Having appropriate storage for hosting business-critical data and advanced Security Information and Event Management (SIEM) software for deep inspection, detection, and prioritization of threats has become a necessity for any business. This IBM® Redpaper publication explains how the storage features of IBM Spectrum® Scale, when combined with the log analysis, deep inspection, and detection of threats that are provided by IBM QRadar®, help reduce the impact of incidents on business data. Such integration provides an excellent platform for hosting unstructured business data that is subject to regulatory compliance requirements. This paper describes how IBM Spectrum Scale File Audit Logging can be integrated with IBM QRadar. Using IBM QRadar, an administrator can monitor, inspect, detect, and derive insights for identifying potential threats to the data that is stored on IBM Spectrum Scale. When the threats are identified, you can quickly act on them to mitigate or reduce the impact of incidents. We further demonstrate how the threat detection by IBM QRadar can proactively trigger data snapshots or cyber resiliency workflow in IBM Spectrum Scale to protect the data during threat. This third edition has added the section "Ransomware threat detection", where we describe a ransomware attack scenario within an environment to leverage IBM Spectrum Scale File Audit logs integration with IBM QRadar. This paper is intended for chief technology officers, solution engineers, security architects, and systems administrators. This paper assumes a basic understanding of IBM Spectrum Scale and IBM QRadar and their administration.

In PostGIS in Action, Third Edition you will learn: An introduction to spatial databases Geometry, geography, raster, and topology spatial types, functions, and queries Applying PostGIS to real-world problems Extending PostGIS to web and desktop applications Querying data from external sources using PostgreSQL Foreign Data Wrappers Optimizing queries for maximum speed Simplifying geometries for greater efficiency PostGIS in Action, Third Edition teaches readers of all levels to write spatial queries for PostgreSQL. You’ll start by exploring vector-, raster-, and topology-based GIS before quickly progressing to analyzing, viewing, and mapping data. This fully updated third edition covers key changes in PostGIS 3.1 and PostgreSQL 13, including parallelization support, partitioned tables, and new JSON functions that help in creating web mapping applications. About the Technology PostGIS is a spatial database extender for PostgreSQL. It offers the features and firepower you need to take on nearly any geodata task. PostGIS lets you create location-aware queries with a few lines of SQL code, then build the backend for mapping, raster analysis, or routing application with minimal effort. About the Book PostGIS in Action, Third Edition shows you how to solve real-world geodata problems. You’ll go beyond basic mapping, and explore custom functions for your applications. Inside this fully updated edition, you’ll find coverage of new PostGIS features such as PostGIS Window functions, parallelization of queries, and outputting data for applications using JSON and Vector Tile functions. What's Inside Fully revised for PostGIS version 3.1 and PostgreSQL 13 Optimize queries for maximum speed Simplify geometries for greater efficiency Extend PostGIS to web and desktop applications About the Reader For readers familiar with relational databases and basic SQL. No prior geodata or GIS experience required. About the Authors Regina Obe and Leo Hsu are database consultants and authors. Regina is a member of the PostGIS core development team and the Project Steering Committee. Quotes The best introduction I’ve seen for engineers who want to get ramped up quickly and build advanced GIS applications. - Ikechukwu Okonkwo, Orum.io A wealth of information that showcases how powerful PostGIS is. - Luis Moux-Dominguez, EMO An extraordinary book for the world of GIS. Truly learned a lot! - DeUndre’ Rushon, DigiDiscover LLC Gives you insight into how best to provide map services for a wide audience. - Marcus Brown, Enel Green Power

Get a comprehensive overview on how to set up and design an effective database with MySQL. This thoroughly updated edition covers MySQL's latest version, including its most important aspects. Whether you're deploying an environment, troubleshooting an issue, or engaging in disaster recovery, this practical guide provides the insights and tools necessary to take full advantage of this powerful RDBMS. Authors Vinicius Grippa and Sergey Kuzmichev from Percona show developers and DBAs methods for minimizing costs and maximizing availability and performance. You'll learn how to perform basic and advanced querying, monitoring and troubleshooting, database management and security, backup and recovery, and tuning for improved efficiency. This edition includes new chapters on high availability, load balancing, and using MySQL in the cloud. Get started with MySQL and learn how to use it in production Deploy MySQL databases on bare metal, on virtual machines, and in the cloud Design database infrastructures Code highly efficient queries Monitor and troubleshoot MySQL databases Execute efficient backup and restore operations Optimize database costs in the cloud Understand database concepts, especially those pertaining to MySQL

