Lily B. Mummert

Problem Determination in Enterprise Middleware Systems using Change Point Correlation of Time Series Data

Clustered enterprise middleware systems employing dynamic workload scheduling are susceptible to a variety of application malfunctions that can manifest themselves in a counterintuitive fashion and cause debilitating damage. Until now, diagnosing problems in that domain involves investigating log files and configuration settings and requires in-depth knowledge of the middleware architecture and application design. This paper presents a method for problem determination using change point detection techniques and problem signatures consisting of a combination of changes (or absence of changes) in different metrics. We implemented this approach on a clustered middleware system and applied it to the detection of the storm drain condition: a debilitating problem encountered in clustered systems with counterintuitive symptoms. Our experimental results show that the system detects 93% of storm drain faults with no false positives

Using a utility computing framework to develop utility systems

In this paper we describe a utility computing framework, consisting of a component model, a methodology, and a set of tools and common services for building utility computing systems. This framework facilitates the creation of new utility computing systems by providing a set of common functions, as well as a set of standard interfaces for those components that are specialized. It also provides a methodology and tools to assemble and re-use resource provisioning and management functions used to support new services with possibly different requirements. We demonstrate the benefits of the framework by describing two sample systems: a life-science utility computing service designed and implemented using the framework, and an on-line gaming utility computing service designed in compliance with the framework.

Health monitoring and control for application server environments

Web applications have assumed a central role in the enterprise data center, and are becoming the foundation of an increasing number of critical business functions. The availability of such applications is a problem of critical importance. To address this problem, we present a health monitoring and control system for application server environments. We build on past work in the area of measuring system health by evaluating a number of parameters that convey health information. We propose a class-based model that assigns health policies to application servers to monitor health conditions of interest and correct problems before they cause catastrophic damage. We describe an implementation of the system, and provide a utility-based experimental evaluation.

Design and Implementation of a Resource Manager in a Distributed Database System

This paper describes a system called Trends for managing IT resources in a production server environment. The objective of Trends is to reduce operational costs associated with unplanned outages, unbalanced utilization of resources, and inconsistent service delivery. The Trends resource manager balances utilization of multiple resources such as processor and disk space, manages growth to extend resource lifetimes, and factors in variability to improve temporal stability of balancing solutions. The methodology applies to systems in which workload has a strong affinity to databases, files, or applications that can be selectively placed on one or more nodes in a distributed system. Studies in a production environment demonstrate that balancing solutions remain stable for as long as the 9–12 months covered by our data. This work takes place in the context of the Lotus Notes distributed database system, and is based on analysis and data from a production server farm hosting over 20,000 databases.