This IBM® Redbooks® publication is a guide to IBM Power Private Cloud with Shared Utility Capacity featuring Power Enterprise Pools 2.0 (also known as PEP 2.0). This technology allows multiple servers in an to share base processor and memory resources, and draw upon pre-paid credits when the base is exceeded. Previously, the Shared Utility feature supported IBM Power System E950 (9040-MR9) and IBM Power System E980 (9080-M9S). It was extended in August 2020 to include the Scale-out Power Systems announced on July 14th 2020 and received dedicated processor support later in the year. The IBM Power System S922 (9009-22G), and IBM Power System S924 (9009-42G) servers which use the latest IBM POWER9™ processor-based technology and support the IBM AIX®, IBM i, and Linux operating systems are now supported. The previous Scale-out models: IBM Power System S922 (9009-22A), and IBM Power System S924 (9009-42A) servers cannot be added to an Enterprise Pool. The goal of this book is to provide an overview of the environment and guidance for planning a deployment. The paper also covers how to configure PEP 2.0. There are also chapters on migrating from PEP 1.0 to PEP 2.0 and various use cases. This publication is for professionals who want to acquire a better understanding of IBM Power Private Cloud, and Shared Utility. The intended audience includes: Clients Sales and marketing professionals Technical support professionals IBM Business Partners This book expands the set of Power Systems documentation by providing a desktop reference which offers a detailed technical description of IBM Power Private Cloud, and Shared Utility.

Database developers and administrators will use this book to learn how to deploy machine learning models in Oracle Database and in Oracle’s Autonomous Database cloud offering. The book covers the technologies that make up the Oracle Machine Learning (OML) platform, including OML4SQL, OML Notebooks, OML4R, and OML4Py. The book focuses on Oracle Machine Learning as part of the Oracle Autonomous Database collaborative environment. Also covered are advanced topics such as delivery and automation pipelines. Throughout the book you will find practical details and hand-on examples showing you how to implement machine learning and automate deployment of machine learning. Discussion around the examples helps you gain a conceptual understanding of machine learning. Important concepts discussed include the methods involved, the algorithms to choose from, and mechanisms for process and deployment. Seasoned database professionals looking to make the leap into machine learning as a growth path will find much to like in this book as it helps you step up and use your current knowledge of Oracle Database to transition into providing machine learning solutions. What You Will Learn Use the Oracle Machine Learning (OML) Notebooks for data visualization and machine learning model building and evaluation Understand Oracle offerings for machine learning Develop machine learning with Oracle database using the built-in machine learning packages Develop and deploy machine learning models using OML4SQL and OML4R Leverage the Oracle Autonomous Database and its collaborative environment for Oracle Machine Learning Develop and deploy machine learning projects in Oracle Autonomous Database Build an automated pipeline that can detect and handle changes in data/model performance Who This Book Is For Database developers and administrators who want to learn about machine learning, developers who want to build models and applications using Oracle Database’s built-in machine learning feature set, and administrators tasked with supporting applications on Oracle Database that make use of the Oracle Machine Learning feature set

Data engineers who need to hit the ground running will use this book to build skills in Azure Data Factory v2 (ADF). The tutorial-first approach to ADF taken in this book gets you working from the first chapter, explaining key ideas naturally as you encounter them. From creating your first data factory to building complex, metadata-driven nested pipelines, the book guides you through essential concepts in Microsoft’s cloud-based ETL/ELT platform. It introduces components indispensable for the movement and transformation of data in the cloud. Then it demonstrates the tools necessary to orchestrate, monitor, and manage those components. The hands-on introduction to ADF found in this book is equally well-suited to data engineers embracing their first ETL/ELT toolset as it is to seasoned veterans of Microsoft’s SQL Server Integration Services (SSIS). The example-driven approach leads you through ADF pipeline construction from the ground up, introducing important ideas and making learning natural and engaging. SSIS users will find concepts with familiar parallels, while ADF-first readers will quickly master those concepts through the book’s steady building up of knowledge in successive chapters. Summaries of key concepts at the end of each chapter provide a ready reference that you can return to again and again. What You Will Learn Create pipelines, activities, datasets, and linked services Build reusable components using variables, parameters, and expressions Move data into and around Azure services automatically Transform data natively using ADF data flows and Power Query data wrangling Master flow-of-control and triggers for tightly orchestrated pipeline execution Publish and monitor pipelines easily and with confidence Who This Book Is For Data engineers and ETL developers taking their first steps in Azure Data Factory, SQL Server Integration Services users making the transition toward doing ETL in Microsoft’s Azure cloud, and SQL Server database administrators involved in data warehousing and ETL operations

