Risk and Governance Considerations in Cloud Era

Cloud Computing (CC) has recently emerged as a compelling paradigm for managing and delivering computing services over the internet. It is rapidly changing the landscape of technology and ultimately turning the long-held promise of utility computing into a reality. Nevertheless, jumping into the cloud is never a trivial task. A special approach is required to discover and mitigate risks, also to apply controls related to the cloud jump. The main objective of this chapter is to specify some of the phenomena associated with the CC paradigm and associated business transformation. It looks at the motivations, contracting, obstacles and the agile project rollout methodologies. It then provides an in-depth analysis for the allied risks and governance directions. CC governance is being more crucial as the CC paradigm is still evolving. In this context, this chapter build few bricks toward a full Cloud Computing Risk and Governance Framework (CCRGF).

Virtual Machine Placement in IaaS Cloud

A crucial component of providing services over virtual machines to users is how the provider places those virtual machines on physical servers. While one strategy can offer an increased performance for the virtual machine, and hence customer satisfaction, another can offer increased savings for the cloud operator. Both have their trade-offs. Also, with increasing costs of electricity, and given the fact that the major component of the operational cost of a data center is that of powering it, green strategies also offer an attractive alternative. In this chapter, the authors will look into what kind of different placement strategies have been developed, and the kind of advantages they purport to offer.

Industrial Patterns on Cloud

Cloud Computing is rapidly gaining traction today as the preferred platform for deploying both development and production workloads. Every industry has started adopting hybrid hosting models to leverage benefits that accrue from a convergence of technologies; Cloud is being used as a flexible springboard to mount a defense against disruptive digital trends. The use cases and associated gains are industry specific, ranging from leveraging auto-scaling to assuage seasonal spikes in Retail, and creating software-defined network functions in Telecom, to aggregating and analyzing sensor data in Automotive, and deploying multi-site disaster recovery in Government. In this chapter, we will embark on an expedition spanning ten industries, searching for patterns where Cloud enables advantageous solutions to business-specific categories of use cases. The observations are based on actual case studies chosen from hundreds of real Cloud deals across industries.

Cost of Using Cloud Computing

With the recent advancement in computing technologies, business and research applications are not only executed in the traditional systems such as enterprise systems and supercomputers (HPC systems) but also in the cloud. The traditional HPC systems are expensive and sometimes require huge start-up investment, technical and administrative support and job queuing. With the benefits of cloud computing, cloud services such as Infrastructure as a Service (IaaS) and Hardware as a Service (HaaS), enables business, scientists and researchers to run their business and HPC applications in the cloud without upfront investment associated with the traditional infrastructures. Therefore, in this paper we analyze the computational performance and dollar cost of running HPC applications in the cloud when IaaS or HaaS is leased. We find that HaaS significantly reduces the cost of running HPC application in the cloud by 20% compare to IaaS without significant impact to application's performance. We also found that there is a substantial improvement in computational performance in HaaS compare to IaaS.

Design and Implementation of Service Management in DevOps Enabled Cloud Computing Models

This chapter examines the importance of including value-add service management practices early in the Continuous Integration/Continuous Delivery (CI/CD) pipeline. The authors will also address the importance of establishing a balance between the development and delivery of features with the development and delivery of practices that support overall infrastructure and service management capabilities. Without fully encompassing all of these practices, the DevOps benefits of reducing time-to-market for a set of features can be negated by a potential increase in security exposures as well as overall quality issues. Within this chapter, several key service management practices are identified as well as the importance of fully incorporating those practices into a DevOps adoption.

Establishing Governance for Hybrid Cloud and the Internet of Things

This chapter is focused on the current and future state of operating a Hybrid Cloud or Internet of Things (IoT) environment. This includes tools, data, and processes which allow an organization to use these assets to serve business goals. Examining governance in this context shows how it works today and how it should change, using some real-world examples to show the impacts and advantages of these changes. It is a high level overview of those important topics with prescriptive detail left for a future and follow-on analysis. Finally, all of the lessons learned, when combined together form a governance fabric, resulting in a set of techniques and actions which tie together into a supporting framework and set of processes. The important questions include: Why does governance matter in the deployment and operation of Hybrid Cloud and IoT? If governance already exists how must it change? What are the important and salient characteristics of governance which need special focus? Thus, this analysis gives a context of how today's governance approach should change when moving to a Hybrid Cloud or IoT model.

Workload Migration to Cloud

Workload migration to cloud is a critical area in increasing the adoption of cloud. In order to fully leverage the power of cloud computing, clients need to determine what workloads and applications are good candidates in the cloud and migrate them quickly and in an efficient manner into the cloud. The main goal of this chapter is to explore and study how workloads can be migrated into cloud. In addition, this chapter will also describe the overall end-to-end process for cloud migration and its resulting benefits.

Transition and Transformation into a Cloud Environment

It is a challenge to migrate and transform existing workloads into the cloud, especially those requiring the higher standardization of managed services. Covered here are the various types of transition and transformation into the cloud from lift and shift to automated migration; the tooling and automation for the cloud environment; and the migration services via wave planning and check-pointing to the cloud for customers. Transition and Transformation is an integral part of cloud services, and creating a repeatable, reusable, factory model for a customer ensures a successful cloud migration.

Cloud Build Methodology

The cloud build methodology chapter provides an introduction to the build methods for hybrid clouds. It does this by first introducing the concept of a hybrid cloud and the different types of services provides by clouds. It then overviews the components of hybrid clouds and how these components get incorporated into the design. It takes a brief look at the cost drivers with building a cloud to provide background with design decisions to be made. With the background on the design, it takes the reader through the build of a hybrid cloud and how automation can be used to reduce the cost. Lastly, it takes a brief look at a possible direction of cloud builds.

A Survey and Taxonomy of Energy Efficient Resource Management Techniques in Platform as a Service Cloud

The numerous advantages of cloud computing environments, including scalability, high availability, and cost effectiveness have encouraged service providers to adopt the available cloud models to offer solutions. This rise in cloud adoption, in return encourages platform providers to increase the underlying capacity of their data centers so that they can accommodate the increasing demand of new customers. Increasing the capacity and building large-scale data centers has caused a drastic growth in energy consumption of cloud environments. The energy consumption not only affects the Total Cost of Ownership but also increases the environmental footprint of data centers as CO2 emissions increases. Hence, energy and power efficiency of the data centers has become an important research area in distributed systems. In order to identify the challenges in this domain, this chapter surveys and classifies the energy efficient resource management techniques specifically focused on the PaaS cloud service models.