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

This IBM® Redbooks Product Guide provides an overview of the features and functions that are available with the IBM DS8900F models that run microcode Release 9.2 (Bundle 89.20 / Licensed Machine Code 7.9.20). As of August 2021, the DS8900F with DS8000 Release 9.2 is the latest addition. The DS8900F is an all-flash system exclusively, and it offers three classes: IBM DS8980F: Analytic Class: The DS8980F Analytic Class offers best performance for organizations that want to expand their workload possibilities to artificial intelligence (AI), Business Intelligence, and Machine Learning. IBM DS8950F: Agility Class: The agility class is efficiently designed to consolidate all your mission-critical workloads for IBM Z, IBM LinuxONE, IBM Power Systems, and distributed environments under a single all-flash storage solution.. IBM DS8910F: Flexibility Class: The flexibility class delivers significant performance for midrange organizations that are looking to meet storage challenges with advanced functionality delivered as a single rack solution.

This IBM® Redpaper publication provides guidance on building an enterprise-grade data lake by using IBM Spectrum® Scale and Cloudera Data Platform (CDP) Private Cloud Base for performing in-place Cloudera Hadoop or Cloudera Spark-based analytics. It also covers the benefits of the integrated solution and gives guidance about the types of deployment models and considerations during the implementation of these models. August 2021 update added CES protocol support in Hadoop environment

Address the most common integration challenges, by understanding the ins and outs of the choices and exemplifying the solutions with practical examples on how to create cloud native applications using Apache Camel. Camel will be our main tool, but we will also see some complementary tools and plugins that can make our development and testing easier, such as Quarkus, and tools for more specific use cases, such as Apache Kafka and Keycloak. You will learn to connect with databases, create REST APIs, transform data, connect with message oriented software (MOMs), secure your services, and test using Camel. You will also learn software architecture patterns for integration and how to leverage container platforms, such as Kubernetes. This book is suitable for those who are eager to learn an integration tool that fits the Kubernetes world, and who want to explore the integration challenges that can be solved using containers. What You Will Learn Focus on how to solve integration challenges Understand the basics of the Quarkus as it’s the foundation for the application Acquire a comprehensive view on Apache Camel Deploy an application in Kubernetes Follow good practices Who This Book Is For Java developers looking to learn Apache Camel; Apache Camel developers looking to learn more about Kubernetes deployments; software architects looking to study integration patterns for Kubernetes based systems; system administrators (operations teams) looking to get a better understand of how technologies are integrated.

Single-purpose databases were designed to address specific problems and use cases. Given this narrow focus, there are inherent tradeoffs required when trying to accommodate multiple datatypes or workloads in your enterprise environment. The result is data fragmentation that spills over into application development, IT operations, data security, system scalability, and availability. In this report, author Alice LaPlante explains why developing modern, data-driven applications may be easier and more synergistic when using a converged database. Senior developers, architects, and technical decision-makers will learn cloud-native application development techniques for working with both structured and unstructured data. You'll discover ways to run transactional and analytical workloads on a single, unified data platform. This report covers: Benefits and challenges of using a converged database to develop data-driven applications How to use one platform to work with both structured and unstructured data that includes JSON, XML, text and files, spatial and graph, Blockchain, IoT, time series, and relational data Modern development practices on a converged database, including API-driven development, containers, microservices, and event streaming Use case examples including online food delivery, real-time fraud detection, and marketing based on real-time analytics and geospatial targeting

This document is intended to facilitate the solution for Safeguarded Copy for cyber resiliency and logical air gap solution for IBM FlashSystem and SAN Volume Controller. The document showcases the configuration and end-to-end architecture for configuring the logical air-gap solution for cyber resiliency by using the Safeguarded Copy feature in IBM FlashSystem and IBM SAN Volume Control storage. The information in this document is distributed on an "as is" basis without any warranty that is either expressed or implied. Support assistance for the use of this material is limited to situations where IBM FlashSystem or IBM SAN Volume Controller storage devices are supported and entitled and where the issues are specific to a blueprint implementation.

