Runtime Data Trait Upgrades Without Downtime
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Solution Overview
Problem
Existing data systems require downtime for updates or changes, which is problematic for continuous availability expected by users, especially in distributed and cloud-based repositories.
Innovation Solution
Implementing a method to dynamically update or upgrade data structures and policies in data systems without taking them offline, allowing for continuous operation by using dynamic definitions of data objects and traits, which can be added or modified at runtime, and applying upgrade policies to individual objects, sets, or entire repositories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data system updates or schema changes are performed using traditional methods, then data structure integrity is maintained, but system availability deteriorates due to required downtime
Solution Approach 1:
The patent segments the data repository into multiple versions (current version and new version) that can coexist. Data objects are gradually migrated from the current version to the new version in segments, allowing the system to maintain availability while performing schema changes. This is achieved through versioned data objects and incremental migration processes.
Solution Approach 2:
The patent implements dynamic version management where the data repository can transition between versions without complete downtime. The system dynamically switches between reading from the current version and writing to the new version, allowing continuous operation during schema evolution.
2Reliability
If the data repository is taken offline for schema updates, then upgrade completeness is achieved, but user access is lost during the update period
Solution Approach 1:
The patent performs preliminary actions by creating the new version schema and data structures before the current version is fully deprecated. The new version is prepared in advance and tested, then gradually activated while the old version continues to serve existing operations, ensuring upgrade completeness without full downtime.
Solution Approach 2:
The patent maintains continuity of useful action by allowing simultaneous operation of old and new versions. Users can continue accessing data in the current version while new data is written to the new version, ensuring continuous productive operation throughout the upgrade process.
3Stability of the object's composition
If rigid database structures are used to ensure data integrity, then system stability is maintained, but flexibility to accommodate business process changes is reduced
Solution Approach 1:
The patent changes the parameter of version management from static to dynamic. By introducing version numbers and allowing incremental version transitions, the system maintains data integrity through version control while gaining flexibility to adapt to business changes through controlled schema evolution.
Solution Approach 2:
The patent makes the database structure dynamic by allowing versioned schemas to coexist and transition. This enables the system to maintain stability through versioned data integrity while accommodating business changes through flexible version migration paths.
Data Source
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AI summary
A method, article of manufacture, and apparatus for managing a computing environment, such as a cloud data repository. In some embodiments, this includes modifying an object or a component of an object at runtime and storing the modified object or modified component of an object in a storage device. In some embodiment, the component of an object modified may include traits. In some embodiments, objects or traits may have more than one version.