Cloud monitoring activity involves dynamically tracking the Quality of Service (QoS) parameters related to virtualized resources (e.g., VM, storage, network, appliances, etc.), the physical resources they share, the applications running on them and data hosted on them. Applications and resources configuration in cloud computing environment is quite challenging considering a large number of heterogeneous cloud resources. Further, considering the fact that at each point of time, there will be a different and specific cloud service which may be massively required. Hence, cloud monitoring tools can assist a cloud providers or application developers in: (i) keeping their resources and applications operating at peak efficiency; (ii) detecting variations in resource and application performance; (iii) accounting the Service Level Agreement (SLA) violations of certain QoS parameters; and (iv) tracking the leave and join operations of cloud resources due to failures and other dynamic configuration changes.In this paper, we identify and discuss the major research dimensions and design issues related to engineering cloud monitoring tools. We further discuss how aforementioned research dimensions and design issues are handled by current academic research as well as by commercial monitoring tools.

Data analysis is an important part of the scientific process carried out by domain experts in data-intensive science. Despite the availability of several software tools and systems, their use in combination with each other for conducting complex types of analyses is a very difficult task for non-IT experts. The main contribution of this paper is to introduce an open architectural framework based on service-oriented computing (SOC) principles called the Ad-hoc DAta Grid Environment (ADAGE) framework that can be used to guide the development of domain-specific problem-solving environments or systems to support data analysis activities. Through an application of the ADAGE framework and a prototype implementation that supports the analysis of financial news and market data, this paper demonstrates that systems developed based on the framework allow users to effectively express common analysis processes. This paper also outlines some limitations as well as avenues for future research.

This paper comes back to the problem of coordination of cooperative activities with a Workflow management system. First, we describe the differences that we have noted between business processes and cooperative processes. Then we present a set of requirements for a Workflow management system that aims to support cooperative workflow, and among these requirements are high flexibility and dynamicity. Then we describe how this has been taken into account in the development of the Bonita workflow management system that proposes to remove the idea of process model to work only with process instances that can be derived from each others or that can be composed.