This IBM® Redpaper Redbooks publication provides guidance about a backup and recovery solution for SAP High-performance Analytic Appliance (HANA) running on IBM Power Systems. This publication provides case studies and how-to procedures that show backup and recovery scenarios. This publication provides information about how to protect data in an SAP HANA environment by using IBM Spectrum® Protect and IBM Spectrum Copy Data Manager. This publication focuses on the data protection solution, which is described through several scenarios. The information in this publication 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 Spectrum Scale or IBM Spectrum Protect are supported and entitled, and where the issues are specific to a blueprint implementation. The goal of the publication is to describe the best aspects and options for backup, snapshots, and restore of SAP HANA Multitenant Database Container (MDC) single and multi-tenant installations on IBM Power Systems by using theoretical knowledge, hands-on exercises, and documenting the findings through sample scenarios. This document provides resources about the following processes: Describing how to determine the best option, including SAP Landscape aspects to back up, snapshot, and restore of SAP HANA MDC single and multi-tenant installations based on IBM Spectrum Computing Suite, Red Hat Linux Relax and Recover (ReAR), and other products. Documenting key aspects, such as recovery time objective (RTO) and recovery point objective (RPO), backup impact (load, duration, scheduling), quantitative savings (for example, data deduplication), integration and catalog currency, and tips and tricks that are not covered in the product documentation. Using IBM Cloud® Object Storage and documenting how to use IBM Spectrum Protect to back up to the cloud. SAP HANA 2.0 SPS 05 has this feature that is built in natively. IBM Spectrum Protect for Enterprise Resource Planning (ERP) has this feature too. Documenting Linux ReaR to cover operating system (OS) backup because ReAR is used by most backup products, such as IBM Spectrum Protect and Symantec Endpoint Protection (SEP) to back up OSs. This publication targets technical readers including IT specialists, systems architects, brand specialists, sales teams, and anyone looking for a guide about how to implement the best options for SAP HANA backup and recovery on IBM Power Systems. Moreover, this publication provides documentation to transfer the how-to-skills to the technical teams and solution guidance to the sales team. This publication complements the documentation that is available at IBM Knowledge Center, and it aligns with the educational materials that are provided by IBM Garage™ for Systems Technical Education and Training.

