Version-Controlled Container Updates with DAG Scheduling
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Solution Overview
Problem
Existing container orchestration platforms face limitations in environments requiring specific ordering and timing of updates, especially in automotive settings, leading to reduced efficiency, reliability, and control over updates.
Innovation Solution
Integrate a version control system repository with hooks to provide a backing store for cluster data, using a directed-acyclic graph (DAG) to control the ordering and timing of multi-stage updates, enabling decentralized synchronization across multiple datacenters or cloud providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a traditional backing store is used for cluster data, then the system can store configuration data, but it cannot ensure specific ordering and timing of updates
Solution Approach 1:
The patent introduces a version control system as an intermediary layer between the container orchestration platform and the backing store. This VCS mediates update operations by enforcing ordering and timing constraints through its commit history and branch management mechanisms, thereby achieving reliable update sequencing without requiring changes to the underlying storage infrastructure.
Solution Approach 2:
The patent applies a version control system originally designed for software development to manage infrastructure configuration data. This multi-functional application allows the same system to handle both code versioning and infrastructure update ordering, providing a universal solution that works across different environments including automotive systems with strict update sequencing requirements.
2Adaptability or versatility
If decentralized synchronization is implemented across multiple datacenters, then cloud provider flexibility improves, but update coordination complexity increases
Solution Approach 1:
The patent implements feedback mechanisms through the version control system's commit history and status tracking. Each datacenter reports its update state back to the centralized VCS, which then coordinates subsequent updates based on this feedback. This allows decentralized operations while maintaining global consistency, as the VCS uses the feedback to determine the next appropriate update action across different cloud providers.
3Extent of automation
If hooks are integrated with the version control system, then update automation improves, but system complexity increases
Solution Approach 1:
The patent implements hooks that automatically trigger update operations based on version control events. When a commit is detected, the hook automatically initiates the update process without requiring manual intervention. This self-service mechanism automates the orchestration platform's update application, reducing operational overhead while the underlying complexity is encapsulated within the hook implementation rather than the user interface.
Data Source
AI summary
A change to a repository of a version control system is identified. A processing device may provide update data to a container orchestration platform in response to identification of the change to the repository of the version control system. The update data may be associated with a multi-stage update on a component of the container orchestration platform. The update data may indicate scheduling information associated with each stage of the multi-stage update. The repository may be updated based on completion data received from the container orchestration platform in response to performing at least a portion of the multi-stage update based on the update data.