In-Memory Orchestration for Low-Latency Synchronous Processing
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Solution Overview
Problem
Existing orchestration platforms face latency issues due to heavy database accesses for synchronous processing, which hinder efficient and secure management of customer flows.
Innovation Solution
Implementing an in-memory database on a per-transaction basis within a synchronous orchestration engine, with serialization and deserialization operations to manage customer flow data, followed by storage in a disk-based database for asynchronous processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a disk-based database is used for synchronous processing in orchestration platforms, then data persistence and auditing capabilities are improved, but processing latency increases due to heavy database access overhead
Solution Approach 1:
The patent segments the database system into two distinct layers: an in-memory database for high-speed synchronous processing operations, and a disk-based database for data persistence and auditing. This segmentation allows each layer to specialize in its strength - the in-memory database eliminates I/O latency for frequent access operations, while the disk-based database ensures data durability and long-term storage capabilities.
Solution Approach 2:
The in-memory database serves as an intermediary layer between the synchronous orchestration engine and the disk-based database. It acts as a buffer that captures and caches data during synchronous processing, thereby shielding the orchestration engine from the latency of direct disk-based database access while ensuring data is eventually persisted to the disk-based database for reliability.
2Loss of information
If frequent database accesses are performed for tracking customer flow operations, then auditing and tracking capabilities are improved, but system performance deteriorates due to I/O overhead
Solution Approach 1:
The system performs preliminary action by pre-loading data into the in-memory database before synchronous processing operations require it. This allows the orchestration engine to access frequently needed data without triggering disk I/O operations during critical processing paths, thereby maintaining both auditing capability and system performance.
Solution Approach 2:
The in-memory database creates copies of data from the disk-based database for active processing. These copies reside in volatile memory and can be accessed rapidly for auditing and tracking operations without impacting the performance of synchronous processing, as the expensive disk I/O operations are decoupled from the time-critical processing path.
Data Source
AI summary
An orchestration platform leverages an in-memory database for guaranteed synchronous processing of requests from origin devices. The in-memory database is created on a per-transaction basis and localized to a synchronous orchestration engine, which is a part of an orchestration platform. The in-memory database is serialized and stored in memory. To update the in-memory database, the in-memory database is deserialized and one or more database operations can be performed on the in-memory database. The updated in-memory database is communicated to a return to caller service which deserializes and extracts data from the updated in-memory database. The data is stored in a disk-based database that is accessible by an asynchronous orchestration engine. At this point, the updated in-memory database no longer exists.