An operational reliability and service assurance framework for enterprise IT systems supporting large user populations

Ensuring the availability of enterprise IT systems is a challenging task. The factors that can bring systems down are numerous, and their impact on various system architectures is difficult to predict. At the same time, maintaining high availability is crucial in many applications, ranging from control systems in the electric power grid, over electronic trading systems on the stock market to specialized command and control systems for military and civilian purposes. This paper describes a Bayesian decision support model, designed to help enterprise IT system decision-makers evaluate the consequences of their decisions by analyzing various scenarios. The model is based on expert elicitation from 50 experts on IT systems availability, obtained through an electronic survey. The Bayesian model uses a leaky Noisy-OR method to weigh together the expert opinions on 16 factors affecting systems availability. Using this model, the effect of changes to a system can be estimated beforehand, providing decision support for improvement of enterprise IT systems availability. The Bayesian model thus obtained is then integrated within a standard, reliability block diagram-style, mathematical model for assessing availability on the architecture level. In this model, the IT systems play the role of building blocks. The overall assessment framework thus addresses measures to ensure high availability both on the level of individual systems and on the level of the entire enterprise architecture. Examples are presented to illustrate how the framework can be used by practitioners aiming to ensure high availability.

Economic mega-shifts and technology advances have created an entirely new context for the enterprise IT systems. It is now a very common expectation that the cost/performance ratios will be constantly improving while always offering better services and novel IT features. To fit such expectations, enterprise IT systems should be architected differently. In general, cost savings should be used to finance innovative projects fitting into enterprise architecting blueprints. In this paper we give a top-level view into typical enterprise IT system and outline four architecting principles to guide the implementation of these innovative projects articulated together as 'renewal program' across entire IT. After describing in more depth each principle, we conclude with some practical challenges and outline a few interesting research directions. We also share some practical insights from an internal HP project.

The fragility created by hierarchical organizational constructs crosses over into the design of many large scale IT systems that are distributed across an enterprise. This means, that for these systems, end-to-end system design comes from the top down, creating a situation in which all fragility rises up to the largest scales of the system; this is a result of these systems being centrally controlled, often at the top of a hierarchy. In order for enterprise systems such as these to augment or repair themselves, they must undergo a catastrophic, enterprise-wide failure and be reengineered, once again by top-down direction [1]. This is the opposite of resilient system design and represents a situation where federal IT can be very inefficient. The current climate in the US of proactive and aggressive infrastructure consolidation via the Federal Data Center Consolidation Initiative (FDCCI) and the National Defense Authorization Act (NDAA) only serves to further incentivize system designers to construct extremely fragile systems at both the application and infrastructure layers. This fragility puts these systems at greater risk for enterprise failure. An example of a critical federal enterprise IT system's design and resulting fragility when perturbed (i.e., via consolidation and modernization) will be examined in this paper. Engineering guidelines from a complex systems perspective will be recommended to counter this resulting fragility. These guidelines will be from both an IT and government policy point of view and are generalized for applicability to systems engineering outside the scope of just IT systems.

The last decade has seen several changes in the structure and emphasis of enterprise IT systems. Specific infrastructure trends have included the emergence of large consolidated data centers, the adoption of virtualization and modularization, and an increased commoditization of hardware. At the application level, both the workload mix and usage patterns have evolved to an increased emphasis on service-centric computing and SLA-driven performance tuning. These, often dramatic, changes in the enterprise IT landscape motivate equivalent changes in the emphasis of architecture research. In this paper, we summarize some recent trends in enterprise IT systems and discuss the implications for architecture research, suggesting some high-level challenges and open questions for the community to address.

The development of enterprise IT architectures has become a real challenge in the recent years. Most of the issues stem from heterogeneous applications, platforms and environments that need to operate as a homogeneous unit. It is for this reason that the enterprise IT systems of today are increasingly driven to integrate all of their current and future components. The additional motivation for integration is also a need for narrowing the gap between the IT and the business world of today's enterprises, in order to increase competitiveness. This article provides an introduction to enterprise IT systems integration and gives a summary of methodologies most in use today.

