Architecting Data Intensive Applications PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Architecting Data Intensive Applications PDF full book. Access full book title Architecting Data Intensive Applications by Anuj Kumar. Download full books in PDF and EPUB format.
Author: Anuj Kumar
Publisher:
ISBN: 9781786465092
Category : Computers
Languages : en
Pages : 340
Get Book
Book Description
Architect and design data-intensive applications and, in the process, learn how to collect, process, store, govern, and expose data for a variety of use cases Key Features Integrate the data-intensive approach into your application architecture Create a robust application layout with effective messaging and data querying architecture Enable smooth data flow and make the data of your application intensive and fast Book Description Are you an architect or a developer who looks at your own applications gingerly while browsing through Facebook and applauding it silently for its data-intensive, yet fluent and efficient, behaviour? This book is your gateway to build smart data-intensive systems by incorporating the core data-intensive architectural principles, patterns, and techniques directly into your application architecture. This book starts by taking you through the primary design challenges involved with architecting data-intensive applications. You will learn how to implement data curation and data dissemination, depending on the volume of your data. You will then implement your application architecture one step at a time. You will get to grips with implementing the correct message delivery protocols and creating a data layer that doesn't fail when running high traffic. This book will show you how you can divide your application into layers, each of which adheres to the single responsibility principle. By the end of this book, you will learn to streamline your thoughts and make the right choice in terms of technologies and architectural principles based on the problem at hand. What you will learn Understand how to envision a data-intensive system Identify and compare the non-functional requirements of a data collection component Understand patterns involving data processing, as well as technologies that help to speed up the development of data processing systems Understand how to implement Data Governance policies at design time using various Open Source Tools Recognize the anti-patterns to avoid while designing a data store for applications Understand the different data dissemination technologies available to query the data in an efficient manner Implement a simple data governance policy that can be extended using Apache Falcon Who this book is for This book is for developers and data architects who have to code, test, deploy, and/or maintain large-scale, high data volume applications. It is also useful for system architects who need to understand various non-functional aspects revolving around Data Intensive Systems.
Author: Anuj Kumar
Publisher:
ISBN: 9781786465092
Category : Computers
Languages : en
Pages : 340
Get Book
Book Description
Architect and design data-intensive applications and, in the process, learn how to collect, process, store, govern, and expose data for a variety of use cases Key Features Integrate the data-intensive approach into your application architecture Create a robust application layout with effective messaging and data querying architecture Enable smooth data flow and make the data of your application intensive and fast Book Description Are you an architect or a developer who looks at your own applications gingerly while browsing through Facebook and applauding it silently for its data-intensive, yet fluent and efficient, behaviour? This book is your gateway to build smart data-intensive systems by incorporating the core data-intensive architectural principles, patterns, and techniques directly into your application architecture. This book starts by taking you through the primary design challenges involved with architecting data-intensive applications. You will learn how to implement data curation and data dissemination, depending on the volume of your data. You will then implement your application architecture one step at a time. You will get to grips with implementing the correct message delivery protocols and creating a data layer that doesn't fail when running high traffic. This book will show you how you can divide your application into layers, each of which adheres to the single responsibility principle. By the end of this book, you will learn to streamline your thoughts and make the right choice in terms of technologies and architectural principles based on the problem at hand. What you will learn Understand how to envision a data-intensive system Identify and compare the non-functional requirements of a data collection component Understand patterns involving data processing, as well as technologies that help to speed up the development of data processing systems Understand how to implement Data Governance policies at design time using various Open Source Tools Recognize the anti-patterns to avoid while designing a data store for applications Understand the different data dissemination technologies available to query the data in an efficient manner Implement a simple data governance policy that can be extended using Apache Falcon Who this book is for This book is for developers and data architects who have to code, test, deploy, and/or maintain large-scale, high data volume applications. It is also useful for system architects who need to understand various non-functional aspects revolving around Data Intensive Systems.
Author: Martin Kleppmann
Publisher: "O'Reilly Media, Inc."
ISBN: 1491903104
Category : Computers
Languages : en
Pages : 658
Get Book
Book Description
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Author: Artur Ejsmont
Publisher: McGraw Hill Professional
ISBN: 0071843663
Category : Computers
Languages : en
Pages : 432
Get Book
Book Description
This invaluable roadmap for startup engineers reveals how to successfully handle web application scalability challenges to meet increasing product and traffic demands. Web Scalability for Startup Engineers shows engineers working at startups and small companies how to plan and implement a comprehensive scalability strategy. It presents broad and holistic view of infrastructure and architecture of a scalable web application. Successful startups often face the challenge of scalability, and the core concepts driving a scalable architecture are language and platform agnostic. The book covers scalability of HTTP-based systems (websites, REST APIs, SaaS, and mobile application backends), starting with a high-level perspective before taking a deep dive into common challenges and issues. This approach builds a holistic view of the problem, helping you see the big picture, and then introduces different technologies and best practices for solving the problem at hand. The book is enriched with the author's real-world experience and expert advice, saving you precious time and effort by learning from others' mistakes and successes. Language-agnostic approach addresses universally challenging concepts in Web development/scalability—does not require knowledge of a particular language Fills the gap for engineers in startups and smaller companies who have limited means for getting to the next level in terms of accomplishing scalability Strategies presented help to decrease time to market and increase the efficiency of web applications
Author: Stefano Ceri
Publisher: Morgan Kaufmann
ISBN: 9781558608436
Category : Computers
Languages : en
Pages : 596
Get Book
Book Description
This text represents a breakthrough in the process underlying the design of the increasingly common and important data-driven Web applications.
