Concurrency Controller for Cloud Migration Flow Control
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Solution Overview
Problem
Existing organization migration processes in cloud-based systems face inefficiencies, errors, and resource contention due to high manual intervention, leading to prolonged downtimes and potential failures, especially when migrating application data and services between computing instances.
Innovation Solution
Implementing a framework that uses a migration scheduler and orchestration engine with concurrency controllers to manage resource utilization and flow control, dynamically adjusting concurrency limits based on feedback from the target system instance, thereby minimizing manual intervention and optimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If close and intensive human supervision is used for organization migrations, then migration reliability is improved, but migration time and system resource contentions increase
Solution Approach 1:
The system implements self-service through automated migration execution where the migration framework autonomously performs data and service migration without requiring continuous human intervention. The automated concurrency controller dynamically manages migration processes, eliminating the need for expert supervision throughout the entire migration time period while maintaining reliability through systematic control mechanisms.
Solution Approach 2:
The automated concurrency controller receives feedback from the target system instance about resource availability and migration progress. Based on this feedback, the controller dynamically adjusts concurrency limits and migration pacing to optimize both reliability and time efficiency, resolving the contradiction between thorough supervision and migration speed.
2Manufacturing precision
If manual input and human supervision are increased, then migration control precision is improved, but system resource contentions and errors increase
Solution Approach 1:
The automated concurrency controller continuously monitors feedback from the target system instance regarding resource utilization and adjusts migration concurrency limits accordingly. This closed-loop control provides precise migration management while preventing resource contentions by dynamically adapting to system conditions, eliminating the harmful effects of manual intervention.
Solution Approach 2:
The system transitions from static manual control to dynamic automated control where concurrency limits are continuously adjusted based on real-time system conditions. The automated controller adapts migration parameters dynamically to match available resources, providing precision control without causing resource contentions that arise from fixed manual schedules.
3Productivity
If migration speed is increased, then productivity is improved, but performance degradation and failures increase
Solution Approach 1:
The automated concurrency controller dynamically adjusts migration speed based on real-time feedback from the target system instance. When the system can handle high concurrency, the controller increases migration speed to maximize productivity. When resource constraints are detected, the controller automatically reduces speed to maintain performance stability, preventing failures while optimizing overall migration throughput.
Data Source
AI summary
Migration specific action requests to perform a set of migration specific actions are sent from a source system instance to a target system instance. Migration specific action responses are received from the target system instance. Based on the migration specific action responses, traffic lights for resource utilization of the target system instance are determined. Based on the traffic lights, a concurrency limit is determined for the specific time. The concurrency limit is applied to scale a total number of ongoing migration specific actions to be requested of the target system instance at the specific time.