Enterprise computing faces major challenges such as ever-increasing size and complexity and escalating costs of administering mission-critical IT systems, numerous human-caused failures and outages of IT systems, lack of sufficient supply of trained system administrators, and major obstacles in dealing with changes throughout the software system life cycle. Thus, it is practically impossible to rely on human intervention and administration for development, integration, deployment, and management of enterprise IT systems in mission critical applications. This has led to the development of autonomic computing that is derived from human body's self-regulatory nervous system. Autonomic computing is an emerging trend for building nextgeneration enterprise IT systems. Autonomic systems are envisioned to be self-aware and able to selfmanage. The focus of our research is to develop multi-agent autonomic architectures. The application domains range from telehealth and telemedicine to quality management and space exploration. This paper presents our multi-agent autonomic architecture design.

As more enterprises buy information technology services, studying their underpinning contracts becomes more important. With cloud computing and outsourcing, these service level agreements (SLAs) are now often the only link between the business and the supporting IT services. This paper presents an experimental economics investigation of decision-making with regard to availability SLAs, among enterprise IT professionals. The method and the ecologically valid subjects make the study unique to date among IT service SLA studies. The experiment consisted of pairwise choices under uncertainty, and subjects ( $N=46$ ) were incentivized by payments based on one of their choices, randomly selected. The research question investigated in this paper is: Do enterprise IT professionals maximize expected value when procuring availability SLAs, as would be optimal from the business point of view? The main result is that enterprise IT professionals fail to maximize expected value. Whereas some subjects do maximize expected value, others are risk-seeking, risk-averse, or exhibit nonmonotonic preferences. The nonmonotonic behavior in particular is an interesting observation, which has no obvious explanation in the literature. For a subset of the subjects ( $N=29$ ), a few further hypotheses related to associations between general attitude to risk or professional experience on the one hand, and behavior in SLAs on the other hand, were investigated. No support for these associations was found. The results should be interpreted with caution, due to the limited number of subjects. However, given the prominence of SLAs in modern IT service management, the results are interesting and call for further research, as they indicate that current professional decision-making regarding SLAs can be improved. In particular, if general attitude to risk and professional experience do not impact decision-making with regard to SLAs, more extensive use of decision-support systems might be called for in order to facilitate proper risk management.

Effective monitoring solutions are critical to the smooth running of enterprise systems. However, real-world constraints present several challenges in designing such solutions. With the increasing scale and complexity of today's enterprise IT systems and their increasing use for business-critical applications, traditional approaches to monitoring must be reconsidered. This article stresses the need for a paradigm-shift from manual intuition-led approaches to an automated analytics-driven approach to monitor the IT systems. The authors propose that analytics-led solutions can provide powerful levers to design monitoring and event management solutions for next-generation enterprise IT systems.

Management operates at different levels and so it is possible to apply management information systems at these varied levels. Basic examples of management information systems are human resources management systems, financial management information systems and marketing management information systems. Enterprise IT Systems Enterprise IT systems are technologies designed to integrate and manage entire business processes for large organisations. Typically, enterprise application software is hosted on large servers over a computer network. Transmission of information can either be internal or external. Examples of enterprise information systems may be accounting software, health care specific software or electronic data Interchange (EDI). Another example of software within this category is CRM (Customer relationship management software). Information technology plays various roles in business, and provides a huge range of capabilities that enhance management performance. It is therefore important to understand the four major categories of IT systems and their functions in a business environment.

