End-Host Flow Agents for Datacenter Performance Diagnosis
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Solution Overview
Problem
Traditional approaches to collecting data in datacenters are inadequate for characterizing performance and diagnosing issues, as they focus on network traffic metrics, which do not account for the complex distributed processing and storage tasks, leading to incomplete and unwieldy data sets that are difficult to analyze.
Innovation Solution
Implementing a system with flow agents at end-hosts that collect and correlate traffic information with job-implementation details, such as hardware resource usage and task properties, to generate more comprehensive and nuanced data sets that reflect datacenter performance and usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional network traffic statistics are collected to measure datacenter performance, then network aspects of performance can be monitored, but the data is incomplete and cannot characterize overall datacenter performance including distributed processing and storage tasks
Solution Approach 1:
The patent segments data collection into multiple specialized agents: flow agents for network traffic, task agents for distributed processing tasks, and resource agents for hardware resources. Each agent collects specific types of data independently, then their data is integrated to form complete performance characterization, resolving the contradiction between data completeness and system complexity
Solution Approach 2:
The patent introduces a datacenter performance monitor as an intermediary component that receives and integrates data from multiple specialized agents. This mediator coordinates the collection efforts, correlates data from different sources, and produces unified performance metrics, enabling complete characterization without requiring each component to handle all complexity
2Measurement precision
If comprehensive data including task classifications and implementation details are collected, then performance characterization improves, but the data set size increases and becomes unwieldy to analyze
Solution Approach 1:
The patent extracts only the most relevant and salient metrics from comprehensive data collections. Instead of collecting and analyzing all possible data, the system identifies key performance indicators specific to datacenter operations (such as task completion rates, resource utilization metrics, and network flow patterns) and extracts these for focused analysis, maintaining precision while reducing data volume
Solution Approach 2:
The patent implements partial data collection by focusing on representative samples and key metrics rather than attempting to collect and analyze every possible data point. The system collects sufficient data to achieve accurate performance characterization without the overwhelming volume that would make analysis unwieldy
3Reliability
If detailed task implementation information is gathered, then diagnostic capability improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent implements feedback mechanisms where collected data is continuously analyzed and used to adjust monitoring focus. The system identifies patterns, anomalies, and correlations in the data, then uses this feedback to prioritize which detailed metrics require further investigation, making diagnosis more reliable while managing analysis difficulty through iterative refinement
Data Source
AI summary
Systems and methods are disclosed for aggregating data capable of diagnosing unique datacenter issues. Traffic statistic collection may be moved from intermediate, datacenter nodes to end hosts providing reports for aggregation and correlation with events at an analytic controller, uncovering implications for such events. To track metrics and/or diagnose datacenter issues not addressed in traffic statistics, information locally available to the end hosts may be combined and/or correlated with traffic statistics. Examples may involve information about: virtual and physical computing resources; a sub-cluster; an application and/or process utilized by a datacenter task; a task/job type; an implementation phase; an initiating user; a task priority; link utilization and/or other traffic statistics relative to the foregoing. Also, for efficiency purposes, the analytic controller may apply a hash to map a virtual to a physical IP address in determining a datacenter path based on topology limited to a physical network, saving computational expense.