Cloud Computing

All Indian Reprints of O'Reilly are printed in Grayscale FinOps brings financial accountability to the variable spend model of cloud. Used by the majority of global enterprises, this management practice has grown from a fringe activity to the de facto discipline managing cloud spend. In this book, authors J.R. Storment and Mike Fuller outline the process of building a culture of cloud FinOps by drawing on real-world successes and failures of large-scale cloud spenders.

All Indian Reprints of O'Reilly are printed in Grayscale Learn the essentials of working with Flutter and Dart to build full stack applications that meet the needs of a cloud-driven world. Together, the Flutter open source UI software development kit and the Dart programming language for client development provide a unified solution to building applications capable of targeting multiple platforms. Recipes in this cookbook show you how this potent combination provides an efficient approach to application development. Typically used in frontend development, Flutter helps you develop cross-platform applications for Android, iOS, Linux, Mac, Windows, and the Google Fuchsia operating systems. The Dart SDK provides native access to third-party solutions, including APIs, databases, and authentication. When used in concert with Flutter, Dart allows you to compile source code ahead of time to native code. This cookbook shows you how to: Write effective Dart code by using variables and data structures Build applications with Flutter by exploring widgets and data handling Understand cloud provider solutions and learn how to integrate them with Flutter Manage data through APIs using Google Cloud Serverless Work with Firebase solutions such as Authentication and the Cloud Firestore database Build web applications that also work with mobile and desktop platforms

All Indian Reprints of O'Reilly are printed in Grayscale More organizations than ever understand the importance of data lake architectures for deriving value from their data. Building a robust, scalable, and performant data lake remains a complex proposition, however, with a buffet of tools and options that need to work together to provide a seamless end-to-end pipeline from data to insights. This book provides a concise yet comprehensive overview on the setup, management, and governance of a cloud data lake. Author Rukmani Gopalan, a product management leader and data enthusiast, guides data architects and engineers through the major aspects of working with a cloud data lake, from design considerations and best practices to data format optimizations, performance optimization, cost management, and governance. Learn the benefits of a cloud-based big data strategy for your organization Get guidance and best practices for designing performant and scalable data lakes Examine architecture and design choices, and data governance principles and strategies Build a data strategy that scales as your organizational and business needs increase Implement a scalable data lake in the cloud• Use cloud-based advanced analytics to gain more value from your data

All Indian Reprints of O'Reilly are printed in Grayscale The cloud promises cost savings, agility, and more. But the increasing complexity of modern IT systems often prevents businesses from realizing the outcomes they sought by moving to the cloud in the first place. At the core of this complexity is technical debt. Ad hoc decisions, traditional approaches, and "quick and dirty" solutions add up to fragile, more complex systems (and organizations)--reducing the pace of change, driving up costs, and degrading security. To succeed in the cloud, you first have to manage the problems IT complexity creates. This practical guide will help. If you're tasked with designing, delivering, or approving IT systems that support business growth, this book will teach you the principles and strategies you need to break out of silos, reassess traditional thinking, provide the business a better competitive position, and achieve cloud success across the company. You'll learn: How to assess your current IT environment to identify complexity-centered risks How to structure cross-functional teams to reduce friction points How to create a framework for IT investments that's aligned with your business goals How to measure your outcomes for continued success

All Indian Reprints of O'Reilly are printed in Grayscale Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness. If your data processing or server application has grown beyond what a single computer can handle, this book is for you. You'll explore distributed processing (the pure Python implementation of serverless) and learn how to: Implement stateful applications with Ray actors Build workflow management in Ray Use Ray as a unified system for batch and stream processing Apply advanced data processing with Ray Build microservices with Ray Implement reliable Ray applications

All Indian Reprints of O'Reilly are printed in Grayscale Is Kubernetes ready for stateful workloads? This open-source system has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help. Using Kubernetes as your platform, you'll learn open-source technologies that are designed and built for the cloud. Authors Jeff Carpenter and Patrick McFadin provide case studies to help you explore new use cases and avoid the pitfalls others have faced. You'll get an insider's view of what's coming from innovators who are creating next-generation architectures and infrastructure. With this book, you will: Learn how to use basic Kubernetes resources to compose data infrastructure Automate the deployment and operations of data infrastructure on Kubernetes using tools like Helm and operators Evaluate and select data infrastructure technologies for use in your applications Integrate data infrastructure technologies into your overall stack Explore emerging technologies that will enhance your Kubernetes-based applications in the future

