Offloading Service Mesh to DPU for Micro-service Governance
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Solution Overview
Problem
In micro-services architectures, the current Service Mesh deployment mode leads to resource competition between sidecars and micro-service applications, affecting service performance and increasing deployment costs, as sidecars share resources like CPU, OS, and memory with service processes.
Innovation Solution
The proposed solution involves offloading the Service Mesh to a Data Processing Unit (DPU) to perform micro-service processing operations, achieving physical isolation and utilizing a combination of programmable hardware and software units to execute micro-service governance logic, thereby reducing resource competition and improving service performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Service Mesh is deployed using sidecars in each micro-service application, then micro-service governance logic can be implemented, but resource competition occurs between sidecars and service processes affecting performance and increasing deployment cost
Solution Approach 1:
The system is segmented into two independent parts: micro-service applications running on computing nodes and Service Mesh running on separate DPU devices. This physical separation eliminates resource competition while maintaining governance functionality through network communication between the components.
Solution Approach 2:
The Service Mesh governance logic is extracted from the micro-service applications and deployed independently on DPU devices. This extraction removes the harmful resource competition while preserving the essential governance capabilities through dedicated hardware resources.
2Reliability
If sidecars are deployed with each micro-service application to implement governance logic, then service governance functions are achieved, but deployment cost increases
Solution Approach 1:
Multiple micro-service governance functions are merged into a single Service Mesh deployment on the DPU device. Instead of each application having its own sidecar, the governance capability is consolidated and shared across all micro-services through the unified Service Mesh implementation.
Solution Approach 2:
The Service Mesh deployed on the DPU provides universal governance functionality that serves all micro-service applications. This multi-functional approach eliminates the need for separate sidecars for each application, reducing deployment complexity while maintaining comprehensive governance coverage.
3Use of energy by moving object
If sidecars share resources with micro-service applications, then resource utilization is shared, but resource competition affects service performance
Solution Approach 1:
Network communication acts as an intermediary between the micro-service applications and the Service Mesh on the DPU. This intermediary enables resource sharing through information exchange while preventing direct resource competition, as the two systems operate on separate hardware platforms.
Data Source
AI summary
An information processing method, a computer device, and a storage medium are provided. The method includes: acquiring communication information to be processed; extracting a key information character of the communication information to be processed by using a programmable hardware unit of a data processor; and according to the key information character, determining whether there is matching target processing operation information in a generated character mapping table, a character mapping table is generated by the programmable software unit of the data processor according to historical key information characters of historical communication information and their corresponding historical processing operation information, and the target processing operation information includes at least one micro-service processing operation; if yes, executing the micro-service processing operation included in the target processing operation information for the communication information to be processed.


