Outcome-Based Data Protection via Rule Engine and Artifacts
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data protection approaches rely on a single controlling application, limiting data protection to its throughput and availability, and focus on the success or failure of specific actions rather than the overall protection objectives over time, failing to guarantee a desired level of data protection beyond the time of the action.
Innovation Solution
An outcome-based data protection system that evaluates data protection artifacts against predefined objectives, using a rule engine to determine necessary actions and verify if the objectives are met, allowing for a collection of data protection applications to work together without coordination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single controlling data protection application is used to manage all data protection actions, then the system has simplified control and configuration, but the data protection capability is limited to the throughput and availability of that single application
Solution Approach 1:
The patent segments the data protection system into multiple independent data protection applications, each capable of performing data protection actions autonomously. Instead of one centralized controller, multiple applications work in parallel, each handling specific data protection tasks. This segmentation allows the system to scale beyond the limitations of a single application's throughput and availability.
Solution Approach 2:
The patent creates a universal data protection artifact that can be produced by any data protection application and consumed by any other. This artifact serves as a common interface and communication mechanism, allowing diverse applications with different capabilities to work together seamlessly. The universal artifact enables multi-functionality across the system, combining the strengths of multiple specialized applications.
2Measurement precision
If data protection is measured by the success or failure of specific actions (e.g., backup operations), then the measurement is simple and immediate, but it cannot guarantee a desired level of data protection over time beyond the action time
Solution Approach 1:
The patent implements feedback mechanisms where data protection applications not only execute actions but also produce artifacts that document the protection state. These artifacts provide continuous feedback about the protection status, enabling verification of whether protection objectives are met over time. The feedback loop ensures that protection is not just an instantaneous action result but a sustained state that can be verified and maintained.
Solution Approach 2:
The patent uses data protection artifacts to establish predetermined criteria for successful protection before actual protection events occur. By defining protection objectives and criteria in advance (preliminarily), the system can verify whether these objectives are met after protection actions are executed. This preliminary definition of success criteria enables ongoing verification of protection levels beyond individual action timestamps.
3Ease of operation
If data protection applications are configured in precise detail relative to actions, then the configuration is specific and controllable, but it does not precisely determine the objective attempting to be met
Solution Approach 1:
The patent introduces data protection artifacts as intermediary elements between the configuration details and the protection objectives. These artifacts serve as a mediator that translates specific action configurations into verifiable objective measurements. Rather than directly linking configuration parameters to objectives, the artifacts provide an intermediate layer that documents what protection was achieved and whether it meets the defined objectives, thus preserving objective definition clarity.
Data Source
AI summary
A service level agreement (SLA) is defined for providing data protection with one of data protection levels on data stored in a first system. The SLA includes zero or more service level objectives (SLOs), where each SLO describes a data protection objective to be met. A rule engine applies a set of rules to the SLOs to determine a list of actions to be performed in order to achieve the data protection objectives specified by the SLOs. One or more data protection services are provisioned to be performed at the first storage system and a second storage system that provides data protection for the first storage system. An outcome of the data protection services is evaluated in view of the SLOs to determine whether the data protection objectives have been satisfied.