Archive Expiration Extension via Dynamic Metrics

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Solution Overview

Problem

The existing systems for managing data archives in cloud storage face challenges in efficiently updating the expiration times of objects associated with previous archives, leading to resource-intensive and time-consuming processes, and increased storage costs due to frequent API calls.

Innovation Solution

The proposed solution involves extending the expiration time of objects associated with an archive based on data management policies and dynamically determined metrics, such as historical and predicted data change rates, to reduce the number of API calls and optimize storage costs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the expiration time of objects associated with an archive is updated frequently to reflect data management policies, then the accuracy of data retention management is improved, but the number of API calls increases leading to higher storage costs and reduced operational efficiency

Engineering Contradiction:

Improvedata retention management accuracyVSAvoidtime for updating expiration times

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system calculates and stores the extended expiration time in advance when the archive is created or when data management policies change. Instead of updating expiration times frequently in real-time, the system performs the calculation beforehand and uses this pre-computed value, thereby reducing the need for frequent API calls while maintaining accurate data retention management.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system automatically determines and applies extended expiration times based on the archive creation time and data management policies without requiring manual intervention or frequent API calls. The expiration time extension is calculated autonomously using stored metrics about data change rates, reducing operational overhead while maintaining reliability.

Inventive Principle:

Principle #25Self-service

2Reliability

Engineering Contradiction:

Improvedata retention management accuracyVSAvoidstorage costs

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system performs the expiration time calculation in advance when the archive is created or when data management policies change. By pre-calculating and storing the extended expiration time, the system eliminates the need for frequent subsequent API calls to update expiration times, thereby reducing storage costs while maintaining accurate data retention management.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system autonomously determines and applies extended expiration times based on archive creation time and data management policies without requiring frequent external API calls. This self-service approach reduces the operational overhead and storage costs associated with frequent updates while maintaining reliable data retention management.

Inventive Principle:

Principle #25Self-service

3Productivity

If the expiration time of objects associated with an archive is extended based on predicted data change rates, then operational efficiency is improved, but the complexity of determining appropriate extension periods increases

Engineering Contradiction:

Improveoperational efficiencyVSAvoidcomplexity of determining extension periods

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system uses historical data change rates as feedback to determine appropriate expiration time extensions. By analyzing past data change patterns and using this feedback to calculate extension periods, the system achieves operational efficiency while keeping the complexity manageable through data-driven decision-making rather than complex rule-based systems.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system changes the parameter of expiration time based on predicted data change rates. By adjusting the expiration time extension dynamically according to data change characteristics, the system optimizes operational efficiency. The complexity is managed by using straightforward parameter adjustments rather than complex multi-variable calculations.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250053539A1Extending an expiration time of an object associated with an archive

Publication Date: 2025.02.13 COHESITY INC

AI summary

An amount of expiration time extension for one or more objects associated with a first archive of a first snapshot of a source storage is determined based at least in part on a second data management policy associated with a second archive and one or more dynamically determined metrics. The first archive that includes the one or more objects is caused to be stored to a remote storage. At least a portion of content of the first archive is referenced by data chunks stored in a first chunk object of the remote storage and the first archive is associated with a first data management policy. Based on the determined amount of expiration time extension, an expiration time for the one or more objects associated with the first archive is stored in an archive metadata of the one or more objects associated with the first archive.