Cloud Replication Tail Proxy for Block-Level Data Resilience
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Solution Overview
Problem
Current block-level data replication to public clouds is costly and inefficient due to high usage pricing models and the need for frequent data re-transmission, which increases costs and recovery time.
Innovation Solution
Deploying a replication tail proxy in the destination cloud to locally track and persist data blocks, reducing re-transmission costs and improving recovery time by enabling faster VM deployment for disaster recovery and failover, while minimizing overlapping writes and leveraging concurrent data streaming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is replicated to public cloud using traditional methods, then data backup is achieved, but operating costs increase due to high usage pricing models and frequent re-transmission
Solution Approach 1:
The system performs preliminary actions by establishing a persistent presence in the destination cloud through a replication tail proxy and pre-configuring local storage infrastructure. This allows the system to prepare storage space and tracking mechanisms in advance, eliminating the need for costly re-transmission operations and reducing cloud ingress/egress charges during actual recovery operations.
Solution Approach 2:
A replication tail proxy is deployed as an intermediary component in the destination cloud environment. This proxy maintains local tracking of replicated data and persists data blocks locally before they are fully processed, serving as a mediator between the source system and cloud storage. This intermediary approach reduces redundant data transfers and lowers operating costs by minimizing cloud egress charges.
2Reliability
If traditional cloud replication methods are used, then data redundancy is achieved, but recovery time increases due to frequent re-transmission requirements
Solution Approach 1:
The system performs preliminary actions by pre-establishing a replication tail proxy in the destination cloud that maintains local storage and tracking capabilities. This preliminary presence allows for rapid data retrieval and processing during recovery operations, eliminating the time-consuming re-transmission steps required by traditional methods and enabling faster VM deployment for disaster recovery.
3Reliability
If data blocks are persisted locally at destination cloud, then resiliency is improved, but device complexity increases due to replication tail proxy deployment
Solution Approach 1:
A replication tail proxy is deployed as an intermediary component in the destination cloud environment. This proxy maintains local tracking of replicated data and persists data blocks locally before they are fully processed, serving as a mediator between the source system and cloud storage. This intermediary approach reduces redundant data transfers and lowers operating costs by minimizing cloud egress charges.
Data Source
AI summary
Systems and methods disclosed herein improve on current technology for block-level data replication to cloud computing environments. A new system architecture deploys one or more replication tail proxies in a cloud computing environment, locally (at the cloud) tracks replicated data and determines which replicated data meet criteria for reconstructing a desired point-in-time in the cloud, and persists data blocks received at the replication tail proxy until they are processed as recovery points. The disclosed approach presents resiliency and performance advantages. First, the resiliency of block-level data replication to cloud is improved by deploying the replication tail proxy in the destination cloud. Second, a Recovery Time Objective (RTO) is reduced by enabling faster cloud deployment of virtual machines for disaster recovery, failover, and/or test purposes based on the replicated data.