Author: Ted Malaska
Publisher: "O'Reilly Media, Inc."
ISBN: 1492038695
Category : Computers
Languages : en
Pages : 190
Get Book
Book Description
While many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects. Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project. Start the planning process by considering the key data project types Use guidelines to evaluate and select data management solutions Reduce risk related to technology, your team, and vague requirements Explore system interface design using APIs, REST, and pub/sub systems Choose the right distributed storage system for your big data system Plan and implement metadata collections for your data architecture Use data pipelines to ensure data integrity from source to final storage Evaluate the attributes of various engines for processing the data you collect
Author: Alex Xu
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 280
Get Book
Book Description
The system design interview is considered to be the most complex and most difficult technical job interview by many. Those questions are intimidating, but don't worry. It's just that nobody has taken the time to prepare you systematically. We take the time. We go slow. We draw lots of diagrams and use lots of examples. You'll learn step-by-step, one question at a time.Don't miss out.What's inside?- An insider's take on what interviewers really look for and why.- A 4-step framework for solving any system design interview question.- 16 real system design interview questions with detailed solutions.- 188 diagrams to visually explain how different systems work.
Author: Martin Kleppmann
Publisher: "O'Reilly Media, Inc."
ISBN: 1491903112
Category : Computers
Languages : en
Pages : 614
Get Book
Book Description
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Author: Stefano Ceri
Publisher: Elsevier
ISBN: 9780080503936
Category : Computers
Languages : en
Pages : 562
Get Book
Book Description
The most prominent Web applications in use today are data-intensive. Scores of database management systems across the Internet access and maintain large amounts of structured data for e-commerce, on-line trading, banking, digital libraries, and other high-volume sites. Developing and maintaining these data-intensive applications is an especially complex, multi-disciplinary activity, requiring all the tools and techniques that software engineering can provide. This book represents a breakthrough for Web application developers. Using hundreds of illustrations and an elegant intuitive modeling language, the authors—all internationally-known database researchers—present a methodology that fully exploits the conceptual modeling approach of software engineering, from idea to application. Readers will learn not only how to harness the design technologies of relational databases for use on the Web, but also how to transform their conceptual designs of data-intensive Web applications into effective software components. * A fully self-contained introduction and practitioner's guide suitable for both technical and non-technical members of staff, as well as students. * A methodology, development process, and notation (WebML) based on common practice but optimized for the unique challenges of high-volume Web applications. * Completely platform- and product-independent; even the use of WebML is optional. * Based on well-known industry standards such as UML and the Entity Relationship Model. * Enhanced by its own Web site (http://www.webml.org), containing additional examples, papers, teaching materials, developers' resources, and exercises with solutions.
Author: Rob Botwright
Publisher: Rob Botwright
ISBN: 1839387033
Category : Computers
Languages : en
Pages : 221
Get Book
Book Description
📚 Introducing the Ultimate Application Design Book Bundle! 🚀 Are you ready to take your application design skills to the next level? Dive into the world of data-intensive app systems with our comprehensive book bundle, "Application Design: Key Principles for Data-Intensive App Systems." 🌐💡 📘 Book 1 - Foundations of Application Design: Lay the groundwork for success with an introduction to key principles for data-intensive systems. From data modeling basics to architecture patterns, this volume sets the stage for mastering application design. 📘 Book 2 - Mastering Data-Intensive App Architecture: Elevate your skills with advanced techniques and best practices for architecting data-intensive applications. Explore distributed systems, microservices, and optimization strategies to build scalable and resilient systems. 📘 Book 3 - Scaling Applications: Learn essential strategies and tactics for handling data-intensive workloads. Discover performance optimization techniques, cloud computing, and containerization to scale your applications effectively. 📘 Book 4 - Expert Insights in Application Design: Gain valuable insights from industry experts and thought leaders. Explore cutting-edge approaches and innovations shaping the future of data-intensive application development. With a combined wealth of knowledge, these four books provide everything you need to succeed in the fast-paced world of application design. Whether you're a seasoned professional or just starting your journey, this bundle is your roadmap to success. 🛣️💼 🚀 Don't miss out on this opportunity to master application design and unlock new possibilities in your career. Get your hands on the "Application Design: Key Principles for Data-Intensive App Systems" book bundle today! 🌟📈
Author: Supun Kamburugamuve
Publisher: John Wiley & Sons
ISBN: 1119713013
Category : Computers
Languages : en
Pages : 416
Get Book
Book Description
PEEK “UNDER THE HOOD” OF BIG DATA ANALYTICS The world of big data analytics grows ever more complex. And while many people can work superficially with specific frameworks, far fewer understand the fundamental principles of large-scale, distributed data processing systems and how they operate. In Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood, renowned big-data experts and computer scientists Drs. Supun Kamburugamuve and Saliya Ekanayake deliver a practical guide to applying the principles of big data to software development for optimal performance. The authors discuss foundational components of large-scale data systems and walk readers through the major software design decisions that define performance, application type, and usability. You???ll learn how to recognize problems in your applications resulting in performance and distributed operation issues, diagnose them, and effectively eliminate them by relying on the bedrock big data principles explained within. Moving beyond individual frameworks and APIs for data processing, this book unlocks the theoretical ideas that operate under the hood of every big data processing system. Ideal for data scientists, data architects, dev-ops engineers, and developers, Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood shows readers how to: Identify the foundations of large-scale, distributed data processing systems Make major software design decisions that optimize performance Diagnose performance problems and distributed operation issues Understand state-of-the-art research in big data Explain and use the major big data frameworks and understand what underpins them Use big data analytics in the real world to solve practical problems
