Distributed Consistency Group Splitter for VM IO Latency
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Solution Overview
Problem
The interception of Input/Outputs (IOs) by a splitter in virtual machine (VM) environments introduces latency and reduces throughput, as IOs are not written to disk until an acknowledgement is received from the Data Protection Appliance (DPA), limiting the performance of high-demand VM applications.
Innovation Solution
Implementing a distributed consistency group (CG) with multiple DPAs, where IOs are distributed by a splitter across multiple grid-CGs, allowing each grid-CG to operate independently and reducing latency by eliminating the need for a single DPA acknowledgement, thereby increasing throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single DPA is used to intercept and process IOs, then data protection consistency is maintained, but latency increases and throughput decreases
Solution Approach 1:
The patent divides a single consistency group into multiple sub-consistency groups (sub-CGs), each handled by a separate DPA. This segmentation allows parallel processing of IOs across multiple DPAs, reducing the latency bottleneck of a single DPA while maintaining overall data protection consistency through coordinated bookmarking across all sub-CGs.
2Device complexity
If a single DPA processes all IOs, then system complexity is low, but throughput is limited
Solution Approach 1:
The consistency group is segmented into multiple sub-CGs distributed across multiple DPAs, enabling parallel IO processing that increases throughput. The splitter distributes IOs to appropriate sub-CGs, and coordinated bookmarking maintains consistency, achieving high throughput with managed complexity.
Solution Approach 2:
The patent introduces a new dimension of distribution by organizing DPAs into a grid structure with multiple rows and columns, where each DPA handles specific sub-CGs. This dimensional organization allows scalable throughput improvement while maintaining manageable system complexity through structured distribution.
3Reliability
If IOs are written to disk only after DPA acknowledgement, then data protection is ensured, but performance of high-demand VM applications is limited
Solution Approach 1:
By segmenting the consistency group into multiple sub-CGs handled by different DPAs, the system can process and acknowledge IOs in parallel across multiple DPAs. This reduces the total time for IO completion while maintaining data protection, thereby improving VM application performance without sacrificing reliability.
Data Source
AI summary
One example method includes intercepting an IO that is directed to a volume, writing the IO to a grid-CG that is one of a plurality of grid-CGs that collectively form a distributed CG, adding the IO to a stream journal associated with the grid-CG, receiving a bookmark request, in response to the bookmark request, inserting a bookmark in the stream journal, incrementing a splitter counter and broadcasting a splitter counter value to the grid-CGs in the distributed CG, and inserting the bookmark in respective stream journals of the grid-CGs in the distributed CG.


