Hybrid Cloud Integration Flow Routing to Reduce Serialization Overhead
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Solution Overview
Problem
In hybrid cloud environments, existing technologies face inefficiencies in message processing due to excessive serialization costs and CPU usage across the hybrid cloud boundary, particularly when messages need to be transferred between on-premise systems and public clouds, leading to increased latency and reduced performance.
Innovation Solution
A method and system that monitor integration flows to determine the processing location of messages based on CPU workload and message priority, altering the processing path to optimize CPU usage by routing messages to either on-premise or public cloud nodes, thereby reducing serialization costs and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If messages are processed by transferring between on-premise systems and public cloud, then message routing flexibility is improved, but serialization costs and CPU usage increase
Solution Approach 1:
The system pre-calculates and stores serialization cost thresholds for different message types and routes. Before actual message processing, the integration flow monitor retrieves these pre-computed thresholds to make routing decisions, avoiding real-time serialization cost calculations and reducing CPU overhead during message processing
Solution Approach 2:
The system continuously monitors actual serialization costs and CPU usage metrics from message processing operations. This feedback is used to dynamically adjust routing decisions and update threshold values, optimizing the balance between routing flexibility and serialization costs over time
2Adaptability or versatility
If messages are transferred between hybrid cloud boundaries, then processing location flexibility is improved, but latency increases
Solution Approach 1:
The system pre-determines optimal processing locations by evaluating latency thresholds for different cloud boundaries and message types. These pre-computed routing rules are stored and applied during message processing, enabling rapid routing decisions without real-time latency calculations, thus reducing actual message transfer latency
Solution Approach 2:
The system dynamically adjusts message routing based on real-time conditions such as current workload, message priority, and observed latency patterns. High-priority messages can be routed through lower-latency paths even if they require additional processing, while lower-priority messages follow cost-optimized routes
3Reliability
If integration flow processes all messages through secure connectors, then security is improved, but CPU serialization load increases
Solution Approach 1:
The system applies different security processing levels to different messages based on their sensitivity and routing requirements. Messages are categorized into security tiers, and only those requiring cross-cloud transfer undergo full serialization through secure connectors. Local messages process through simplified paths, reducing overall CPU serialization load while maintaining appropriate security levels for each message type
Solution Approach 2:
The system changes the security processing parameters dynamically based on message characteristics. For low-priority or non-sensitive messages, serialization is skipped or minimized. For high-priority or sensitive messages, full secure connector processing is applied. This parameter-based differentiation reduces average CPU load while maintaining security where required
Data Source
AI summary
An integration flow is monitored to determine a processing location of a message. The integration flow includes a route, one or more nodes, and one or more secure connectors. A first message is received by the integration flow. A central processing unit serialization load is received including a serialization of the first message on a first secure connector and a deserialization of the first message on a second secure connector. A processing load of the first message running on a first node of the one or more nodes is received. A first threshold of a processing load of the first message is received. The first threshold is determined to have been reached. Based on the first threshold being reached, a processing location of the integration flow is altered such that the first message is processed on a second node of the one or more nodes.