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Designing Data-Intensive Applications by Martin Kleppmann Pdf
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
Architecting Data-Driven Systems Book 2 by John Kleppmann Pdf
���� Mastering Data-Driven Systems: A Comprehensive Handbook Unearth the secrets of constructing cutting-edge data-driven systems with this holistic guide tailored for professionals, students, and enthusiasts alike. Here's why this book is the key to unlocking the next era of tech innovation: ���� Solid Foundations: Grasp the essentials with "Foundations of Data-Driven Architectures" and build on a rock-solid base. ���� Design Excellence: Dive deep into "Data Modeling and Design," and its advanced counterpart, setting the blueprint for efficient systems. ���� Next-Gen Storage: Not one, but two comprehensive chapters on modern and advanced storage solutions, ensuring your data is always ready and resilient. ���� Integration Mastery: With a dual focus on "Data Integration and Transformation," understand the magic of merging diverse datasets seamlessly. ���� Analytics Powerhouse: Unlock insights like never before with "Advanced Analytics Frameworks and Engines" and "Real-time Analytics and Stream Processing." ���� AI Synergy: Discover the groundbreaking "Confluence of Data and Artificial Intelligence (AI)," where data meets its most powerful ally. ���� Microservices Edge: Enhance flexibility with "System Scalability with Microservices," making your systems adaptable and agile. ���� Guarding Data: Dive into the intricacies of "Data Governance" with two focused chapters ensuring quality and trust in your data-driven endeavors. ���� Machine Learning Magic: Harness the prowess of "Advanced Machine Learning in Data-Driven Systems" for predictive and actionable insights. ���� All-Encompassing Integration: Unpack the complexities of "Multi-Modal Data Integration in System Design." ���� Reliability & Performance: Ensure your systems are always up, fast, and responsive with chapters on "Scalability" and "Performance Optimization." ���� Safety First: Safeguard your assets with "Advanced Data Security and Compliance." ���� Conclusion: Synthesize your newfound knowledge and gaze into the future of data-driven systems. Embrace the future with this handbook, and elevate your projects, designs, and understanding to newfound heights. ���� Secure your key to the future of data-driven systems! Dive in today. ����
Architecting Enterprise Solutions by Paul Dyson,Andrew Longshaw Pdf
A practical, nuts-and-bolts guide to architectural solutions that describes step-by-step how to design robustness and flexibility into an Internet-based system Based on real-world problems and systems, and illustrated with a running case study Enables software architects and project managers to ensure that nonfunctional requirements are met so that the system won't fall over, that it can be maintained and upgraded without being switched off, and that it can deal with security, scalability, and performance demands Platform and vendor independence will empower architects to challenge product-dictated limitations
System Design Interview - An Insider's Guide by Alex Xu Pdf
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.
Just Enough Software Architecture by George Fairbanks Pdf
This is a practical guide for software developers, and different than other software architecture books. Here's why: It teaches risk-driven architecting. There is no need for meticulous designs when risks are small, nor any excuse for sloppy designs when risks threaten your success. This book describes a way to do just enough architecture. It avoids the one-size-fits-all process tar pit with advice on how to tune your design effort based on the risks you face. It democratizes architecture. This book seeks to make architecture relevant to all software developers. Developers need to understand how to use constraints as guiderails that ensure desired outcomes, and how seemingly small changes can affect a system's properties. It cultivates declarative knowledge. There is a difference between being able to hit a ball and knowing why you are able to hit it, what psychologists refer to as procedural knowledge versus declarative knowledge. This book will make you more aware of what you have been doing and provide names for the concepts. It emphasizes the engineering. This book focuses on the technical parts of software development and what developers do to ensure the system works not job titles or processes. It shows you how to build models and analyze architectures so that you can make principled design tradeoffs. It describes the techniques software designers use to reason about medium to large sized problems and points out where you can learn specialized techniques in more detail. It provides practical advice. Software design decisions influence the architecture and vice versa. The approach in this book embraces drill-down/pop-up behavior by describing models that have various levels of abstraction, from architecture to data structure design.
Cassandra: The Definitive Guide by Jeff Carpenter,Eben Hewitt Pdf
Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition—updated for Cassandra 3.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s non-relational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra on site, in the Cloud, or with Docker Integrate Cassandra with Spark, Hadoop, Elasticsearch, Solr, and Lucene
Designing Distributed Systems by Brendan Burns Pdf
Without established design patterns to guide them, developers have had to build distributed systems from scratch, and most of these systems are very unique indeed. Today, the increasing use of containers has paved the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help make the development of reliable distributed systems far more approachable and efficient. Author Brendan Burns—Director of Engineering at Microsoft Azure—demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. Understand how patterns and reusable components enable the rapid development of reliable distributed systems Use the side-car, adapter, and ambassador patterns to split your application into a group of containers on a single machine Explore loosely coupled multi-node distributed patterns for replication, scaling, and communication between the components Learn distributed system patterns for large-scale batch data processing covering work-queues, event-based processing, and coordinated workflows
Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.
Architecting Data Intensive Applications by Anuj Kumar Pdf
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.
