IBM® Z has a close and unique relationship to its storage. Over the years, improvements to the Z processors and storage software, the disk storage systems, and their communication architecture consistently reinforced this synergy. This IBM Redpaper publication summarizes and highlights the various aspects, advanced functions, and technologies that are often pioneered by IBM, and that make the IBM Z® and the IBM DS8000 products an ideal combination. This paper is intended for users who have some familiarity with IBM Z and the IBM DS8000® series and want a condensed but comprehensive overview of the synergy items up to the IBM z15™ server with z/OS v2.5 and the IBM DS8900 Release 9.2 firmware.

Get started with Hibernate, an open source Java persistence layer and gain a clear introduction to the current standard for object-relational persistence in Java. This updated edition includes the new Hibernate 6.0 framework which covers new configuration, new object relational mapping changes, and enhanced integration with the more general Spring, Boot and Quarkus and other Java frameworks.The book keeps its focus on Hibernate without wasting time on nonessential third-party tools, so you’ll be able to immediately start building transaction-based engines and applications. Experienced authors Joseph Ottinger with Dave Minter and Jeff Linwood provide more in-depth examples than any other book for Hibernate beginners. They present their material in a lively, example-based manner—not a dry, theoretical, hard-to-read fashion. What You'll Learn Build enterprise Java-based transaction-type applications that access complex data with Hibernate Work with Hibernate 6 using a present-day build process Integrate into the persistence life cycle Search and query with the new version of Hibernate Keep track of versioned data with Hibernate Envers Who This Book Is For Programmers experienced in Java with databases (the traditional, or connected, approach), but new to open-source, lightweight Hibernate.

Media content today is increasingly streamed video, and this trend will only grow as the speed of consumer internet and video quality improve. Traditional video streaming platforms, such as Netflix and Hulu, now account for only a portion of this content as more and more live events are streamed over the internet. And consumer-generated content on video-based social networks such as Twitch and TikTok is now more accessible and gaining popularity. This report focuses on the current state of video delivery, including the challenges content providers face and the various solutions they're pursuing. The findings in this report are based on a recent survey conducted by Edgecast, a content delivery network (CDN) that helps companies accelerate and deliver static and dynamic content to end users around the world. You'll explore: The current state of video streaming, how it works, and how streams are delivered Responses from a survey of CDN users that produce video streams How content providers are addressing recent video streaming challenges How the information in this report can help you identify KPIs

Data Engineering with Apache Spark, Delta Lake, and Lakehouse is a comprehensive guide packed with practical knowledge for building robust and scalable data pipelines. Throughout this book, you will explore the core concepts and applications of Apache Spark and Delta Lake, and learn how to design and implement efficient data engineering workflows using real-world examples. What this Book will help me do Master the core concepts and components of Apache Spark and Delta Lake. Create scalable and secure data pipelines for efficient data processing. Learn best practices and patterns for building enterprise-grade data lakes. Discover how to operationalize data models into production-ready pipelines. Gain insights into deploying and monitoring data pipelines effectively. Author(s) None Kukreja is a seasoned data engineer with over a decade of experience working with big data platforms. He specializes in implementing efficient and scalable data solutions to meet the demands of modern analytics and data science. Writing with clarity and a practical approach, he aims to provide actionable insights that professionals can apply to their projects. Who is it for? This book is tailored for aspiring data engineers and data analysts who wish to delve deeper into building scalable data platforms. It is suitable for those with basic knowledge of Python, Spark, and SQL, and seeking to learn Delta Lake and advanced data engineering concepts. Readers should be eager to develop practical skills for tackling real-world data engineering challenges.

The focus of this document is to demonstrate an early threat detection by using IBM® QRadar® and the Safeguarded Copy feature that is available as part of IBM FlashSystem® and IBM SAN Volume Controller. Such early detection protects and quickly recovers the data if a cyberattack occurs. This document describes integrating IBM FlashSystem audit logs with IBM QRadar, and the configuration steps for IBM FlashSystem and IBM QRadar. It also explains how to use the IBM QRadar's device support module (DSM) editor to normalize events and assign IBM QRadar identifier (QID) map to the events. Post IBM QRadar configuration, we review configuring Safeguarded Copy on the application volumes by using volume groups and applying Safeguarded backup polices on the volume group. Finally, we demonstrate the use of orchestration software IBM Copy Services Manager to start a recovery, restore operations for data restoration on online volumes, and start a backup of data volumes.

IBM® Spectrum Protect Plus is a data protection solution that provides near-instant recovery, replication, retention management, and reuse for virtual machines, databases, and application backups in hybrid multicloud environments. This IBM Redpaper publication focuses on protecting database applications. IBM Spectrum® Protect Plus supports backup, restore, and data reuse for multiple databases, such as Oracle, IBM Db2®, MongoDB, Microsoft Exchange, and Microsoft SQL Server. Although other IBM Spectrum Protect Plus features focus on virtual environments, the database and application support of IBM Spectrum Protect Plus includes databases on virtual physical servers.

