An SLA defines the services delivered by a provider to a client and the metrics for measuring those services. If the actual services received by the client do not meet the SLA guarantees promised by the provider, the agreement has been violated. In that case, the provider may owe the client a refund or whatever penalty is defined in the SLA.
The solution brief includes a high-level overview of a proposed solution for self-assessing SLAs. This proposed solution uses Hyperledger Fabric blockchain technology to tackle the gray areas of conventional SLA assessment.
This unique architecture provides a trusted and privacy-preserving network that can precisely monitor and compute SLA metrics, with full transparency for both provider and client.
Achieving effective SLA self-assessments will benefit everyone in the ecosystem by building trust, removing friction, streamlining processes, and saving costs.
The Problem: Lack of transparency
An effective SLA clearly defines all performance metrics and parameters.
But in most conventional SLAs, the provider assesses their own performance using their own tools and frameworks. The client generally has no way to see how these metrics are monitored or calculated. This increases the risk of biased results that favor the provider.
This lack of transparency means the client could well suffer from misunderstandings, missed violations, and insufficient refunds. All this undermines trust between the provider and the client.
The Solution: Using blockchain for transparent self-assessment
This solution brief proposes a novel architecture that is based on the Hyperledger Fabric blockchain framework and Hyperledger Fabric Private Chaincode (FPC). As shown in the figure below, the installed Trusted Execution Environment (TEE) provides secure and private monitoring, and computation of all performance metrics governed by the SLA.
Both client and provider benefit from the presented solution, which builds trust where little previously existed. More details are provided in the full white paper.
The scientific research performed on SLA Self-Assessment and applied to the telecom context adheres to work accomplished under the Pledger project.
The full paper is available to download here.
Get Involved with the Group
To learn more about the Hyperledger Telecom Special Interest Group, check out the group’s wiki and mailing list. If you have questions, comments or suggestions, feel free to post messages to the list. And you’re welcome to join any of the group’s upcoming calls to meet group members and learn how to get involved. On February 9 at 9:00 am PT, the authors will be presenting the paper during the Telecom Special Interest Group call. All are welcome to join.
The Hyperledger Telecom Special Interest Group would like to thank the following people who contributed to this solution brief: Nima Afraz, David Boswell, Gordon Graham, Nikolaos Kapsoulis, Antonios Litke, Alexandros Psychas, Vipin Rathi, and Theodora Varvarigou.