IBM® Power Virtualization Center (IBM® PowerVC™) is an advanced enterprise virtualization management offering for IBM Power Systems. This IBM Redbooks® publication introduces IBM PowerVC and helps you understand its functions, planning, installation, and setup. It also shows how IBM PowerVC can integrate with systems management tools such as Ansible or Terraform and that it also integrates well into a OpenShift container environment. IBM PowerVC Version 2.0.0 supports both large and small deployments, either by managing IBM PowerVM® that is controlled by the Hardware Management Console (HMC), or by IBM PowerVM NovaLink. With this capability, IBM PowerVC can manage IBM AIX®, IBM i, and Linux workloads that run on IBM POWER® hardware. IBM PowerVC is available as a Standard Edition, or as a Private Cloud Edition. IBM PowerVC includes the following features and benefits: Virtual image capture, import, export, deployment, and management Policy-based virtual machine (VM) placement to improve server usage Snapshots and cloning of VMs or volumes for backup or testing purposes Support of advanced storage capabilities such as IBM SVC vdisk mirroring of IBM Global Mirror Management of real-time optimization and VM resilience to increase productivity VM Mobility with placement policies to reduce the burden on IT staff in a simple-to-install and easy-to-use graphical user interface (GUI) Automated Simplified Remote Restart for improved availability of VMs ifor when a host is down Role-based security policies to ensure a secure environment for common tasks The ability to enable an administrator to enable Dynamic Resource Optimization on a schedule IBM PowerVC Private Cloud Edition includes all of the IBM PowerVC Standard Edition features and enhancements: A self-service portal that allows the provisioning of new VMs without direct system administrator intervention. There is an option for policy approvals for the requests that are received from the self-service portal. Pre-built deploy templates that are set up by the cloud administrator that simplify the deployment of VMs by the cloud user. Cloud management policies that simplify management of cloud deployments. Metering data that can be used for chargeback. This publication is for experienced users of IBM PowerVM and other virtualization solutions who want to understand and implement the next generation of enterprise virtualization management for Power Systems. Unless stated otherwise, the content of this publication refers to IBM PowerVC Version 2.0.0.

Through explosive growth in the past decade, data now drives significant portions of our lives, from crowdsourced restaurant recommendations to AI systems identifying effective medical treatments. Software developers have unprecedented opportunity to build data applications that generate value from massive datasets across use cases such as customer 360, application health and security analytics, the IoT, machine learning, and embedded analytics. With this report, product managers, architects, and engineering teams will learn how to make key technical decisions when building data-intensive applications, including how to implement extensible data pipelines and share data securely. The report includes design considerations for making these decisions and uses the Snowflake Data Cloud to illustrate best practices. This report explores: Why data applications matter: Get an introduction to data applications and some of the most common use cases Evaluating platforms for building data apps: Evaluate modern data platforms to confidently consider the merits of potential solutions Building scalable data applications: Learn design patterns and best practices for storage, compute, and security Handling and processing data: Explore techniques and real-world examples for building data pipelines to support data applications Designing for data sharing: Learn best practices for sharing data in modern data applications

In 'Distributed Data Systems with Azure Databricks', you will explore the capabilities of Microsoft Azure Databricks as a platform for building and managing big data pipelines. Learn how to process, transform, and analyze data at scale while developing expertise in training distributed machine learning models and integrating them into enterprise workflows. What this Book will help me do Design and implement Extract, Transform, Load (ETL) pipelines using Azure Databricks. Conduct distributed training of machine learning models using TensorFlow and Horovod. Integrate Azure Databricks with Azure Data Factory for optimized data pipeline orchestration. Utilize Delta Engine for efficient querying and analysis of data within Delta Lake. Employ Databricks Structured Streaming to manage real-time production-grade data flows. Author(s) None Palacio is an experienced data engineer and cloud computing specialist, with extensive knowledge of the Microsoft Azure platform. With years of practical application of Databricks in enterprise settings, Palacio provides clear, actionable insights through relatable examples. They bring a passion for innovative solutions to the field of big data automation. Who is it for? This book is ideal for data engineers, machine learning engineers, and software developers looking to master Azure Databricks for large-scale data processing and analysis. Readers should have basic familiarity with cloud platforms, understanding of data pipelines, and a foundational grasp of Python and machine learning concepts. It is perfect for those wanting to create scalable and manageable data workflows.

