Niteesh Dubey

Workload characterization of selected JEE-based Web 2.0 applications

Web 2.0 represents the evolution of the web from a source of information to a platform. Network advances have permitted users to migrate from desktop applications to so-called Rich Internet Applications (RIAs) characterized by thin clients, which are browser-based and store their state on managed servers. Other Web 2.0 technologies have enabled users to more easily participate, collaborate, and share in web-based communities. With the emergence of wikis, blogs, and social networking, users are no longer only consumers, they become contributors to the collective knowledge accessible on the web. In another Web 2.0 development, content aggregation is moving from portal-based technologies to more sophisticated so-called mashups where aggregation capabilities are greatly expanded. While Web 2.0 has generated a great deal of interest and discussion, there has not been much work on analyzing these emerging workloads. This paper presents a detailed characterization of several applications that exploit Web 2.0 technologies, running on an IBM Power5 system, with the goal of establishing, whether the server-side workloads generated by Web 2.0 applications are significantly different from traditional web workloads, and whether they present new challenges to underlying systems. In this paper, we present a detailed characterization of three Web 2.0 workloads, and a synthetic benchmark representing commercial workloads that do not exploit Web 2.0, for comparison.

Performance Studies of Commercial Workloads on a Multi-core System

The multi-threaded nature of many commercial applications makes them seemingly a good fit with the increasing number of available multi-core architectures. This paper presents our performance studies of a collection of commercial workloads on a multi-core system that is designed for total throughput. The selected workloads include full operational applications such as SAP-SD and IBM Trade, and popular synthetic benchmarks such as SPECjbb2005, SPEC SDET, Dbench, and Tbench. To evaluate the performance scalability and the thread-placement sensitivity, we monitor the application throughput, processor performance, and the memory subsystem of 8, 16, 24, and 32 hardware threads with (a) increasing number of cores and (b) increasing number of threads per core. We observe that these workloads scale close to linearly (with efficiencies ranging from 86% to 99%) with increasing number of cores. For scaling with hardware-threads per core, the efficiencies are between 50% and 70%. Furthermore, among other observations, our data show that the ability of hiding long latency memory operations (i.e. L2 misses) in a multi-core system enables the performance scaling.

Web applications and dynamic reconfiguration in UNIX servers

In recent years, several large UNIX SMP Servers have added support for dynamic resource management through partitioning and dynamic resource reconfiguration. In this paper we study the ability of Dynamic Reconfiguration (DR) to accommodate fluctuating workloads and changes in operational priorities for a commercial web application. We use a WebSphere HTTP server, a WebSphere Application Server, and a DB2 Database for the application. This combination represents a popular platform for commercial computing deployments, and supports a number of common web-based application scenarios. In our study, we treat this application as a black box to provide a realistic measurement of the efficacy of the DR technology in UNIX Servers. We also use nonparametric estimation techniques to obtain an ab initio and unbiased study of the jitters in our experimental data. Our main conclusions are: (1) Resource allocations for the application (even for a complex and function-rich middleware system such as WebSphere) can be efficiently managed by DR, without the need for explicit accommodation of the DR features by the application, and (2) To obtain efficient resource utilization, the resource management system has to empirically monitor the throughput obtained from the application, rather than rely primarily on long time-scale estimations.

End-to-end performance of commercial applications in the face of changing hardware

This paper investigates the changes in AIX behavior, or the lack of them, and the resulting performance impact from a generational change in servers in a typical large scale eCommerce application environment without extensive tuning of the OS and the application stack for the changing hardware. We have investigated the performance and impediments to performance at the microprocessor level and at the OS level. This paper dissects the performance data as observed from the OS and from hardware performance counters, and suggests areas for further improvements.

Dynamic reconfiguration of CPU and WebSphere on IBM pSeries servers

This paper studies the effects that dynamic reconfiguration (DR) has on a WebSphere workload while CPUs are dynamically added to and removed from the underlying AIX instance. DR is a new technology available in AIX 5.2. This study shows that the resource allocations for a complex and function‐rich middleware system such as WebSphere can be efficiently and dynamically managed by the DR technology, without WebSphere having to explicitly accommodate for the DR features of the operating system. Copyright

AHAFS subsystem for enhancing operating system health in the cloud computing era

Cloud computing is becoming an important paradigm for information technology (IT) infrastructures. A key advantage of cloud computing is its ability to decrease the cost of computing for a variety of applications. For the infrastructure layer, which includes servers and operating systems (OSs), cost reduction is achieved through the consolidation of many OS instances onto a single physical server and through significant improvements in system-administrator productivity. However, these productivity improvements require a scalable easy-to-use OS event-management subsystem so that the higher level software can reliably and effectively automate operations. This paper presents the design and implementation of an OS event-monitoring subsystem called Autonomic Health Advisor FileSystem (AHAFS) that is scalable, has little system-performance overhead, and provides instantaneous event notifications with useful information, for improving the robustness, security, and performance of an OS instance. AHAFS is extensible and can monitor various events for a wide variety of event consumers. AHAFS does not require the use of a new application programming interface (API) but uses the ubiquitous filesystem API; hence, AHAFS is usable by monitoring applications written in any of the languages commonly used for monitoring (e.g., C, C++, Perl®, and Java®) without requiring additional runtime modules or packages.

Whole-Stack Analysis and Optimization of Commercial Workloads on Server Systems

The evolution of the Web as an enabling tool for e-business introduces a challenge to understanding the execution behavior of large-scale middleware systems, such as J2EE [2], and their commercial workloads. This paper presents a brief description of the whole-stack analysis and optimization system – being developed at IBM Research – for commercial workloads on Websphere Application Server (WAS) [5] – IBM’s implementation of J2EE – running on IBM’s pSeries [4] and zSeries [3] server systems.

Automation of Cloud Node Installation for Testing and Scalable Provisioning

Motivated by the lack of automated provisioning and testing tools for physical systems in modern cloud infrastructures, we developed a toolset to automate the installation of a commercial platform virtualization software: the IBM PowerVM NovaLink software. This toolset automates numerous manual installation steps and post-installation tests. The toolset uses Python programs to prepare the target system and to generate installation-configuration files through interaction with a web-interface of the POWER firmware. Expect scripts are used to drive the rest of the installation via interactions through a remote text console. With different scenarios of applying this automation toolset, we demonstrate its use in driving regression testing for the development of the NovaLink installer in a DevOps environment. Furthermore, we discuss its use in provisioning a large number of IBM POWER systems to be ready for cloud management software.