Landscape Simulation for Service Relocation Latency
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Solution Overview
Problem
Existing systems face challenges in efficiently evaluating and optimizing the impact of service relocation on overall system performance due to communication latency in geographically distributed computing services, particularly when considering high availability and disaster recovery scenarios, and require costly and risky iterative testing processes.
Innovation Solution
A tool that monitors inter-service communication, generates models of service landscapes, and simulates changes to latency, allowing for faster and less costly analysis of different service deployments by selectively introducing latency and evaluating its effects on service-to-service communication patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a service is moved from an on-premise system to a cloud-based server, then cost savings and scalability are achieved, but communication latency increases affecting system performance
Solution Approach 1:
The system performs preliminary analysis of communication patterns and latency impacts before service relocation. By monitoring inter-service communication and generating landscape models in advance, the system can predict performance consequences and make informed relocation decisions, preventing unacceptable latency increases before they occur.
Solution Approach 2:
The patent introduces a landscape simulator as an intermediary tool between service relocation decisions and actual production landscape changes. This simulator allows evaluation of latency impacts in a virtual environment before implementing real migrations, acting as a mediator that prevents harmful latency increases while enabling cost-effective relocations.
2Measurement precision
If iterative testing is performed to evaluate landscape changes, then accurate performance assessment is achieved, but time and cost increase significantly
Solution Approach 1:
The system creates a virtual copy of the service landscape including services, communication patterns, and latency characteristics. This landscape model serves as a replica that can be used for iterative testing and evaluation without affecting the actual production system, enabling accurate performance assessment while eliminating the need for costly parallel test landscapes.
Solution Approach 2:
The landscape model is built in advance by monitoring actual communication patterns in the production environment. This preliminary capture of communication data allows subsequent iterative testing to be performed on the model rather than requiring actual iterative deployments and measurements in production, dramatically reducing testing time while maintaining accuracy.
3Measurement precision
If production landscape is used for testing latency impacts, then real-world accuracy is achieved, but system stability and availability are compromised
Solution Approach 1:
The landscape simulator acts as an intermediary that captures real-world communication patterns from production but provides a safe virtual environment for testing. By injecting latency into the model rather than the actual production system, the simulator maintains real-world accuracy while protecting production stability and availability during evaluation processes.
4Productivity
If comprehensive service relocation options are evaluated, then optimal performance is achieved, but computational complexity increases exponentially
Solution Approach 1:
The system focuses evaluation on local communication patterns and latency impacts for each service rather than exhaustively analyzing all possible global configurations. By generating landscape models that capture actual communication frequencies and patterns, the system identifies which service relocations will have the most significant local impact, enabling efficient optimization without exponential computational complexity.
Data Source
AI summary
Systems and methods include reception of first data representing each of a plurality of calls transmitted between services of a service landscape, the first data representing each call comprising a respective value of an identifier, identification of a first plurality of the plurality of calls as comprising a same value of the identifier, determination, for each outbound call of the first plurality of calls, of a hypothesis associating the outbound call with a time delay relative to a preceding inbound call of the first plurality of calls, reception of second data representing each of a second plurality of calls transmitted between the services of the service landscape while a latency between two services of the service landscape is increased, the second data representing each of the second plurality of calls comprising a second same value of the identifier, determination of an expected timing of each outbound call of the second plurality of calls based on the hypotheses and the increased latency, comparison of the expected timing of each outbound call of the second plurality of calls with a timing of each outbound call of the second plurality of calls, and verification of one or more of the hypotheses based on the comparisons of the expected timing of each outbound call of the second plurality of calls with the timing of each outbound call of the second plurality of calls.