Handbook of Dynamic Data Driven Applications Systems by Frederica Darema,Erik P. Blasch,Sai Ravela,Alex J. Aved Pdf
This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
This book provides full scope of automotive ECU development activities including cybersecurity and safety plus SOTIF. Every computing system has two, and only two attributes: Data Value and Data timing, which represent fully the system functionalities from the system external behavior point of view. The data driven system engineering is the approach to develop the system by focusing on the two attributes mentioned above, in which, the data values are derived by the system operation concept design, and the data timing is derived by the system latency design. Based on which, this book provides a full range of system and software engineering development activities: Requirement Elicitation Requirement Engineering System and Software Architecture Design System Operation Concept Design System and Software Structure Design Electronic Architect Design Functionality Allocation Failure Mode and Effect Analysis (FMEA) Safety Cybersecurity (full compliant with UN ECE 155/156) System and software Verification System and Software Integration and Verification System and Software Black Box Verification each of which has its own clearly defined scope and approach, which is different from the conventional development, in some cases even different from some ISO standards, for example: Safety Development: the safety requirements for every part in a vehicle are cascaded from the vehicle safety requirements, which is different from the Concept Phase in the Part 3 of ISO 26262, and the functional safety development will be fully covered by (1) Reliability (2) Availability (3) Quality. Error Detection and Protection: there are only two types of errors to be detected in a computing system: Data Value error and Data Timing error, to detect which, there are only two aspects to be considered: (1) input data (2) middle data and output data in addition to the platform error detection. The approaches of detection and protection include (1) data transfer protocol check, (2) data range and reasonable value check, (3) execution time check and control. FMEA: this book provides the optimized approach by following the data relationships between the input data, middle data and output data, which will be both inductive and deductive, and re-use the system operation concept that is built at the system development first phase, to make the development efficient. Cybersecurity: this book provides the full solution to cover the UN ECE 155 by implementing three aspects: (1) Trusted contents in the ECU (2) Authenticated access to the ECU (3) Authenticated communication with the ECU. Requirement Engineering: This book makes the goal and scope of requirement engineering in the computing system development specific, accurate and measurable by defining the scope as: the requirement engineering is to use the computer executable information to describe the system under development which consists only two types of information: Signal and Test Case, and defining the requirement quality measurement as: (1) Signals, either input or output signals, shall be computer readable. (2) Test cases shall be executable in the system. System Architecture Design: The goal of system architecture design is to provide the platform that transfers and transforms the input signal to become the required output signal via some middle data. This book introduces the following system functional modulizations based on the AUTOSAR that satisfies a generic automotive ECU structure: (1) Feature Function (2) Diagnostic Service (3) Cybersecurity Function (4) Serial Signal Manager (5) Application Mode Manager (6) AUTOSAR, and based on the characteristics of those functions, the book provides the approach to design the electronic architecture and allocate the functions to the architecture.
Patterns of Enterprise Application Architecture by Martin Fowler Pdf
The practice of enterprise application development has benefited from the emergence of many new enabling technologies. Multi-tiered object-oriented platforms, such as Java and .NET, have become commonplace. These new tools and technologies are capable of building powerful applications, but they are not easily implemented. Common failures in enterprise applications often occur because their developers do not understand the architectural lessons that experienced object developers have learned. Patterns of Enterprise Application Architecture is written in direct response to the stiff challenges that face enterprise application developers. The author, noted object-oriented designer Martin Fowler, noticed that despite changes in technology--from Smalltalk to CORBA to Java to .NET--the same basic design ideas can be adapted and applied to solve common problems. With the help of an expert group of contributors, Martin distills over forty recurring solutions into patterns. The result is an indispensable handbook of solutions that are applicable to any enterprise application platform. This book is actually two books in one. The first section is a short tutorial on developing enterprise applications, which you can read from start to finish to understand the scope of the book's lessons. The next section, the bulk of the book, is a detailed reference to the patterns themselves. Each pattern provides usage and implementation information, as well as detailed code examples in Java or C#. The entire book is also richly illustrated with UML diagrams to further explain the concepts. Armed with this book, you will have the knowledge necessary to make important architectural decisions about building an enterprise application and the proven patterns for use when building them. The topics covered include · Dividing an enterprise application into layers · The major approaches to organizing business logic · An in-depth treatment of mapping between objects and relational databases · Using Model-View-Controller to organize a Web presentation · Handling concurrency for data that spans multiple transactions · Designing distributed object interfaces
Designing Data Reports that Work by Jenny Grant Rankin Pdf
Designing Data Reports that Work provides research-based best practices for constructing effective data systems in schools and for designing reports that are relevant, necessary, and easily understood. Clear and coherent data systems and data reports significantly improve educators’ data use and save educators time and frustration. The strategies in this book will help those responsible for designing education data reports—including school leaders, administrators, and educational technology vendors—to create productive data reports individualized for each school or district. This book breaks down the key concepts in creating and implementing data systems, ensuring that you are a better partner with teachers and staff so they can work with and use data correctly and improve teaching and learning.
Learning Domain-Driven Design by Vlad Khononov Pdf
Building software is harder than ever. As a developer, you not only have to chase ever-changing technological trends but also need to understand the business domains behind the software. This practical book provides you with a set of core patterns, principles, and practices for analyzing business domains, understanding business strategy, and, most importantly, aligning software design with its business needs. Author Vlad Khononov shows you how these practices lead to robust implementation of business logic and help to future-proof software design and architecture. You'll examine the relationship between domain-driven design (DDD) and other methodologies to ensure you make architectural decisions that meet business requirements. You'll also explore the real-life story of implementing DDD in a startup company. With this book, you'll learn how to: Analyze a company's business domain to learn how the system you're building fits its competitive strategy Use DDD's strategic and tactical tools to architect effective software solutions that address business needs Build a shared understanding of the business domains you encounter Decompose a system into bounded contexts Coordinate the work of multiple teams Gradually introduce DDD to brownfield projects
