Regional Resource Reclamation for Dependency-Safe Cloud Shutdown
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Solution Overview
Problem
Cloud computing systems face challenges in gracefully shutting down resources while respecting dependencies, leading to data loss, corruption, and service disruptions during resource reclamation, especially in complex, distributed deployments across multiple regions, which also generate significant network traffic and resource consumption.
Innovation Solution
A decentralized, local resource reclamation process that identifies and respects dependencies between computing resources, allowing for graceful shutdowns and a reversible intermediate suspend state to minimize network traffic and resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud computing resources are shut down during reclamation, then resources are freed for reuse, but data loss and corruption occur due to incomplete operations
Solution Approach 1:
The system performs preliminary actions by identifying all dependencies and constructing a shutdown order before actually shutting down resources. The dependency identification module analyzes resource relationships and creates a structured shutdown sequence, ensuring that parent resources are shut down before child resources, preventing data loss while maintaining efficient reclamation.
Solution Approach 2:
The resource shutdown process is segmented into distinct phases: dependency identification, shutdown order construction, and staged execution. Resources are shut down in discrete groups according to their dependency levels, allowing systematic resource reclamation while maintaining data integrity through controlled segmentation of the shutdown process.
2Device complexity
If centralized resource reclamation control is implemented, then coordination is simplified, but network traffic and resource consumption increase significantly
Solution Approach 1:
The centralized reclamation control is segmented into distributed regional controllers. Each region independently manages its own resource shutdown based on local dependency information, eliminating the need for continuous centralized coordination. This reduces network traffic while maintaining proper shutdown sequencing through local autonomy.
Solution Approach 2:
Regional controllers autonomously identify dependencies and execute shutdown sequences within their own regions without requiring constant external coordination. The system enables self-service reclamation where each region manages its own resources independently, significantly reducing network overhead while ensuring proper shutdown order through local dependency analysis.
3Productivity
If resources are permanently reclaimed, then hardware is freed for immediate reuse, but the process cannot be reversed causing permanent data loss
Solution Approach 1:
The system implements a two-stage process where resources are first suspended (recoverable state) and then reclaimed (permanent state). The suspend operation preserves resources in a state where they can be recovered if needed, while the subsequent reclaim operation permanently frees them. This staged approach allows flexibility to recover resources if reclamation proves premature, while still achieving hardware availability when reclamation is appropriate.
Data Source
AI summary
A method includes receiving, at a first instance of a resource reclamation service, a lifecycle event for a cloud computing tenancy, where the first instance is deployed at a first region of a plurality of regions of a cloud environment; identifying, at the first instance, a subset of the plurality of regions to which computing resources of the tenancy are deployed, the subset of the plurality of regions including the first region and a second region; transmitting, from the first instance to a second instance of the resource reclamation service, an indication of the lifecycle event, where the second instance is deployed at the second region; identifying, at the second instance, a first subset of the computing resources of the tenancy deployed at the second region; and executing, at the second instance, a first set of reclamation actions for the first subset of the computing resources of the tenancy.