Gain practical guidance for implementing data models on the SAP BW/4HANA platform using modern modeling concepts. You will walk through the various modeling scenarios such as exposing HANA tables and views through BW/4HANA, creating virtual and hybrid data models, and integrating SAP and non-SAP data into a single data model. Data Modeling with SAP BW/4HANA 2.0 gives you the skills you need to use the new SAP BW/HANA features and objects, covers modern modelling concepts, and equips you with the practical knowledge of how to use the best of the HANA and BW/4HANA worlds. What You Will Learn Discover the new modeling features in SAP BW/4HANA Combine SAP HANA and SAP BW/4HANA artifacts Leverage virtualization when designing and building data models Build hybrid data models combining InfoObject, OpenODS, and a field-based approach Integrate SAP and non-SAP data into single model Who This Book Is For BI consultants, architects, developers, and analysts working in the SAP BW/4HANA environment.

Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure. In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. About the Technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the Book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's Inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the Reader For data engineers familiar with cloud computing and DevOps. About the Author Vlad Riscutia is a software architect at Microsoft. Quotes A definitive and complete guide on data engineering, with clear and easy-to-reproduce examples. - Kelum Prabath Senanayake, Echoworx An all-in-one Azure book, covering all a solutions architect or engineer needs to think about. - Albert Nogués, Danone A meaningful journey through the Azure ecosystem. You’ll be building pipelines and joining components quickly! - Todd Cook, Appen A gateway into the world of Azure for machine learning and DevOps engineers. - Krzysztof Kamyczek, Luxoft

In "Developing Modern Database Applications with PostgreSQL", you will master the art of building database applications with the highly available and scalable PostgreSQL. Walk through a series of real-world projects that fully explore both the developmental and administrative aspects of PostgreSQL, all tied together through the example of a banking application. What this Book will help me do Set up high-availability PostgreSQL clusters using modern best practices. Monitor and tune database performance to handle enterprise-level workloads seamlessly. Automate testing and implement test-driven development strategies for robust applications. Leverage PostgreSQL along with DevOps pipelines to deploy applications on cloud platforms. Develop APIs and geospatial databases using popular tools like PostgREST and PostGIS. Author(s) The authors of this book, None Le and None Diaz, are experienced professionals in database technologies and software development. With a passion for PostgreSQL and its applications in modern computing, they bring a wealth of expertise and a practical approach to this book. Their methods focus on real-world applicability, ensuring that readers gain hands-on skills and practical knowledge. Who is it for? This book is perfect for database developers, administrators, and architects who want to advance their expertise in PostgreSQL. It is also suitable for software engineers and IT professionals aiming to tackle end-to-end database development projects. A basic knowledge of PostgreSQL and Linux will help you dive into the hands-on projects easily. If you're looking to take your PostgreSQL skills to the next level, this book is for you.

Continuing its commitment to developing and delivering industry-leading storage technologies, IBM® introduces the IBM FlashSystem® solution that is powered by IBM Spectrum® Virtualize V8.4. This innovative storage offering delivers essential storage efficiency technologies and exceptional ease of use and performance, all integrated into a compact, modular design that is offered at a competitive, midrange price. The solution incorporates some of the top IBM technologies that are typically found only in enterprise-class storage systems, which raises the standard for storage efficiency in midrange disk systems. This cutting-edge storage system extends the comprehensive storage portfolio from IBM and can help change the way organizations address the ongoing information explosion. This IBM Redbooks® publication introduces the features and functions of an IBM Spectrum Virtualize V8.4 system through several examples. This book is aimed at pre-sales and post-sales technical support and marketing and storage administrators. It helps you understand the architecture, how to implement it, and how to take advantage of its industry-leading functions and features.