About Our Authors

Colleges and universities have become data-rich, multifaceted enterprises that are heavily dependent on large-scale information technology systems to support teaching, research, administration, and student services. With the growth of academic services and the reach of universities' commercial activities, institutional agility, data governance and service quality are increasingly constrained by legacy and fractured IT systems. This article explores the concept of digital transformation as an enterprise-wide strategic imperative for higher education, rather than a mere roll of random technology upgrades. It stresses the need to implement a unified change across the academic and administrative spheres by adopting the principles of enterprise architecture alignment, platform modernization, and integration-first design. Special focus is placed on the role of modern enterprise platforms that enable standardization, interoperability, and mechanization of institutional systems. Also, the article discusses the increased practicality of new technologies, such as data transformation and migration assisted by artificial intelligence, for solving longstanding problems in data quality, system interoperability, and the preservation of institutional knowledge. Drawing on experience with large-scale applications at research universities, this work offers scalable strategies that can be applied to higher education institutions, tailored to their specific governance structures and operational needs. The results are relevant to the emerging literature on higher education digital transformation, as they provide practical insights that connect theory and practice. Finally, the article also positions enterprise digital transformation as a continuous organizational strength that builds institutional resilience, improves the user experience, and supports innovation in teaching, research, and administration in the increasingly competitive and regulated higher-education sector.

In future, the so called “sensing enterprise”, as part of the Future Internet, will play a crucial role in the success or the failure of an enterprise. We present our vision of an enterprise interacting with the physical world based on a retail scenario. One of the main challenges is the interoperability not only between the enterprise IT systems themselves, but also between these systems and the sensing devices. We will argue that semantically enriched service descriptions, the so called linked services will ease interoperability between two or more enterprises IT systems, and between enterprise systems and the physical environment.

The proliferation of commodity based big data platforms and an exponential increase in the research in machine learning techniques lead to a change in application development paradigm from traditional control-flow Software 1.0 to data-flow Software 2.0 programming paradigm e.g. use of machine learning based models over customer-scoring methods for generating recommendations. The Software 2.0 paradigm is a data-driven programming that requires specialized data management to get clean, governed and unbiased data sets, well defined neural network architectures for building a model, efficient model training, extensive testing and high performance deployment. Unlike Software 1.0 paradigm, a Software 2.0 program's output is probabilistic in nature as the correctness is highly dependent on the size and quality of the input data, however the program's performance is deterministic. This has led to the research in specialized hardware and high performance architectures for deep-learning algorithms. Also, the nature of Software 2.0 paradigm brings in heterogeneity in the whole life cycle starting from an application development until its deployment in the production environment and hence posing numerous architecture and performance challenges.In this paper, we outline the research problems that will emerge due to migration of apart of Software 1.0 to Software 2.0. We present the challenges and the approaches to address them, for accelerating the development and deployment of Software 2.0 programs. We also envision evolution of existing enterprise IT systems to the data-driven enterprise IT systems, referred to as EIT 2.0. We have compared a conventional development life-cycle of applications with that in EIT 2.0. We address research problems and approaches with the related state-of-art in the performance engineering of modern enterprise applications during its life cycle in EIT 2.0.

ISO's process to adopt the IEEE 1471 standard on architecture descriptions has revealed of the order of 130 standards concerning or relating to architectures and architecting. Within the “enterprise architecture” theme alone, different people use the term to refer to mean quite different things: the “architecture of the enterprise as a system”; the enterprise context for the enterprise IT system; or the architecture of the enterprise IT system itself. A focus on tools and methods has led to confusion between the creative activity of “architecting”, by which I mean making or exposing the key strategic decisions about the purpose, organisation, behaviour and critical design features of the system, and the analytical and descriptive activity of architecture modelling, which supports and captures the results of architecting. The INCOSE UK Architecture Working Group established a “belief systems” methodology to explore and seek to reconcile the many conflicting views on architecting This paper expands on the views presented by the author at the IS08 Architecture panel session in an effort to identify and communicate a better understanding of the fundamental skills, principles, philosophy and approach underpinning effective systems architecting. It seeks to improve their integration by focusing on “purpose, context and process” of architecting with the perspective that “hard systems exist inside soft systems”, and to show that “lean pull” allows architecting to focus on the intended use of its products rather than adherence to process standard or frameworks.

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.