In the aerospace industry, it is not unusual for an IT infrastructure, which consists of hundreds of applications, thousands of computers, and massive data storage, to serve only a single program. The quality requirement of services varies from time to time and ensuring the quality of services becomes extremely challenging. The difficulty is compounded if a cutting-edge new technology needs to be integrated with the existing services. From the IT service management standpoint, forecasting changes and adapting to changes are necessary to deliver high quality and cost-effective services. As a quality management system, there are two key elements, processes and techniques. This paper describes a practical experience of managing a large IT services and support. An adaptive service level management approach was used to deliver just-in-time quality services. Techniques, such as the reliability block diagram and scalability weight factor, were used to assist for determining the quality level of a large complex system.

The objective of fault injection is to mimic the existence of faults and to force the exercise of the fault tolerance mechanisms of the target system. To maximize the efficacy of each injection, the locations, timing, and conditions for faults being injected must be carefully chosen. Faults should be injected with a high probability of being accessed. This paper presents two fault injection methodologies-stress-based injection and path-based injection; both are based on resource activity analysis to ensure that injections cause fault tolerance activity and, thus, the resulting exercise of fault tolerance mechanisms. The difference between these two methods is that stress-based injection validates the system dependability by monitoring the run-time workload activity at the system level to select faults that coincide with the locations and times of greatest workload activity, while path-based injection validates the system from the application perspective by using an analysis of the program flow and resource usage at the application program level to select faults during the program execution. These two injection methodologies focus separately on the system and process viewpoints to facilitate the testing of system dependability. Details of these two injection methodologies are discussed in this paper, along with their implementations, experimental results, and advantages and disadvantages.

This paper presents a dependability study of high-speed, switched Local Area Networks (LANs) using Myrinet as an example testbed (with theoretical speeds of 2.56 Gbps). The study uses results of two fault injection methods, simulated fault injection and software-implemented fault injection (SWIFI), to analyze the application-level impact of transient faults injected into the network interface hardware. These results include a number of errors, such as dropped or corrupt messages, host interface or host resets, and local or remote host interface hangs. The paper presents the study in two parts: First, the results from the SWIFI method in the real system are used as a basis to validate the simulation and identify the major factors leading to differences between the methods. A comparison between the two injection methods shows that they agree for 83 percent of the fault injections. The results, however, vary greatly, depending on the fault type considered. The study also presents an analysis of the effects of varying workload intensity, host platform, and interface function targeted by the injection. An example of this analysis is to show that the function targeted has a significant impact on the fault activation rate. Finally, the study identifies two mechanisms by which faults may propagate from the interface to other parts of the network; in one example, this propagation caused the interface's host computer to reboot, while another caused a remote interface in the network to hang.

Because the complexity of today's systems is so high, the changes in technology so fast, and the use of technology so broad, systems are no longer defined and bounded by their physical form, nor by their components. Instead, systems are defined by the characteristics of their use. The traditional performance focus, black-box system testing is no longer adequate to evaluate the capability and dependability of today's complex systems. This paper presents five system test objectives for today's systems, a usage-model approach to determine the system application environments as well as to verify functional aspects of the systems, and a structure testing technique to explore the non-functional aspects of the systems.

Today, enterprises are seeking solutions to integrate their business functions by using advanced computing technologies. Meanwhile, these enterprises are cutting the information centers' budgets to lower the costs. Computer downsizing becomes essential for cost saving. However, computer downsizing also threatens those enterprises whose business success depends heavily on delivering fast, accurate service to customers. System performance is the number one issue followed by the scalability. This paper presents an experimental study conducted on a system that mimicked a production system installed at a customer site. The experiment was designed to focus on the online work-load characterization and the performance evaluation when the use of the system changed along with the projected business growth.>

A measurement-based performability model is described that is based on error and resource-usage data collected on a multiprocessor system. A method for identifying the model structure is introduced, and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal behavior and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, which is based on the service rate and the error rate in each state, is defined in order to estimate the performability of the system and to depict the cost of different types of errors.>

This paper demonstrates a practical approach to the study of the failure behavior of computer systems. Particular attention is devoted to the analysis of permanent failures. A number of important techniques, which may have general applicability in both failure and workload analysis, are brought together in this presentation. These include: smeared averaging of the workload data, clustering of like failures, and joint analysis of workload and failures. Approximately 17 percent of all failures affecting the CPU were estimated to be permanent. The manifestation of a permanent failure was found to be strongly correlated with the level and type of workload prior to the failure. Although, in strict terms, the results only relate to the manifestation of permanent failures and not to their occurrence, there are strong indications that permanent failures are both caused and discovered by increased activity. More measurements and experiments are necessary to determine their respective contributions to the measured workload/failure relationship.