Stateful Topic Scaling With Backup State Transfer
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Solution Overview
Problem
Existing event-driven platforms like Apache Kafka face inefficiencies in dynamically scaling topics due to the unavailability of backup states during repartitioning, leading to tedious and error-prone manual data transfer and state reconstruction during upscaling and the lack of downscaling support, which results in overprovisioned or underutilized resources.
Innovation Solution
A partition management system that suspends stateful applications, redistributes backup states and record logs using a consistent hash function, and generates temporary topics to facilitate efficient upscaling and downscaling of topics by maintaining state availability and reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual data transfer and state reconstruction is performed during topic upscaling, then topic scaling can be achieved, but the process becomes tedious and error-prone
Solution Approach 1:
The system performs preliminary actions by maintaining backup states of applications before topic scaling operations. These backup states are prepared in advance and can be quickly restored to new partitions during scaling, eliminating the need for tedious manual data transfer and state reconstruction after scaling occurs.
2Stability of the object's composition
If topic downscaling is not supported, then system stability is maintained, but resources become overprovisioned or underutilized
Solution Approach 1:
The system implements dynamic topic scaling by enabling both upscaling and downscaling operations. Topic partitions can be dynamically adjusted based on actual workload requirements, allowing the system to adapt its resource allocation and prevent overprovisioning or underutilization while maintaining stability through controlled scaling procedures.
3Device complexity
If backup states are not maintained during repartitioning, then system complexity is reduced, but state availability becomes unavailable during scaling
Solution Approach 1:
The system creates backup copies of application states before performing topic repartitioning operations. These copied states are stored in a recoverable format and can be quickly restored to new partitions during scaling operations, ensuring state availability without requiring complex real-time synchronization mechanisms.
4Productivity
If automatic state redistribution is implemented, then scaling efficiency is improved, but computational overhead increases
Solution Approach 1:
The system performs state redistribution preparations in advance by creating and storing backup states before scaling operations. This preliminary action allows for efficient automated redistribution during scaling without requiring intensive real-time computation, as the heavy lifting of state preparation is completed beforehand.
Data Source
AI summary
A system facilitating scaling of topics is provided. During operation, the system can suspend a stateful application of a topic and a stateful backup topic on an event-driven platform. The topic corresponds to a stream of events associated with the application. The system can modify configuration at the platform to allow a new set of partitions of the topic and a new set of backup partitions of the backup topic. The system can identify a state of event records from the application in a previous backup partition and identify a new backup partition allocated to the application. If they are different, the system can transfer the state to the new backup partition. The system can resume the application for generating an updated state, which is maintained at the new backup partition, based on the state and subsequent event records associated with the application.