Telemetry Query Injection for Microservice Debugging
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Solution Overview
Problem
In microservices architectures with disaggregated computing, it is challenging to provide fine-grained tracing capabilities, including dynamic query generation and injection, due to the complexity of interdependent microservices components and heterogeneous hardware resources.
Innovation Solution
Implementing telemetry targeted query injection through a service management component that dynamically recommends and ingests queries to detect anomalies, discover activation profiles, and modify queries for enhanced debugging, while utilizing service mesh capabilities for observability and traceability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If microservices are deployed across many heterogeneous hardware devices to increase elasticity and resource utilization, then scalability and resource efficiency are improved, but fine-grained tracing capabilities and debugging difficulty deteriorate
Solution Approach 1:
The patent introduces a service mesh as an intermediary layer between microservices and heterogeneous hardware devices. The service mesh includes a data plane for packet forwarding and a control plane for managing tracing and debugging operations. This intermediary abstracts the complexity of tracing across diverse hardware devices, allowing fine-grained tracing capabilities without directly managing the heterogeneity of underlying devices.
Solution Approach 2:
The service mesh implements universal tracing and debugging mechanisms that work across all heterogeneous hardware devices. By creating a unified service mesh layer, the system provides consistent tracing capabilities regardless of the underlying hardware diversity, making the system adaptable to different devices while maintaining manageable complexity.
2Loss of energy
If disaggregated computing resources are used to improve resource utilization and lower costs, then resource efficiency is improved, but the difficulty of providing fine-grained tracing and dynamic query generation increases
Solution Approach 1:
The service mesh acts as an intermediary between the control system and disaggregated computing resources. It provides a unified interface for dynamic query generation and injection across distributed hardware accelerators, CPUs, and GPUs, simplifying the detection and measurement processes despite resource disaggregation.
Solution Approach 2:
The patent segments the tracing and debugging functionality into modular components within the service mesh. The data plane handles packet forwarding while the control plane manages tracing operations, allowing independent optimization of each component for disaggregated resources while maintaining overall system coherence.
3Reliability
If service mesh is introduced to manage network-based inter-process communication, then communication reliability is improved, but system complexity increases
Solution Approach 1:
The service mesh is segmented into distinct data plane and control plane components. The data plane handles high-speed packet forwarding with minimal complexity, while the control plane manages the more complex tracing and debugging operations. This segmentation allows the system to achieve high communication reliability without uniformly increasing complexity across all layers.
Solution Approach 2:
The service mesh implements partial tracing and debugging capabilities selectively applied where needed. Rather than full instrumentation of all communication paths, the system applies tracing selectively to critical paths and events, reducing overall system complexity while maintaining sufficient reliability for debugging purposes.
Data Source
AI summary
An apparatus to facilitate telemetry targeted query injection for enhanced debugging in microservices architectures is disclosed. The apparatus includes one or more processors to: identify contextual trace of a previous query recorded in collected data of a service, where microservices of the service responded to the previous query; access an interdependency flow graph representing an architecture and interaction of microservices deployed for a service; retrieve, based on the interdependency flow graph, telemetry data of the microservices corresponding to the contextual trace; identify, based on the telemetry data, an activation profile corresponding to the previous query, the activation profile detailing a response of the microservices to the previous query; compare the activation profile to a correlation profile for the previous query to detect whether an anomaly occurred in the service in response to the previous query; and recommend a modified query based on detection of the anomaly.