Microservice Utilization Tracking via Hop Data Records
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Solution Overview
Problem
Current systems lack effective methods for tracking microservice utilization in distributed application structures, making it difficult to identify which microservices are used by client applications and how often, leading to inefficiencies in scaling and performance optimization.
Innovation Solution
A method involving trace programs that record and aggregate hop data records between microservices, including client applications, to count instances and calculate latency, allowing for provisioning and decommissioning of microservices based on usage data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If distributed application structure with microservices is used, then system scalability and flexibility are improved, but tracking and monitoring of service utilization becomes difficult
Solution Approach 1:
The patent introduces hop data records as intermediary components that mediate between microservices and the tracking system. Each hop data record captures interaction information between service pairs, serving as a measurable unit that enables centralized aggregation and analysis without requiring direct instrumentation of every microservice interaction. This intermediary layer resolves the contradiction by making distributed service utilization trackable through standardized data collection points.
Solution Approach 2:
The system implements feedback mechanisms by aggregating hop data records to generate utilization metrics that are fed back into the microservice management process. The aggregated data enables automatic provisioning and decommissioning decisions based on actual service usage patterns, creating a closed-loop system where tracking information directly informs scalability decisions. This feedback loop transforms the difficulty of tracking into a useful monitoring capability that enhances system adaptability.
2Productivity
If microservice instances are dynamically provisioned and decommissioned, then resource efficiency is improved, but service utilization data accuracy is compromised
Solution Approach 1:
The patent applies preliminary action by pre-defining hop data record structures and aggregation rules before microservice provisioning decisions are made. The tracking system is established in advance with standardized data collection mechanisms, ensuring that utilization data is captured consistently regardless of dynamic provisioning events. This preliminary setup ensures measurement precision is maintained even as service instances are dynamically created or removed.
Solution Approach 2:
The system segments utilization tracking into discrete hop data records for individual service pairs, which are then aggregated to produce overall utilization metrics. This segmentation allows for precise tracking of each microservice's usage independently, enabling accurate resource efficiency calculations even when instances are dynamically provisioned or decommissioned. Each segment can be measured and managed independently, maintaining data accuracy throughout dynamic changes.
Data Source
AI summary
Methods and systems for tracking client application utilization of microservices are provided. Exemplary methods include: requesting completed hop data records, the completed hop data records being associated with a plurality of microservices, a hop being between two microservices of the plurality of microservices; receiving the completed hop data records; aggregating the completed hop data records to identify hop data records associated with a client application, count a number of instances the client application utilized each microservice of the plurality of microservices, and calculate an average latency for each hop; and provisioning and/or decommissioning instances of the plurality of microservices using the aggregated hop data records.