This IBM® Redpaper publication is a comprehensive guide that covers the IBM Power System IC922 (9183-22X) server that uses IBM POWER9™ processor-based technology and supports Linux operating systems (OSs). The objective of this paper is to introduce the system offerings and their capacities and available features. The Power IC922 server is built to deliver powerful computing, scaling efficiency, and storage capacity in a cost-optimized design to meet the evolving data challenges of the artificial intelligence (AI) era. It includes the following features: High throughput and performance for high-value Linux workloads, such as inferencing data or storage-rich workloads, or cloud. Potentially low acquisition cost through system optimization, such as using industry standard memory and warranty. Two IBM POWER9 processor-based single-chip module (SCM) devices that provide high performance with 24, 32, or 40 fully activated cores and a maximum 2 TB of memory. Up to six NVIDIA T4 graphics processing unit (GPU) accelerators. Up to twenty-four 2.5-inch SAS/SATA drives. One dedicated and one shared 1 Gb Intelligent Platform Management Interface (IPMI) port.. This publication is for professionals who want to acquire a better understanding of IBM Power Systems products. The intended audience includes: Clients Sales and marketing professionals Technical support professionals IBM Business Partners Independent software vendors (ISVs) This paper expands the current set of IBM Power Systems documentation by providing a desktop reference that offers a detailed technical description of the Power IC922 server.

Imagine you are a business user, consultant, or developer about to enter an SAP S/4HANA implementation project. You are well-versed with SAP’s product portfolio and you know that the preferred reporting option in S/4HANA is embedded analytics. But what exactly is embedded analytics? And how can it be implemented? And who can do it: a business user, a functional consultant specialized in financial or logistics processes? Or does a business intelligence expert or a programmer need to be involved? Good questions! This book will answer these questions, one by one. It will also take you on the same journey that the implementation team needs to follow for every reporting requirement that pops up: start with assessing a more standard option and only move on to a less standard option if the requirement cannot be fulfilled. In consecutive chapters, analytical apps delivered by SAP, apps created using Smart Business Services, and Analytical Queries developed either using tiles or in adevelopment environment are explained in detail with practical examples. The book also explains which option is preferred in which situation. The book covers topics such as in-memory computing, cloud, UX, OData, agile development, and more.Author Freek Keijzer writes from the perspective of an implementation consultant, focusing on functionality that has proven itself useful in the field. Practical examples are abundant, ranging from “codeless” to “hardcore coding.” What You Will Learn Know the difference between static reporting and interactive querying on real-time data Understand which options are available for analytics in SAP S/4HANA Understand which option to choose in which situation Know how to implement these options Who This Book is For SAP power users, functional consultants, developers

A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, keeping every process along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, Data Pipelines with Apache Airflow teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. About the Technology Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. Apache Airflow provides a single platform you can use to design, implement, monitor, and maintain your pipelines. Its easy-to-use UI, plug-and-play options, and flexible Python scripting make Airflow perfect for any data management task. About the Book Data Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines. You’ll explore the most common usage patterns, including aggregating multiple data sources, connecting to and from data lakes, and cloud deployment. Part reference and part tutorial, this practical guide covers every aspect of the directed acyclic graphs (DAGs) that power Airflow, and how to customize them for your pipeline’s needs. What's Inside Build, test, and deploy Airflow pipelines as DAGs Automate moving and transforming data Analyze historical datasets using backfilling Develop custom components Set up Airflow in production environments About the Reader For DevOps, data engineers, machine learning engineers, and sysadmins with intermediate Python skills. About the Authors Bas Harenslak and Julian de Ruiter are data engineers with extensive experience using Airflow to develop pipelines for major companies. Bas is also an Airflow committer. Quotes An Airflow bible. Useful for all kinds of users, from novice to expert. - Rambabu Posa, Sai Aashika Consultancy An easy-to-follow exploration of the benefits of orchestrating your data pipeline jobs with Airflow. - Daniel Lamblin, Coupang The one reference you need to create, author, schedule, and monitor workflows with Apache Airflow. Clear recommendation. - Thorsten Weber, bbv Software Services AG By far the best resource for Airflow. - Jonathan Wood, LexisNexis

