions. From the quantum software engineering (QSE) perspective, this SMS provides empirically grounded findings that could help derive processes, patterns, and reference architectures to engineer software services for QC.
Quantum systems have started to emerge as a disruptive technology and enabling platforms - exploiting the principles of quantum mechanics via programmable quantum bits (QuBits) - to achieve quantum supremacy in computing. Academic research, industrial projects (e.g., Amazon Braket, IBM Qiskit), and consortiums like 'Quantum Flagship' are striving to develop practically capable and commercially viable quantum computing (QC) systems and technologies. Quantum Computing as a Service (QCaaS) is viewed as a solution attuned to the philosophy of service-orientation that can offer QC resources and platforms, as utility computing, to individuals and organisations who do not own quantum computers. This research investigates a process-centric and architecture-driven approach to offer a software engineering perspective on enabling QCaaS - a.k.a quantum service-orientation. We employed a two-phase research method comprising (a) a systematic mapping study and (b) an architecture-based development, first to identify the phases of the quantum service development life cycle and subsequently to integrate these phases into a reference architecture that supports QCaaS. The SMS process retrieved a collection of potentially relevant research literature and based on a multi-step selection and qualitative assessment, we selected 41 peer-reviewed studies to answer three RQs. The RQs investigate (i) demographic details in terms of frequency, types, and trends of research, (ii) phases of quantum service development lifecycle to derive a reference architecture for conception, modeling, assembly, and deployment of services, and (iii) The results identify a 4-phased development lifecycle along with quantum significant requirements (QSRs), various modeling notations, catalogue of patterns, programming languages, and deployment platforms that can be integrated in a layered reference architecture to engineer QCaaS.
Quantum computing is increasingly accessed through cloud-based hybrid environments, but practical adoption depends on more than exposing remote quantum backends. It also requires managed abstractions for orchestrating classical and quantum stages, handling queues, binding backends, and integrating surrounding workflow logic. This paper presents a comprehensive survey of Quantum Serverless from that perspective. Our contribution is twofold: (1) we consolidate the key architectural components of Quantum Serverless into a unified reference architecture; and (2) we evaluate current industry and research offerings through a KPI-driven framework covering ecosystem coverage, service operability, queue handling, pricing flexibility, near-real-time readiness, and production maturity. Using this framework, we analyze 18 quantum cloud platforms and show that the ecosystem is growing but remains unevenly mature. Queue-based execution is already a baseline capability, whereas stronger serverless characteristics, such as Function-as-a-Service, Containers-as-a-Service, near-real-time responsiveness, and production readiness, remain limited. Overall, current Quantum Serverless is best understood as a queue-driven hybrid orchestration model rather than a fully mature cloud-native serverless layer. The survey identifies the main maturity gaps and outlines directions for future development.
This paper introduces a vision for Quantum Software Development lifecycle, proposing a hybrid full-stack iterative model that integrates quantum and classical computing. Addressing the current challenges in Quantum Computing (QC) such as the need for integrating diverse programming languages and managing the complexities of quantum-classical systems, this model is rooted in the principles of DevOps and continuous software engineering. It presents a comprehensive lifecycle for quantum software development, encompassing quantum-agnostic coding, testing, deployment, cloud computing services, orchestration, translation, execution, and interpretation phases. Each phase is designed to accommodate the unique demands of QC, enabling traditional software developers to engage with QC environments without needing in-depth QC expertise. The paper presents a detailed implementation roadmap, utilizing a range of existing tools and frameworks, thereby making quantum software development more accessible and efficient. The proposed model not only addresses current challenges in quantum software development but also makes a substantial contribution to the field of Quantum Software Engineering (QSE). By proposing a structured and accessible model, it sets the stage for further advancements and research in QSE, enhancing its practicality and relevance in a wide range of applications.
As quantum computers mature, the complexity of quantum software increases. As we move from the initial standalone quantum algorithms toward complex solutions combining quantum algorithms with traditional software, new software engineering methods and abstractions are needed. Nowadays, quantum computers are usually offered in the cloud, under a pay-per-use model, leading to the adoption of the service-oriented good practices that dominate the cloud today. However, specific adaptations are needed to reap the benefits of service-oriented computing while dealing with quantum hardware limitations. In this article, we propose the Quantum API Gateway—an adaptation of the API Gateway pattern that takes into account the fact that quantum services cannot be deployed as traditional services. Instead, the Quantum API Gateway recommends the best quantum computer to run a specific quantum service at run time. As proof of concept, we provide an implementation of the Quantum API Gateway for the Amazon Braket platform.
While quantum computing technologies are evolving toward achieving full maturity, hybrid algorithms, such as variational quantum computing, are already emerging as valid candidates to solve practical problems in fields, such as chemistry and operations research. This situation calls for a tighter and better integration of classical and quantum computing infrastructures to improve efficiency and users’ quality of service. Inspired by recent developments in cloud technologies, serverless computing has recently been considered a promising solution for this purpose by both industry and research. In this work, we define a system model for a hybrid classical–quantum serverless system, with an associated open-source numerical simulator that can be driven by production traces and stochastic workload models. We therefore describe how we produced a public dataset using IBM Qiskit in a local and remote infrastructure, with a sample application on optimization. The simulation results show initial insights on some distinguishing features of the platform simulated, measured in terms of user and system metrics, for jobs with heterogeneous problem sizes and priorities. We also report a few lessons we learned from developing the application with IBM Qiskit serverless and running it on IBM Quantum backends