This IBM® Redbooks® publication presents an overview of the IBM Geographically Dispersed Parallel Sysplex® (IBM GDPS®) offerings and the roles they play in delivering a business IT resilience solution. The book begins with general concepts of business IT resilience and disaster recovery, along with issues related to high application availability, data integrity, and performance. These topics are considered within the framework of government regulation, increasing application and infrastructure complexity, and the competitive and rapidly changing modern business environment. Next, it describes the GDPS family of offerings with specific reference to how they can help you achieve your defined goals for disaster recovery and high availability. Also covered are the features that simplify and enhance data replication activities, the prerequisites for implementing each offering, and tips for planning for the future and immediate business requirements. Tables provide easy-to-use summaries and comparisons of the offerings. The extra planning and implementation services available from IBM also are explained. Then, several practical client scenarios and requirements are described, along with the most suitable GDPS solution for each case. The introductory chapters of this publication are intended for a broad technical audience, including IT System Architects, Availability Managers, Technical IT Managers, Operations Managers, System Programmers, and Disaster Recovery Planners. The subsequent chapters provide more technical details about the GDPS offerings, and each can be read independently for those readers who are interested in specific topics. Therefore, if you read all of the chapters, be aware that some information is intentionally repeated.

Data Modeling for Azure Data Services is an essential guide that delves into the intricacies of designing, provisioning, and implementing robust data solutions within the Azure ecosystem. Through practical examples and hands-on exercises, this book equips you with the knowledge to create scalable, performant, and adaptable database designs tailored to your business needs. What this Book will help me do Understand and apply normalization, dimensional modeling, and data vault modeling for relational databases. Learn to provision and implement scalable solutions like Azure SQL DB and Azure Synapse SQL Pool. Master how to design and model a Data Lake using Azure Storage efficiently. Gain expertise in NoSQL database modeling and implementing solutions using Azure Cosmos DB. Develop ETL/ELT processes effectively using Azure Data Factory to support data integration workflows. Author(s) None Braake brings a wealth of expertise as a data architect and cloud solutions builder specializing in Azure's data services. With hands-on experience in projects requiring sophisticated data modeling and optimization, None crafts detailed learning material to help professionals level up their database design and Azure deployment skills. Dedicated to explaining complex topics with clarity and approachable language, None ensures that the learners gain not just knowledge but applied competence. Who is it for? This book is a valuable resource for business intelligence developers, data architects, and consultants aiming to refine their skills in data modeling within modern cloud ecosystems, particularly Microsoft Azure. Whether you're a beginner with some foundational cloud data management knowledge or an experienced professional seeking to deepen your Azure data services proficiency, this book caters to your learning needs.

Build a modern data platform by deploying SQL Server in Kubernetes. Modern application deployment needs to be fast and consistent to keep up with business objectives and Kubernetes is quickly becoming the standard for deploying container-based applications, fast. This book introduces Kubernetes and its core concepts. Then it shows you how to build and interact with a Kubernetes cluster. Next, it goes deep into deploying and operationalizing SQL Server in Kubernetes, both on premises and in cloud environments such as the Azure Cloud. You will begin with container-based application fundamentals and then go into an architectural overview of a Kubernetes container and how it manages application state. Then you will learn the hands-on skill of building a production-ready cluster. With your cluster up and running, you will learn how to interact with your cluster and perform common administrative tasks. Once you can admin the cluster, you will learn how to deploy applications and SQL Server in Kubernetes. You will learn about high-availability options, and about using Azure Arc-enabled Data Services. By the end of this book, you will know how to set up a Kubernetes cluster, manage a cluster, deploy applications and databases, and keep everything up and running. What You Will Learn Understand Kubernetes architecture and cluster components Deploy your applications into Kubernetes clusters Manage your containers programmatically through API objects and controllers Deploy and operationalize SQL Server in Kubernetes Implement high-availability SQL Server scenarios on Kubernetes using Azure Arc-enabled Data Services Make use of Kubernetes deployments for Big Data Clusters Who This Book Is For DBAs and IT architects who are ready to begin planning their next-generation data platform and want to understand what it takes to run SQL Server in a container in Kubernetes. SQL Server on Kubernetes is an excellent choice for those who want to understand the big picture of why Kubernetes is the next-generation deployment method for SQL Server but also want to understand the internals, or the how, of deploying SQL Server in Kubernetes. When finished with this book, you will have the vision and skills to successfully architect, build and maintain a modern data platform deploying SQL Server on Kubernetes.