This IBM® Redbooks® publication covers IBM TS7700 R5.1. The IBM TS7700 is part of a family of IBM Enterprise tape products. This book is intended for system architects and storage administrators who want to integrate their storage systems for optimal operation. Building on over 20 years of virtual tape experience, the TS7770 supports the ability to store virtual tape volumes in an object store. The TS7700 supported off loading to physical tape for over two decades. Off loading to physical tape behind a TS7700 is utilized by hundreds of organizations around the world. By using the same hierarchical storage techniques, the TS7700 (TS7770 and TS7760) can also off load to object storage. Because object storage is cloud-based and accessible from different regions, the TS7700 Cloud Storage Tier support essentially allows the cloud to be an extension of the grid. As of this writing, the TS7700C supports the ability to off load to IBM Cloud® Object Storage and Amazon S3. This publication explains features and concepts that are specific to the IBM TS7700 as of release R5.1. The R5.1 microcode level provides IBM TS7700 Cloud Storage Tier enhancements, IBM DS8000® Object Storage enhancements, Management Interface dual control security, and other smaller enhancements. The R5.1 microcode level can be installed on the IBM TS7770 and IBM TS7760 models only. TS7700 provides tape virtualization for the IBM z environment. Tape virtualization can help satisfy the following requirements in a data processing environment: Improved reliability and resiliency Reduction in the time that is needed for the backup and restore process Reduction of services downtime that is caused by physical tape drive and library outages Reduction in cost, time, and complexity by moving primary workloads to virtual tape Increased efficient procedures for managing daily batch, backup, recall, and restore processing On-premises and off-premises object store cloud storage support as an alternative to physical tape for archive and disaster recovery New and existing capabilities of the TS7700 5.1 include the following highlights: Eight-way Grid Cloud, which consists of up to three generations of TS7700 Synchronous and asynchronous replication Full AES256 encryption for replication data that is in-flight and at-rest Tight integration with IBM Z and DFSMS policy management Optional target for DS8000 Transparent Cloud Tier using DFSMS DS8000 Object Store AES256 in-flight encryption and compression Optional Cloud Storage Tier support for archive and disaster recovery 16 Gb IBM FICON® throughput up to 5 GBps per TS7700 cluster IBM Z hosts view up to 3,968 common devices per TS7700 grid Grid access to all data independent of where it exists TS7770 Cache On-demand feature that is based capacity licensing TS7770 support of SSD within the VED server The TS7700T writes data by policy to physical tape through attachment to high-capacity, high-performance IBM TS1150, and IBM TS1140 tape drives that are installed in an IBM TS4500 or TS3500 tape library. The TS7770 models are based on high-performance and redundant IBM POWER9™ technology. They provide improved performance for most IBM Z tape workloads when compared to the previous generations of IBM TS7700.

This IBM® Redbooks® publication introduces the latest member of the IBM Z® platform, the IBM z15™. It includes information about the Z environment and how it helps integrate data and transactions more securely. It also provides insight for faster and more accurate business decisions. The z15 is a state-of-the-art data and transaction system that delivers advanced capabilities, which are vital to any digital transformation. The z15 is designed for enhanced modularity, and occupies an industry-standard footprint. It is offered as a single air-cooled 19-inch frame called the z15 T02, or as a multi-frame (1 to 4 19-inch frames) called the z15 T01. Both z15 models excel at the following tasks:: Using hybrid multicloud integration services Securing and protecting data with encryption everywhere Providing resilience with key to zero downtime Transforming a transactional platform into a data powerhouse Getting more out of the platform with operational analytics Accelerating digital transformation with agile service delivery Revolutionizing business processes Blending open source and IBM Z technologies This book explains how this system uses innovations and traditional Z strengths to satisfy growing demand for cloud, analytics, and open source technologies. With the z15 as the base, applications can run in a trusted, reliable, and secure environment that improves operations and lessens business risk.

