article · Discover Applied Sciences
Blockchain-as-a-Service allows users to deploy blockchain applications on cloud infrastructure, with providers managing the underlying resources according to service level agreements. Traditional resource management often fails to handle fluctuating performance demands economically. To resolve this, an adaptive framework was designed for Hyperledger Fabric deployments on cloud platforms. It combines automated performance tracking using Hyperledger Caliper, service level violation detection using smart contracts, and virtual machine scaling via OpenStack. A multi-objective scheduling approach selects resource adjustments based on performance improvements relative to cost. Testing on the Nectar Research Cloud showed that the framework reliably achieved targeted performance increases of 50 percent, 100 percent, and 200 percent over baseline levels. Specifically, pairing virtual machine scaling with block size adjustments provided the most balanced configuration for performance and cost efficiency.
Running enterprise blockchain systems in the cloud can be expensive and technically difficult to balance during varying demand. This framework enables cloud providers to automatically adjust computing resources and blockchain settings to meet agreed customer performance targets. By keeping resource use economical, it helps make cloud-hosted blockchain networks more reliable and cost-effective to operate.
This work is directly relevant to cloud computing companies and enterprise blockchain service providers seeking to deliver automated, reliable Blockchain-as-a-Service platforms. The technology has been applied and tested in a cloud environment using Hyperledger Fabric 2.5 and OpenStack APIs. However, because continuous online scheduling under dynamically changing workloads is not yet implemented, the system is in an advanced prototype stage rather than fully near-market ready.
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Integrating blockchain technology with cloud computing has enabled Blockchain as a Service (BaaS), a cloud-based paradigm that allows users to design, deploy, and manage customized blockchain applications, including smart contracts and domain-specific business functionalities. BaaS providers manage infrastructure provisioning, maintenance, and scalability while ensuring quality of service (QoS) compliance through service level agreements (SLAs). However, existing resource management approaches often struggle to satisfy dynamic performance requirements in a cost-efficient manner without increasing operational overhead or reducing provider efficiency. This paper presents a structured Adaptive SLA-based assistance framework for deploying Hyperledger Fabric on cloud platforms. The framework integrates automated performance monitoring using Hyperledger Caliper, SLA violation detection through programmed SLA chaincode, and automated VM scaling via the OpenStack4J API within a 3E (effective–efficient–economical) verification methodology. A greedy multi-objective scheduling mechanism guides parameter optimization by selecting scaling actions according to marginal performance gain per unit cost. Experiments were conducted on the Nectar Research Cloud using Hyperledger Fabric 2.5 to evaluate the impact of VM size, block size, peer count, and storage configuration on throughput (TPS) and average latency. Results demonstrate that the framework consistently achieves performance targets of 50%, 100%, and 200% above the baseline configuration through adaptive resource reconfiguration. Among evaluated strategies, Comb2, which combines dual block size adjustment with VM scaling, emerged as the optimal balanced configuration in terms of performance and cost efficiency. While automated monitoring, SLA enforcement, and VM scaling are fully implemented, continuous online scheduling under dynamically changing workloads remains future work. The proposed framework establishes a practical foundation for SLA-driven blockchain optimization in cloud environments and supports future extensibility to additional BaaS platforms.
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DOI: 10.1007/s42452-026-09310-9
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