Version Control for Distributed Computing State Management
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Solution Overview
Problem
Legacy techniques for managing and controlling the state of distributed computing systems are inadequate, as they fail to efficiently track and restore the state due to the complexity of interdependencies and non-procedural aspects, often resulting in manual intervention to achieve the desired state.
Innovation Solution
The implementation of a version control system that commits resource usage intent specifications and associated data snapshots at specific moments, allowing for efficient tracking and control of system states, enabling seamless state management and reversion by capturing macro-states and referencing deterministic sets of objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If procedural tracking techniques are used to record system operations, then state changes can be captured, but the techniques fail to consider interdependencies and non-procedural aspects, resulting in incomplete state capture
Solution Approach 1:
The patent creates a virtual copy of the entire computing cluster state at specific points in time, storing it as immutable data in a version control system. This copy captures the complete state including configuration, topology, and resource distribution without needing to track every procedural change, thereby capturing complete state information while avoiding the complexity of tracking all operations.
Solution Approach 2:
The patent introduces a state management service as an intermediary between the computing cluster and the version control system. This service automatically captures state snapshots and manages version control operations, eliminating the need for administrators to manually track state changes while ensuring complete and accurate state capture.
2Ease of operation
If legacy procedural techniques are used for state restoration, then some state recovery is possible, but manual intervention is required to achieve the desired state due to interdependencies
Solution Approach 1:
By storing complete virtual copies of cluster states in the version control system, the patent enables direct restoration to any previous state without manual intervention. The stored state snapshots contain all necessary information including interdependencies, allowing administrators to restore states accurately and easily by simply applying the stored configuration.
3Measurement precision
If complete cluster state snapshots are stored frequently, then state tracking accuracy improves, but memory and processing resources are consumed
Solution Approach 1:
The patent implements periodic state snapshotting at meaningful intervals (e.g., when significant configuration changes occur or at scheduled times) rather than continuous monitoring. This approach maintains high state tracking precision by capturing states at critical moments while minimizing storage consumption by avoiding redundant snapshots during stable periods.
Solution Approach 2:
The patent extracts and stores only the essential state information needed for restoration in the version control system, separating critical state data from transient operational data. This extraction approach maintains state tracking precision by preserving all necessary restoration information while reducing overall storage requirements.
Data Source
AI summary
Systems and methods commence upon detecting certain computing system specification change events. Changes are recorded in resource usage intent specification records that characterize desired states associated with respective resources of the computing system. The change event causes generation of a data state snapshot of data stored in the computing system. A state tuple is constructed to associate the desired state with the data state. The state tuple is committed to a version control system. At any time, a user or process can select a selected system state tuple from committed tuples stored in the version control system. The tuple is analyzed to determine its associated desired state and its data state. Actions are taken to restore the data state of the tuple to the computing system, and then bringing the computing system to the state of the tuple so as to reproduce the desired system state in the computing system.