Public Cloud Snapshot Storage With Dynamic Immutability
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Solution Overview
Problem
Storage of snapshot data in public cloud environments is vulnerable to unauthorized access, modification, and deletion, and marking data as permanently immutable can prevent garbage collection, leading to increased storage costs.
Innovation Solution
Implement dynamic immutability for snapshot data entities by initially marking them as immutable for a limited period and periodically extending the immutability period based on retention needs, using a scan job to evaluate and extend the immutability of snapshot data entities that are not yet eligible for garbage collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If snapshot data is marked as permanently immutable in public cloud environment, then data protection from unauthorized access and modification is improved, but garbage collection capability deteriorates leading to increased storage costs
Solution Approach 1:
The patent implements dynamic immutability by transitioning snapshot data from mutable to immutable state based on retention policy evaluation. The system periodically assesses snapshot data and selectively applies immutability markers only to data that has satisfied retention requirements, allowing flexible garbage collection for data ready for deletion while maintaining protection for data requiring retention. This dynamic state management resolves the contradiction between permanent protection and cost-effective storage.
Solution Approach 2:
The system changes the immutability parameter of snapshot data dynamically based on retention policy satisfaction. Rather than maintaining a fixed immutable state, the system adjusts the immutability parameter according to whether the data meets retention criteria, enabling cost optimization through selective garbage collection while maintaining reliability for protected data through policy-driven parameter changes.
2Stability of the object's composition
If snapshot data is marked as immutable for extended periods, then data integrity is improved, but storage cost increases due to prevention of garbage collection
Solution Approach 1:
The system implements periodic evaluation of snapshot data against retention policies, transitioning data between mutable and immutable states at regular intervals. This periodic action ensures data integrity is maintained only when necessary (when retention criteria are met) while enabling cost reduction through garbage collection of data that has completed its retention period, resolving the contradiction between continuous integrity protection and cost optimization.
3Adaptability or versatility
If dynamic immutability extension is implemented through periodic scan jobs, then flexibility in garbage collection is improved, but system complexity increases
Solution Approach 1:
The system implements self-service through automated scan jobs that periodically evaluate snapshot data against retention policies and automatically adjust immutability status accordingly. This self-service mechanism provides flexible garbage collection capability without requiring complex manual management, as the system autonomously determines which data should be protected and which can be collected, balancing adaptability with manageable complexity.
Data Source
AI summary
A data management system may support techniques for immutable storage of snapshot data entities, which may each include data corresponding to one or more snapshots, in a cloud environment. The data management system may determine respective retention periods and respective immutability periods for the snapshot data entities. The data management system may extend the respective immutability period for a first snapshot data entity based on the respective retention period for the first snapshot data entity being greater than or equal to a threshold duration. Additionally or alternatively, the data management system may maintain (refrain from extending) the respective immutability period for a second snapshot data entity based at least in part on the respective retention period for the second snapshot data entity being less than the threshold duration.