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Journal of Parallel and Distributed Computing

Comprehensive overview of quantum serverless: Elastic integration of quantum and classical computing

Dimitar Mileski, Marjan Gušev, Sasko Ristov

Published Jun 22, 2026• 0 citations
Publisher

Abstract

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.

DOI
10.1016/j.jpdc.2026.105303

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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.
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Starting from the idea of Quantum Computing which is a concept that dates back to 80s, we come to the present day where we can perform calculations on real quantum computers. This sudden development of technology opens up new scenarios that quickly lead to the desire and the real possibility of integrating this technology into current software architectures. The usage of frameworks that allow computation to be performed directly on quantum hardware poses a series of challenges. This document describes a an architectural framework that addresses the problems of integrating an API exposed Quantum provider in an existing Enterprise architecture and it provides a minimum viable product (MVP) solution that really merges classical quantum computers on a basic scenario with reusable code on GitHub repository. The solution leverages a web-based frontend where user can build and select applications/use cases and simply execute it without any further complication. Every triggered run leverages on multiple backend options, that include a scheduler managing the queuing mechanism to correctly schedule jobs and final results retrieval. The proposed solution uses the up-to-date cloud native technologies (e.g. Cloud Functions, Containers, Microservices) and serves as a general framework to develop multiple applications on the same infrastructure.
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The evolution of cloud computing towards multi-cloud architectures has provided significant advantages in flexibility and resilience. Concurrently, quantum computing has emerged as a new computational paradigm with the potential to solve problems intractable for classical systems. However, access to quantum resources is currently fragmented across siloed, provider-specific cloud platforms, negating the benefits of a multi-cloud strategy. This paper addresses this gap by proposing a comprehensive framework for integrating heterogeneous quantum computing resources into a unified multi-cloud architecture. The Method involves a four-layer architectural model comprising: (1) an intelligent orchestration and workload management layer with policy-driven resource selection, (2) a universal quantum gateway for interoperability featuring advanced circuit transpilation, (3) a zero-trust secure communication fabric utilizing post-quantum cryptography and quantum key distribution, and (4) the underlying heterogeneous compute infrastructure of classical and quantum processors. The anticipated Results of implementing this framework include significant, quantifiable enhancements in computational efficiency for complex optimization and simulation problems in fields like drug discovery and materials science, and a strengthened, future-proof security posture resistant to both classical and quantum threats. The Discussion interprets these results, outlining the profound economic and scientific implications. It also provides a deep analysis of the significant challenges to implementation—including quantum hardware immaturity, quantum-classical latency, and interoperability hurdles—and proposes a detailed, phased roadmap for future research. In Conclusion, this work establishes a foundational blueprint for a synergistic quantum-classical ecosystem, paving the way for a new generation of advanced, secure, and powerful cloud environments.
The integration of quantum computing technologies with established classical infrastructure represents a transformative advancement in computational capabilities. This manuscript addresses architectural frameworks enabling seamless orchestration between quantum and classical environments through container-based methodologies. Kubernetes extensions provide standardized interfaces for managing hybrid workloads while ensuring reproducibility across experimental iterations. Custom resource definitions facilitate quantum job specifications with appropriate hardware requirements, while specialized operators handle complex scheduling demands inherent to quantum processing. Implementation architectures demonstrate enhanced resource utilization through dynamic allocation mechanisms that accommodate both paradigms simultaneously. Practical evaluations reveal substantial improvements in workflow automation when orchestration platforms coordinate quantum simulators alongside cloud-based quantum processing units. The extensibility of container-based solutions proves particularly valuable for enterprises navigating evolving quantum hardware landscapes. The technological foundation described establishes a robust framework for quantum-classical integration while addressing security and deployment considerations. Findings indicate strategic advantages in adopting containerized approaches for quantum workflow management, particularly regarding experimental reproducibility and resource optimization across heterogeneous computing environments.