Selective Cloud Data Deletion via Private Server Sync
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Solution Overview
Problem
Public cloud storage becomes expensive when large amounts of data are stored, as users are typically unwilling to delete data, leading to compounding costs, and existing solutions do not efficiently manage data synchronization across public cloud and private server systems.
Innovation Solution
A method that synchronizes data objects between public cloud and private server data buckets using asynchronous notifications, where data is replicated from the cloud to the private server only if it is not already present, and allows selective deletion from the cloud bucket, with conflict resolution mechanisms to manage version dominance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in public cloud systems, then data accessibility and security are improved, but storage costs increase compounding over time
Solution Approach 1:
The system segments data storage across two locations: public cloud and private server. Hot data that needs frequent access remains in the cloud, while cold data that is rarely accessed is replicated to the private server. This segmentation allows the system to maintain data accessibility through cloud infrastructure while reducing compounding storage costs by eliminating redundant cloud storage for infrequently accessed data.
Solution Approach 2:
The system changes the accessibility parameter dynamically based on data access patterns. When data is first uploaded to the cloud, it is highly accessible. Over time, as access frequency decreases, the system automatically replicates the data to private server storage and subsequently deletes it from the cloud. This parameter change optimizes the balance between accessibility and storage cost.
2Reliability
If data is kept in public cloud for long term, then data security and accessibility are maintained, but storage expenses compound continuously
Solution Approach 1:
The system performs preliminary actions by proactively replicating data to private server storage before it becomes necessary to delete from the cloud. The asynchronous notification mechanism detects when data has been successfully stored in the private server, and only then triggers deletion from the cloud. This preliminary replication ensures data security is maintained through redundancy while preventing continuous expense compounding.
Solution Approach 2:
The system creates copies of data in two locations: public cloud and private server. The copying process is automated and asynchronous, triggered by cloud storage events. Once a copy exists in the private server, the original cloud copy can be safely deleted. This copying mechanism maintains data security through redundancy while eliminating the need to pay continuous storage expenses for the same data in both locations.
3Quantity of substance
If data synchronization is performed between cloud and private server, then storage cost is reduced, but system complexity increases
Solution Approach 1:
The system introduces an intermediary component that manages the synchronization between cloud and private server. This intermediary monitors cloud storage events, determines which data should be replicated based on access patterns and policies, initiates replication to the private server, and coordinates deletion from the cloud. By centralizing this logic in an intermediary, the system reduces overall complexity compared to having each component manage its own synchronization logic.
4Quantity of substance
If selective deletion from cloud bucket is implemented, then cloud storage fees are minimized, but data loss risk increases
Solution Approach 1:
The system applies beforehand cushioning by creating a safety buffer through data replication before deletion occurs. The asynchronous notification mechanism ensures that data is successfully replicated to the private server and stored in a policy database record before triggering deletion from the cloud. This cushioning mechanism prevents data loss risk while enabling selective deletion to minimize cloud storage fees.
Data Source
AI summary
Due to slow download speeds from a cloud server to an end-user and the high costs associated therewith, described is a private environment that manages and utilizes resources provided by a public cloud and the storage horsepower of a private server. Certain embodiments envision syncing data objects across at least one cloud data bucket located in a public cloud and at least one server data bucket located in at least one private server. Certain aspects explore using a software platform that manages syncing data from a cloud data bucket to a server data bucket by way of asynchronous notifications from the cloud data bucket to the software platform. However, syncing data in the opposite direction from the server data bucket to the cloud data bucket is by way of direct syncing and not through asynchronous notifications. Conflict resolution is also described when two different data object versions are uploaded to two different data buckets before the data objects can be synced across the data buckets.