Dynamic Data Object Replication in Cloud Services

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Solution Overview

Problem

Cloud computing environments face challenges in allowing external users to dynamically access and process data due to limited access privileges, leading to issues like latency, throttling, and inability to use modern BI tools or implement machine learning models effectively.

Innovation Solution

The solution involves dynamically replicating data objects from an external-access-limited source repository to an external-service-accessible replica repository, using bootstrap and CDC task objects to capture changes, and converting data objects to a consistent format, enabling fast access and analysis by external users.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data objects are stored in an external-access-limited source repository to ensure security and control, then data security and access control are improved, but external users experience latency and cannot access data dynamically for analysis

Engineering Contradiction:

Improvedata securityVSAvoiddata access speed

Core Design Contradiction:

ReliabilityVSSpeed

Solution Approach 1:

The patent creates replica data objects that are copies of the source data objects. These replicas are stored in an external-service-accessible repository, allowing external users to access data without directly accessing the secured source repository. The copying mechanism enables fast access to data copies while the original secured data remains protected.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent introduces a data object repository and replication service as an intermediary between the external users and the secured source data. This intermediary layer manages the replication, synchronization, and access control, allowing external users to query replicas while the source repository maintains its security constraints.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If data objects are replicated dynamically to enable external access, then external user access and analytics capability are improved, but system complexity and synchronization overhead increase

Engineering Contradiction:

Improveexternal access capabilityVSAvoidreplication system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the replication process into distinct components: bootstrap task objects for initial replication, CDC task objects for change detection, and processing queue data objects for managing replication workflows. This segmentation allows each component to be independently managed and optimized, reducing overall system complexity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent uses parameter changes in data objects (such as version identifiers, timestamps, and change indicators) to track and synchronize data state. By monitoring these parameters, the system can determine when source data has changed and trigger appropriate replication actions without complex comparison logic.

Inventive Principle:

Principle #35Parameter changes

3Stability of the object's composition

If change data capture (CDC) mechanisms are implemented to maintain data consistency, then data consistency is improved, but processing overhead and resource consumption increase

Engineering Contradiction:

Improvedata consistencyVSAvoidprocessing overhead

Core Design Contradiction:

Stability of the object's compositionVSUse of energy by moving object

Solution Approach 1:

The patent implements self-service mechanisms where data objects contain embedded change indicators and version information that automatically trigger replication actions. When a source data object changes, the change is detected through CDC mechanisms that monitor data object parameters, and the replication process is automatically initiated without requiring complex external coordination or additional computational overhead.

Inventive Principle:

Principle #25Self-service

4Measurement precision

If multiple task objects (bootstrap and CDC) are used to manage replication, then replication accuracy and data freshness are improved, but system complexity and operational overhead increase

Engineering Contradiction:

Improvedata replication accuracyVSAvoidsystem operation simplicity

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent creates a universal task object framework where both bootstrap and CDC tasks follow the same structural patterns and execution mechanisms. Task objects serve multiple functions: they can be used for initial data replication, ongoing change detection, error handling, and synchronization. This multi-functionality reduces the need for separate specialized components and simplifies operational management.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20230004296A1Methods, apparatuses and computer program products for dynamic data object replication and dynamic data object conversion in a network service cloud

Publication Date: 2023.01.05 ATLASSIAN US INC

AI summary

Various examples herein described are directed to methods, apparatuses and computer program products configured for dynamically replicating and/or converting source data objects in one or more external-access-limited source data object repositories to replica data objects in one or more external-service-accessible replica data object repositories in a network service cloud. For example, a network service server of the network service cloud may generate a plurality of bootstrap task objects and at least one change data capture (CDC) task object, and may generate the replica data objects based on the task objects.