This IBM® Redbooks® publication captures several of the preferred practices and describes the performance gains that can be achieved by implementing the IBM FlashSystem products. These practices are based on field experience. This book highlights configuration guidelines and preferred practices for the storage area network (SAN) topology, clustered system, back-end storage, storage pools and managed disks, volumes, remote copy services, and hosts. It explains how you can optimize disk performance with the IBM System Storage® Easy Tier® function. It also provides preferred practices for monitoring, maintaining, and troubleshooting. This book is intended for experienced storage, SAN, IBM FlashSystem, SAN Volume Controller (SVC), and IBM Storwize® administrators and technicians. Understanding this book requires advanced knowledge of these environments.

Storage Systems: Organization, Performance, Coding, Reliability and Their Data Processing was motivated by the 1988 Redundant Array of Inexpensive/Independent Disks proposal to replace large form factor mainframe disks with an array of commodity disks. Disk loads are balanced by striping data into strips—with one strip per disk— and storage reliability is enhanced via replication or erasure coding, which at best dedicates k strips per stripe to tolerate k disk failures. Flash memories have resulted in a paradigm shift with Solid State Drives (SSDs) replacing Hard Disk Drives (HDDs) for high performance applications. RAID and Flash have resulted in the emergence of new storage companies, namely EMC, NetApp, SanDisk, and Purestorage, and a multibillion-dollar storage market. Key new conferences and publications are reviewed in this book.The goal of the book is to expose students, researchers, and IT professionals to the more important developments in storage systems, while covering the evolution of storage technologies, traditional and novel databases, and novel sources of data. We describe several prototypes: FAWN at CMU, RAMCloud at Stanford, and Lightstore at MIT; Oracle's Exadata, AWS' Aurora, Alibaba's PolarDB, Fungible Data Center; and author's paper designs for cloud storage, namely heterogeneous disk arrays and hierarchical RAID. Surveys storage technologies and lists sources of data: measurements, text, audio, images, and video Familiarizes with paradigms to improve performance: caching, prefetching, log-structured file systems, and merge-trees (LSMs) Describes RAID organizations and analyzes their performance and reliability Conserves storage via data compression, deduplication, compaction, and secures data via encryption Specifies implications of storage technologies on performance and power consumption Exemplifies database parallelism for big data, analytics, deep learning via multicore CPUs, GPUs, FPGAs, and ASICs, e.g., Google's Tensor Processing Units

This book is your complete guide to Snowflake security, covering account security, authentication, data access control, logging and monitoring, and more. It will help you make sure that you are using the security controls in a right way, are on top of access control, and making the most of the security features in Snowflake. Snowflake is the fastest growing cloud data warehouse in the world, and having the right methodology to protect the data is important both to data engineers and security teams. It allows for faster data enablement for organizations, as well as reducing security risks, meeting compliance requirements, and solving data privacy challenges. There are currently tens of thousands of people who are either data engineers/data ops in Snowflake-using organizations, or security people in such organizations. This book provides guidance when you want to apply certain capabilities, such as data masking, row-level security, column-level security, tackling rolehierarchy, building monitoring dashboards, etc., to your organizations. What You Will Learn Implement security best practices for Snowflake Set up user provisioning, MFA, OAuth, and SSO Set up a Snowflake security model Design roles architecture Use advanced access control such as row-based security and dynamic masking Audit and monitor your Snowflake Data Cloud Who This Book Is For Data engineers, data privacy professionals, and security teams either with security knowledge (preferably some data security knowledge) or with data engineering knowledge; in other words, either “Snowflake people” or “data people” who want to get security right, or “security people” who want to make sure that Snowflake gets handled right in terms of security

The IBM® FlashSystem 5015, 5035, and 5200 help you meet the challenges of rapid data growth while staying within limited IT budgets. These systems allow you to quickly consolidate, simplify, and optimize your IT infrastructure with an efficient, highly flexible, yet easy-to-use storage system with powerful virtualization features. This IBM Redpaper™ publication is intended for mid-market clients.

This IBM Redpaper publication describes best practices for deploying and using advanced Cisco NX-OS features to identify, monitor, and protect Fibre Channel (FC) Storage Area Networks (SANs) from problematic devices and media behavior. The paper focuses on the IBM c-type SAN switches with firmware Cisco MDS NX-OS Release 8.4(2a).

Azure Databricks is a robust analytics platform that leverages Apache Spark and seamlessly integrates with Azure services. In the Azure Databricks Cookbook, you'll find hands-on recipes to ingest data, build modern data pipelines, and perform real-time analytics while learning to optimize and secure your solutions. What this Book will help me do Design advanced data workflows integrating Azure Synapse, Cosmos DB, and streaming sources with Databricks. Gain proficiency in using Delta Tables and Spark for efficient data storage and analysis. Learn to create, deploy, and manage real-time dashboards with Databricks SQL. Master CI/CD pipelines for automating deployments of Databricks solutions. Understand security best practices for restricting access and monitoring Azure Databricks. Author(s) None Raj and None Jaiswal are experienced professionals in the field of big data and analytics. They are well-versed in implementing Azure Databricks solutions for real-world problems. Their collaborative writing approach ensures clarity and practical focus. Who is it for? This book is tailored for data engineers, scientists, and big data professionals who want to apply Azure Databricks and Apache Spark to their analytics workflows. A basic familiarity with Spark and Azure is recommended to make the best use of the recipes provided. If you're looking to scale and optimize your analytics pipelines, this book is for you.

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.