Dynamic Immutability for Public Cloud Snapshot Data and Garbage Collection
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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 prevents effective 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 time 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 security and integrity are improved, but storage cost increases due to inability to perform garbage collection
Solution Approach 1:
The patent applies dynamic immutability by transitioning snapshot data entities from mutable to immutable state based on retention policy evaluation. The storage system periodically assesses snapshot data entities and dynamically adjusts their immutability status - marking them immutable when they meet retention criteria and allowing deletion when they no longer need to be retained. This dynamic state change resolves the contradiction by providing security only when necessary while enabling cost-effective garbage collection when retention is no longer required.
Solution Approach 2:
The patent changes the immutability parameter of snapshot data entities based on retention policy evaluation. By evaluating retention policies and dynamically adjusting the immutability parameter - setting it to true when snapshots meet retention criteria and false when they don't - the system achieves both data security for retained snapshots and cost efficiency through garbage collection of non-retained snapshots.
2Reliability
If snapshot data is marked as immutable for extended periods, then protection from unauthorized deletion is improved, but storage capacity efficiency deteriorates due to inability to reclaim space
Solution Approach 1:
The system dynamically adjusts the duration of immutability protection based on retention policy evaluation. Rather than applying static long-term immutability to all snapshot data, the system periodically evaluates which snapshots meet retention criteria and applies immutability protection only to those that do. This dynamic approach ensures protection from unauthorized deletion for necessary snapshots while enabling space reclamation for snapshots that no longer require protection, thus improving storage capacity efficiency.
Solution Approach 2:
The patent changes the immutability parameter and its duration based on retention policy assessment. By evaluating retention policies and adjusting the immutability parameter accordingly - extending immutability duration for snapshots that meet retention criteria and reducing or removing it for others - the system achieves both protection from unauthorized deletion and improved storage capacity efficiency through selective and time-limited immutability application.
3Adaptability or versatility
If dynamic immutability extension is implemented through periodic scan jobs, then flexibility for garbage collection is improved, but system complexity increases due to additional management overhead
Solution Approach 1:
The patent implements periodic scan jobs that evaluate snapshot data entities and their retention policies at scheduled intervals. These periodic evaluations determine whether snapshots should be marked immutable or made eligible for garbage collection. This periodic action provides flexibility for garbage collection by systematically reviewing snapshot status while managing system complexity through scheduled, automated operations rather than continuous manual intervention.
Solution Approach 2:
The system employs automated scan jobs that self-evaluate snapshot data entities against retention policies and automatically adjust immutability status without requiring manual intervention. This self-service approach improves flexibility for garbage collection by enabling automated decision-making while reducing system complexity by eliminating the need for complex manual management processes.
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.