Manage, control, and optimize the cloud spend on AWS. Key Features * Learn best practices in implementing a Cloud FinOps discipline with AWS * Set up your organization for success by enabling people, process, and organization * Choose the right pricing model strategy to optimize usage of AWS resources Book Description Much like how DevOps is a combination of cultural philosophies, practices, and tools that advocate a collaborative working relationship between development and IT operations, FinOps encourages the same collaboration between technology and finance teams. Organizations with a mature FinOps practice decentralize cost ownership to developer teams, and encourage cross-functional collaboration between business, finance, and technology enabling speed, innovation, and business growth. You'll learn how to structure your organization to form the right FinOps team including a Cloud Center of Excellence. You'll learn how to implement practical cost savings measures with AWS tools and processes to optimize cost in both the short- and long-term. By the end of this book, you'll have the basis to implement a successful Cloud FinOps practice for your organization to get the best value of the AWS cloud for your workloads. What you will learn * Use AWS services to monitor and govern your cost usage and spend. * Implement automation to streamline cost optimization operations. * Design the best architecture to fit your workload to optimize on data transfer. * Maximize efficiency with elasticity strategies to optimize on costs. * Leverage cost optimization levers to save on compute and storage costs. * Identify strategies to create and govern the right cost metrics to bring value to your organization. Who This Book Is For This book is for enterprise architects, cloud architects, CFOs, CTOs, product managers, finance managers, and FinOps practitioners looking to optimize their use of the cloud. This book reveals tools, strategies, and frameworks to minimize costs that will allow your business to realize sustainable financial benefits and to efficiently use cloud resources.

Quantitative risk assessments cannot eliminate risk, nor can they resolve trade-offs. They can, however, guide principled risk management and reduction - if the quality of assessment is high and decision makers understand how to use it. This book builds a unifying scientific framework for discussing and evaluating the quality of risk assessments and whether they are fit for purpose. Uncertainty is a central topic. In practice, uncertainties about inputs are rarely reflected in assessments, with the result that many safety measures are considered unjustified. Other topics include the meaning of a probability, the use of probability models, the use of Bayesian ideas and techniques, and the use of risk assessment in a practical decision-making context. Written for professionals, as well as graduate students and researchers, the book assumes basic probability, statistics and risk assessment methods. Examples make concepts concrete, and three extended case studies show the scientific framework in action.

The Asian financial landscape has become more interconnected over the past 2 decades. Previous financial crises have proven how volatility can transmit rapidly across an interconnected financial network. Moreover, empirical analyses have shown how it can reverberate across the macroeconomy. With a summary of lessons from past financial crises, this report also analyzes the impact of deeper financial integration on economic vulnerability.

Risk analysis is not a narrowly defined set of applications. Rather, it is widely used to assess and manage a plethora of hazards that threaten dire implications. However, too few people actually understand what risk analysis can help us accomplish and, even among experts, knowledge is often limited to one or two applications. Explaining Risk Analysis frames risk analysis as a holistic planning process aimed at making better risk-informed decisions and emphasizing the connections between the parts. This framework requires an understanding of basic terms, including explanations of why there is no universal agreement about what risk means, much less risk assessment, risk management and risk analysis. Drawing on a wide range of case studies, the book illustrates the ways in which risk analysis can help lead to better decisions in a variety of scenarios, including the destruction of chemical weapons, management of nuclear waste and the response to passenger rail threats. The book demonstrates how the risk analysis process and the data, models and processes used in risk analysis will clarify, rather than obfuscate, decision-makers' options. This book will be of great interest to students and scholars of risk assessment, risk management, public health, environmental science, environmental economics and environmental psychology.

Actuaries have access to a wealth of individual data in pension and insurance portfolios, but rarely use its full potential. This book will pave the way, from methods using aggregate counts to modern developments in survival analysis. Based on the fundamental concept of the hazard rate, Part I shows how and why to build statistical models, based on data at the level of the individual persons in a pension scheme or life insurance portfolio. Extensive use is made of the R statistics package. Smooth models, including regression and spline models in one and two dimensions, are covered in depth in Part II. Finally, Part III uses multiple-state models to extend survival models beyond the simple life/death setting, and includes a brief introduction to the modern counting process approach. Practising actuaries will find this book indispensable, and students will find it helpful when preparing for their professional examinations.