Dive into the world of data engineering with 'Azure Data Engineering Cookbook' to master building efficient ETL workflows using Microsoft Azure Data services. Whether you're working on batch processing solutions or real-time analytics, this book is your guide to implementing effective, scalable data operations. What this Book will help me do Design and implement efficient ETL pipelines for batch and real-time processing on MS Azure. Understand the use of Azure Blob storage for managing large data sets. Ingest, process, and analyze data using tools like Azure Synapse and Databricks. Develop and secure automation pipelines using Azure Data Factory. Leverage Azure Stream Analytics for real-time data processing workflows. Author(s) Ahmad Osama and Nagaraj Venkatesan bring years of expertise in cloud solutions and data engineering. Renowned for their practical teaching approach, they have helped countless professionals master the intricacies of Azure. Their focus is on equipping readers with actionable skills for real-world data challenges. Who is it for? This book is ideal for data engineers and database professionals aiming to hone their expertise in advanced Azure data engineering tasks. Readers should have a working knowledge of Azure fundamentals and basic data engineering concepts. If you're a technical architect or ETL developer seeking to transition or enhance your skills in Azure's ecosystem, you'll find immense value here.

This IBM® Redpaper® publication is intended to facilitate the deployment and configuration of the IBM Spectrum® Scale based high-performance storage solutions for the scalable data and AI solutions on Amazon Web Services (AWS). Configuration, testing results, and tuning guidelines for running the IBM Spectrum Scale based high-performance storage solutions for the data and AI workloads on AWS are the focus areas of the paper. The LAB Validation was conducted with the Red Hat Linux nodes to IBM Spectrum Scale by using the various Amazon Elastic Compute Cloud (EC2) instances. Simultaneous workloads are simulated across multiple Amazon EC2 nodes running with Red Hat Linux to determine scalability against the IBM Spectrum Scale clustered file system. Solution architecture, configuration details, and performance tuning demonstrate how to maximize data and AI application performance with IBM Spectrum Scale on AWS.

In "Effortless App Development with Oracle Visual Builder," you will explore how to quickly design, develop, and deploy robust web and mobile applications using Oracle Visual Builder's intuitive drag-and-drop features. This book equips you with the know-how to simplify application development tasks, making it perfect for professionals looking to boost productivity. What this Book will help me do Master the core architecture and features of Oracle Visual Builder to develop real-world applications effectively. Learn to create, manage, and leverage business objects and connect to various SaaS APIs within your applications. Build scalable and secure web and mobile applications using practical examples and clear implementation guidelines. Discover best practices for application lifecycle management, debugging, and troubleshooting VB applications. Extend Oracle and non-Oracle SaaS applications through hands-on knowledge tailored to real-world scenarios. Author(s) None Jain is an experienced developer and technical writer specializing in Oracle Visual Builder and cloud-based application development. With years of hands-on experience building and deploying cloud applications, they bring expertise and a practical approach to education. Their engaging writing style focuses on enabling readers to learn and apply new skills confidently. Who is it for? This book is perfectly suited for developers, UI designers, and IT professionals who want to master Oracle Visual Builder for developing web and mobile applications. If you already have experience with technologies like JavaScript, UI frameworks, and REST APIs, and seek to create intuitive applications using a simplified interface, this book is for you. Whether you're in the early stages of learning VB or looking to refine your skills, this book serves as a valuable guide.

The opportunity to modernize and improve the enterprise data warehouse is one of the best reasons for moving your application to the cloud. A data warehouse can access a greater diversity of use cases and practices than is possible in an existing environment. In this report, researcher and analyst Stephen Swoyer offers a comprehensive overview of the benefits and challenges of implementing a cloud-based data warehouse. Senior IT decision makers, chief data officers, and data professionals will learn about the shifts and new trends in the data management landscape. Explore ways to improve data management, build a data warehouse strategy, and learn how to modernize a data warehouse effectively. Understand how AI, machine learning, self-service data integration, and built-in developer-oriented services have transformed the data warehouse role Use data warehouses to work with cloud-based data lakes for end-to-end data management and data governance Explore how data warehouse platforms as a service (PaaS) pave the way to automation Migrate, manage, and secure a data warehouse in a hybrid or multicloud environment

The IBM® TS7700 features a functional enhancement that allows for the TS7700 to act as an object store for transparent cloud tiering with IBM DS8000® (DS8K), DFSMShsm (HSM), and native DFSMSdss (DSS). This function can be used to move data sets directly from DS8000 to TS7700. This IBM Redpaper publication describes the client value, and how DFSMS, DS8000, and TS7700 are set up to enable and use the function.