DESIGNING BIG DATA PLATFORMS Provides expert guidance and valuable insights on getting the most out of Big Data systems An array of tools are currently available for managing and processing data—some are ready-to-go solutions that can be immediately deployed, while others require complex and time-intensive setups. With such a vast range of options, choosing the right tool to build a solution can be complicated, as can determining which tools work well with each other. Designing Big Data Platforms provides clear and authoritative guidance on the critical decisions necessary for successfully deploying, operating, and maintaining Big Data systems. This highly practical guide helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more. Author Yusuf Aytas, a software engineer with a vast amount of big data experience, discusses the design of the ideal Big Data platform: one that meets the needs of data analysts, data engineers, data scientists, software engineers, and a spectrum of other stakeholders across an organization. Detailed yet accessible chapters cover key topics such as stream data processing, data analytics, data science, data discovery, and data security. This real-world manual for Big Data technologies: Provides up-to-date coverage of the tools currently used in Big Data processing and management Offers step-by-step guidance on building a data pipeline, from basic scripting to distributed systems Highlights and explains how data is processed at scale Includes an introduction to the foundation of a modern data platform Designing Big Data Platforms: How to Use, Deploy, and Maintain Big Data Systems is a must-have for all professionals working with Big Data, as well researchers and students in computer science and related fields.

Mapping a person, place, or thing to a software resource in a verifiable manner is the basis of identity. Confirming that identity is a complex process, particularly when the identity mapping has to be verified genuine and authentic. Everything on the internet that houses private information is tied to identity and identity management. In this report, author Lee Atchison shows C-suite execs, engineering execs, architects, and others involved in building software applications the modern identity management techniques available to safeguard that simple access point. You'll learn how and why these techniques constantly need to keep up with modern application development, and you'll understand the growing sophistication of the people who safely interact or maliciously tamper with them. Explore the complex process of mapping a person, place, or thing to a software resource in a verifiable manner Get examples of real-world authentication, including methods and best practices for working with application credentials Understand the differences between single-factor and multifactor authentication Learn why every authentication method has flaws, including today's state-of-the-art processes Explore authorization, the process for granting users access to specific resources, and how it differs from authentication Understand trust relationships using trust systems to create more secure applications and systems

Dive into the world of Amazon Redshift with this comprehensive cookbook, packed with practical recipes to build, optimize, and manage modern data warehousing solutions. From understanding Redshift's architecture to implementing advanced data warehousing techniques, this book provides actionable guidance to harness the power of Amazon Redshift effectively. What this Book will help me do Master the architecture and core concepts of Amazon Redshift to architect scalable data warehouses. Optimize data pipelines and automate ETL processes for seamless data ingestion and management. Leverage advanced features like concurrency scaling and Redshift Spectrum for enhanced analytics. Apply best practices for security and cost optimization in Redshift projects. Gain expertise in scaling data warehouse solutions to accommodate large-scale analytics needs. Author(s) Shruti Worlikar, None Arumugam, and None Patel are seasoned experts in data warehousing and analytics with extensive experience using Amazon Redshift. Their backgrounds in implementing scalable data solutions make their insights practical and grounded. Through their collaborative writing, they aim to make complex topics approachable to learners of various skill levels. Who is it for? This book is tailored for professionals such as data warehouse developers, data engineers, and data analysts looking to master Amazon Redshift. It suits intermediate to advanced practitioners with a basic understanding of data warehousing and cloud technologies. Readers seeking to optimize Redshift for cost, performance, and security will find this guide invaluable.

Build interactive, data-driven websites with the potent combination of open source technologies and web standards, even if you have only basic HTML knowledge. With the latest edition of this popular hands-on guide, you'll tackle dynamic web programming using the most recent versions of today's core technologies: PHP, MySQL, JavaScript, CSS, HTML5, jQuery, and the powerful React library. Web designers will learn how to use these technologies together while picking up valuable web programming practices along the way, including how to optimize websites for mobile devices. You'll put everything together to build a fully functional social networking site suitable for both desktop and mobile browsers. Explore MySQL from database structure to complex queries Use the MySQL PDO extension, PHP's improved MySQL interface Create dynamic PHP web pages that tailor themselves to the user Manage cookies and sessions and maintain a high level of security Enhance JavaScript with the React library Use Ajax calls for background browser-server communication Style your web pages by acquiring CSS skills Implement HTML5 features, including geolocation, audio, video, and the canvas element Reformat your websites into mobile web apps