Agentless Latency Detection in Container Clusters
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Solution Overview
Problem
In containerized infrastructures, identifying and addressing latency issues across heterogeneous nodes is challenging due to non-homogeneous conditions, affecting application performance and requiring effective replication and migration strategies without introducing security, scalability, and overhead issues associated with agent-based solutions.
Innovation Solution
An agentless method that monitors network interactions to detect low latency groups by generating an undirected graph based on latency values, using interaction counters and latency monitors, and applies a weighing engine to determine edge weights, allowing for cost-benefit analysis and recommendation of replication strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If agent-based solutions are used to monitor and detect latency in containerized infrastructures, then measurement precision and reliability of latency detection is improved, but device complexity and security risks increase due to the overhead of deploying and managing agents across numerous containers
Solution Approach 1:
The patent extracts the latency monitoring function from individual container agents and consolidates it into a centralized controller that passively observes network traffic. This eliminates the need for complex agent deployment while maintaining detection capabilities through network-level observation of communication patterns between containers.
Solution Approach 2:
The patent introduces a centralized controller as an intermediary that sits between the containers and the monitoring system. This controller passively collects latency data from network traffic without requiring agents inside containers, thereby reducing device complexity while maintaining measurement precision through centralized coordination.
2Reliability
If agent-based solutions are deployed across all containers to monitor latency, then reliability of latency detection is improved, but scalability deteriorates due to the overhead of managing numerous agents
Solution Approach 1:
The centralized controller serves multiple functions simultaneously: it acts as a monitoring point for latency detection, a coordination hub for identifying low-latency groups, and a decision-support system for workload placement. This multi-functionality eliminates the need for separate agent deployments while maintaining detection reliability across scalable container environments.
Solution Approach 2:
The system enables containers to be automatically grouped into low-latency clusters based on passive observation of their network communication patterns. The centralized controller autonomously analyzes traffic data and identifies groups without requiring manual configuration or agent-based reporting, thereby maintaining reliability while achieving scalability.
3Measurement precision
If comprehensive monitoring of all container communications is implemented to accurately identify low latency groups, then measurement precision is improved, but loss of energy and computational overhead increase
Solution Approach 1:
The patent implements partial monitoring by focusing only on the network traffic patterns necessary to identify low-latency groups, rather than comprehensively analyzing all container communications. The centralized controller observes sufficient network metadata to detect latency characteristics and group containers, reducing computational overhead while maintaining measurement precision for the specific purpose of low-latency identification.
Data Source
AI summary
Agentless method to automatically detect low latency groups in containerized infrastructures includes obtaining information about communication across workloads within a cluster of containers implemented by an operating environment. The information identifies multiple pairs of containers. Each pair includes a network source container and a corresponding network destination container. The information includes, for each pair of containers, a corresponding latency associated with a network call between the network source container and the corresponding network destination container. An undirected graph is generated using the obtained information. The undirected graph represents a node-wide latency within the cluster. Using the undirected graph, nodes within the cluster with a latency less than a threshold latency level are grouped. Grouped nodes with latencies less than the threshold latency level are provided.