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A self optimized monitoring engine that collects just enough data based on the workload characteristics.

IP.com Disclosure Number: IPCOM000199910D
Publication Date: 2010-Sep-21
Document File: 3 page(s) / 107K

Publishing Venue

The IP.com Prior Art Database

Abstract

Resource Monitoring is a system management activity which is crucial to keep the data processing system healthy. Each resource in the environment provides set of performance statistics, a.k.a sensors, to collect the performance data. When monitoring is enabled, the statistics will be collected at regular intervals and will be persisted for later analysis. Generally, this performance data is used to determine the performance bottlenecks at a resource level.

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A self optimized monitoring engine that collects just enough data based on the workload characteristics.

Solution:

The below graph depicts the general workload patterns observed in a system. The pattern shows that the workload changes quite linearly (or it can be rapidly) and reaches a point where it is constant for long time. The whole concept in the current innovation revolves around this fact.

When workload changes, collect the maximum performance data possible so if there is any

performance repercussions due to workload shift can be analyzed. But once workload remains

constant at one point, the system is stable. Hence, collecting maximum data here is quite expensive and more importantly does not yield any fruitful benefits.

In the proposed solution, a resource monitoring agent(RMA) is defined which is responsible for enabling and controlling the resource level monitoring. Each resource is responsible for organizing its statistics into a)BASIC b)MEDIUM c) HIGH categories. The categorization should be based on the amount of data that is to be collected.

The BASIC level must represent the surface characteristics of a resource such as workload and response time of a resource. The medium and high levels must contain statistics that helps in understanding the internal working of a resource whose details are helpful in performance analysis and debugging. Each resource must also define a policy for RMA to take necessary actions after it analyzes the data available at BASIC level. The policies are always validated against the BASIC data.

BASIC : stddev/variance <0.1

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Workload

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MEDIUM: stddev/variance >0.1 <0.6

HIGH : stddev/variance >0.6 <0.9

When a system is started with monitoring enabled, the RMA will enable monitori...