All Indian Reprints of O'Reilly are Printed in Grayscale. This practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics. You'll get a solid understanding of the architecture patterns and services that are offered in Azure and how they might be used in your bioinformatics practice. You'll get code examples that you can reuse for your specific needs. And you'll get plenty of concrete examples to illustrate how a given service is used in a bioinformatics context. You'll also get valuable advice on how to: Use enterprise platform services to easily scale your bioinformatics workloads Organize, query, and analyze genomic data at scale Build a genomics data lake and accompanying data warehouse Use Azure Machine Learning to scale your model training, track model performance, and deploy winning models Orchestrate and automate processing pipelines using Azure Data Factory and Databricks Cloudify your organization's existing bioinformatics pipelines by moving your workflows to Azure high-performance compute services And more

All Indian Reprints of O'Reilly are Printed in Grayscale. With technological advancements, fast markets, and higher complexity of systems, software engineers tend to skip the uncomfortable topic of software efficiency. However, tactical, observability-driven performance optimizations are vital for every product to save money and ensure business success. With this book, any engineer can learn how to approach software efficiency effectively, professionally, and without stress. Author Bart?omiej P?otka provides the tools and knowledge required to make your systems faster and less resource-hungry. Efficient Go guides you in achieving better day-to-day efficiency using Go. In addition, most content is language-agnostic, allowing you to bring small but effective habits to your programming or product management cycles. This book shows you how to: Clarify and negotiate efficiency goals Optimize efficiency on various levels Use common resources like CPU and memory effectively Assess efficiency using observability signals like metrics, logging, tracing, and (continuous) profiling via open source projects like Prometheus, Jaeger, and Parca Apply tools like go test , pprof , benchstat , and k6 to create reliable micro and macro benchmarks Efficiently use Go and its features like slices, generics, goroutines, allocation semantics, garbage collection, and more!

All Indian Reprints of O'Reilly are Printed in Grayscale. If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it's presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world modern applications. This practical guide from Mike X Cohen teaches the core concepts of linear algebra as implemented in Python, including how they're used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, you'll be able to understand, implement, and adapt myriad modern analysis methods and algorithms. Ideal for practitioners and students using computer technology and algorithms, this book introduces you to: The interpretations and applications of vectors and matrices Matrix arithmetic (various multiplications and transformations) Independence, rank, and inverses Important decompositions used in applied linear algebra (including LU and QR) Eigendecomposition and singular value decomposition Applications including least-squares model fitting and principal components analysis

All Indian Reprints of O'Reilly are printed in Grayscale Snowflake's ability to eliminate data silos and run workloads from a single platform creates opportunities to democratize data analytics, allowing users at all levels within an organization to make data-driven decisions. Whether you're an IT professional working in data warehousing or data science, a business analyst or technical manager, or an aspiring data professional wanting to get more hands-on experience with the Snowflake platform, this book is for you.

All Indian Reprints of O'Reilly are printed in Grayscale With the advent of microservices, Kubernetes, public cloud, and hybrid computing, site reliability and DevOps engineers are facing more complexity than ever before. Service mesh is an exciting new technology that promises to help tackle this complexity. A service mesh provides you with a unified control plane to manage application networking across these distinct platforms.

With the rise of the cloud, every aspect of IT has been shaken to its core. The fundamentals for building systems are changing, and although many of the principles that underpin security still ring true, their implementation has become unrecognizable. This practical book provides recipes for AWS, Azure, and GCP to help you enhance the security of your own cloud native systems. Based on his hard-earned experience working with some of the world's biggest enterprises and rapidly iterating startups, consultant Josh Armitage covers the trade-offs that security professionals, developers, and infrastructure gurus need to make when working with different cloud providers. Each recipe discusses these inherent compromises, as well as where clouds have similarities and where they're fundamentally different. • Learn how the cloud provides security superior to what was achievable in an on-premises world • Understand the principles and mental models that enable you to make optimal trade-offs as part of your solution • Learn how to implement existing solutions that are robust and secure, and devise design solutions to new and interesting problems • Deal with security challenges and solutions both horizontally and vertically within your business