On-demand Cross Data Center Replication Service
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Solution Overview
Problem
Multi-cloud enterprise software applications face challenges in enabling collaboration between customers onboarded at different data centers due to inadequate data replication across multiple centers, which is costly and provides inadequate performance.
Innovation Solution
A replication service is configured to federate data across multiple data centers on an on-demand basis, responding to trigger events such as customer creation, updates, or data sharing by replicating relevant data, while applying settings to control replication to specific data centers based on legal and security permissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is replicated across multiple data centers to enable collaboration, then customer collaboration capability is improved, but replication cost increases
Solution Approach 1:
The system applies selective data replication where only specific data associated with triggered events is replicated to specific data centers where customers are onboarded. This targeted approach ensures collaboration capability is enabled locally where needed while avoiding unnecessary replication costs across all data centers.
Solution Approach 2:
The system dynamically determines data replication based on triggered events such as customer creation, updates, or deletions. The replication behavior changes dynamically based on event type and the onboarding status of customers at different data centers, optimizing the balance between collaboration capability and replication cost.
2Adaptability or versatility
If data is replicated across multiple data centers to enable collaboration, then collaboration between customers is improved, but data replication performance becomes inadequate
Solution Approach 1:
The system uses event-triggered periodic replication where data is replicated at specific intervals based on triggered events rather than continuously. This approach improves replication performance by eliminating unnecessary replication operations while ensuring data is replicated timely when collaboration is actually needed.
3Loss of energy
If selective data replication is applied based on trigger events, then replication cost is optimized, but system complexity increases
Solution Approach 1:
The system pre-establishes the relationship between trigger events and data replication rules during system setup. This preliminary configuration simplifies the runtime operation by eliminating the need for complex real-time decision logic, reducing system complexity while maintaining cost optimization benefits.
4Productivity
If data is replicated only when triggered events occur, then replication performance is improved, but data availability may be delayed
Solution Approach 1:
The system monitors triggered events and uses this feedback to determine when data replication should occur. This feedback mechanism ensures data is replicated reliably when collaboration is needed while maintaining high replication performance by avoiding unnecessary replication operations. The event-triggered feedback loop balances performance and reliability effectively.
Data Source
AI summary
A method may include detecting one or more trigger events at a first data center hosting a software application having a first customer onboarded at the first data center but not a second data center also hosting the software application. In response to the trigger events, a first data associated with the first customer may be replicated at the second data center to enable a collaboration between the first customer and a second customer of the software application onboarded at the second data center but not the first data center. One or more data replication relevant settings may be applied to prevent a second data associated with the first customer from being replicated at the second data center. Furthermore, the data replication relevant settings may be applied to prevent the first data from being replicated at a third data center. Related systems and computer program products are also provided.