Professional Azure SQL Managed Database Administration is a comprehensive guide to mastering data management with Azure's managed database services. Packed with real-world exercises and updated to cover the latest Azure features, this book provides actionable insights into migration, performance tuning, scaling, and securing Azure SQL databases. What this Book will help me do Master the configuration and pricing options for Azure SQL databases to make cost-effective choices. Learn the processes to provision new SQL databases or migrate existing on-premises SQL databases to Azure. Acquire skills in implementing high availability and disaster recovery for ensuring data resilience. Understand the strategies for monitoring, tuning, and optimizing the performance of Azure SQL databases. Discover techniques for scaling uses through elastic pools and securing databases comprehensively. Author(s) Ahmad Osama and Shashikant Shakya are experienced professionals in SQL Server and Azure SQL technologies. With decades of combined experience in database administration and cloud computing, they bring a depth of understanding to the content of this book. Their hands-on teaching approach is evident in the practical exercises and real-world scenarios included. Who is it for? This book is specifically tailored for database administrators, developers, and application developers looking to leverage Azure SQL databases. If you are tasked with migrating applications to the cloud or ensuring top performance and resilience for cloud databases, you will find this book highly valuable. Prior experience with on-premises SQL services will help contextualize the content, making it suitable for professionals with intermediate SQL experience. Readers aiming to deepen their Azure SQL expertise will also greatly benefit.

This Solution Redpaper™ publication explains how the features of IBM Cloud® Object Storage System reduces the effect of incidents on business data when combined with log analysis, deep inspection, and detection of threats that IBM QRadar SIEM provides. This paper also demonstrates how to integrate IBM Cloud Object Storage's access logs with IBM QRadar SIEM. An administrator can monitor, inspect, detect, and derive insights for identifying potential threats to the data that is stored on IBM Cloud Object Storage. Also, IBM QRadar SIEM can proactively trigger cyber resiliency workflow in IBM Cloud Object Storage remotely to protect the data based on threat detection. This publication is intended for chief technology officers, solution and security architects, and systems administrators.

Many organizations must protect their mission-critical applications in production, but security threats can also surface during the development and pre-production phases. Also, during deployment and production, insiders who manage the infrastructure that hosts critical applications can pose a threat given their super-user credentials and level of access to secrets or encryption keys. Organizations must incorporate secure design practices in their development operations and embrace DevSecOps to protect their applications from the vulnerabilities and threat vectors that can compromise their data and potentially threaten their business. IBM® Cloud Hyper Protect Services provide built-in data-at-rest and data-in-flight protection to help developers easily build secure cloud applications by using a portfolio of cloud services that are powered by IBM LinuxONE. The LinuxONE platform ensures that client data is always encrypted, whether at rest or in transit. This feature gives customers complete authority over sensitive data and associated workloads (which restricts access, even for cloud admins) and helps them meet regulatory compliance requirements. LinuxONE also allows customers to build mission-critical applications that require quick time to market and dependable rapid expansion. The purpose of this IBM Redbooks® publication is to: Introduce the IBM Hyper Protect Services that are running on IBM LinuxONE on the IBM Cloud™ and on-premises Provide high-level design architectures Describe deployment best practices Provide guides to getting started and examples of the use of the Hyper Protect Services The target audience for this book is IBM Hyper Protect Virtual Services technical specialists, IT architects, and system administrators.