IBM Storage for Red Hat OpenShift Container Platform is a comprehensive container-ready solution that includes all the hardware & software components necessary to setup and/or expand your Red Hat OpenShift Container Platform V3.11 environment. IBM Storage, bringing enterprise data services to containers. In this blueprint, learn how to: • Combine the benefits of IBM Systems with the performance of IBM Storage solutions so that you can deliver the right services to your clients today! • Build a 24 by 7 by 365 enterprise class private cloud with Red Hat OpenShift Container Platform • Leverage enterprise class services such as NVMe based flash performance, high data availability, and advanced container security IBM Storage for Red Hat OpenShift Container Platform: designed for your DevOps environment for on-premises deployment with easy-to-consume components built to perform and scale for your enterprise. Simplify your journey to cloud with pre-tested and validated blueprints engineered to enable rapid deployment and peace of mind as you move to a hybrid multicloud environment. You now have the capabilities.

This IBM® Redpaper publication provides an update to the original description of IBM Reference Architecture for Genomics. This paper expands the reference architecture to cover all of the major vertical areas of healthcare and life sciences industries, such as genomics, imaging, and clinical and translational research. The architecture was renamed IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences to reflect the fact that it incorporates key building blocks for high-performance computing (HPC) and software-defined storage, and that it supports an expanding infrastructure of leading industry partners, platforms, and frameworks. The reference architecture defines a highly flexible, scalable, and cost-effective platform for accessing, managing, storing, sharing, integrating, and analyzing big data, which can be deployed on-premises, in the cloud, or as a hybrid of the two. IT organizations can use the reference architecture as a high-level guide for overcoming data management challenges and processing bottlenecks that are frequently encountered in personalized healthcare initiatives, and in compute-intensive and data-intensive biomedical workloads. This reference architecture also provides a framework and context for modern healthcare and life sciences institutions to adopt cutting-edge technologies, such as cognitive life sciences solutions, machine learning and deep learning, Spark for analytics, and cloud computing. To illustrate these points, this paper includes case studies describing how clients and IBM Business Partners alike used the reference architecture in the deployments of demanding infrastructures for precision medicine. This publication targets technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for providing life sciences solutions and support.

This IBM® Redbooks® publication provides a security and compliance solution that is optimized for virtualized environments on IBM Power Systems™ servers, running IBM PowerVM® and IBM AIX®. Security control and compliance are some of the key components that are needed to defend the virtualized data center and cloud infrastructure against ever evolving new threats. The IBM business-driven approach to enterprise security that is used with solutions, such as IBM PowerSC™, makes IBM the premier security vendor in the market today. The book explores, tests, and documents scenarios using IBM PowerSC that leverage IBM Power Systems servers architecture and software solutions from IBM to help defend the virtualized data center and cloud infrastructure against ever evolving new threats. This publication helps IT and Security managers, architects, and consultants to strengthen their security and compliance posture in a virtualized environment running IBM PowerVM.

As workloads are being offloaded to IBM® LinuxONE based cloud environments, it is important to ensure that these workloads and environments are secure. This IBM Redbooks® publication describes the necessary steps to secure your environment from the hardware level through all of the components that are involved in a LinuxONE cloud infrastructure that use Linux and IBM z/VM®. The audience for this book is IT architects, IT Specialists, and those users who plan to use LinuxONE for their cloud environments.

This IBM® Redpaper™ publication shows you how to deploy a database instance within a container using an IBM Cloud™ Private cluster on IBM Z®. A preinstalled IBM Spectrum™ Scale 5.0.3 cluster file system provides back-end storage for the persistent volumes bound to the database. A container is a standard unit of software that packages code and all its dependencies, so the application runs quickly and reliably from one computing environment to another. By default, containers are ephemeral. However, stateful applications, such as databases, require some type of persistent storage that can survive service restarts or container crashes. IBM provides several products helping organizations build an environment on an IBM Z infrastructure to develop and manage containerized applications, including dynamic provisioning of persistent volumes. As an example for a stateful application, this paper describes how to deploy the relational database MariaDB using a Helm chart. The IBM Spectrum Scale V5.0.3 cluster file system is providing back-end storage for the persistent volumes. This document provides step-by-step guidance regarding how to install and configure the following components: IBM Cloud Private 3.1.2 (including Kubernetes) Docker 18.03.1-ce IBM Storage Enabler for Containers 2.0.0 and 2.1.0 This Redpaper demonstrates how we set up the example for a stateful application in our lab. The paper gives you insights about planning for your implementation. IBM Z server hardware, the IBM Z hypervisor z/VM®, and the IBM Spectrum Scale cluster file system are prerequisites to set up the example environment. The Redpaper is written with the assumption that you have familiarity with and basic knowledge of the software products used in setting up the environment. The intended audience includes the following roles: Storage administrators IT/Cloud administrators Technologists IT specialists

Big data and advanced analytics have increasingly moved to the cloud as organizations pursue actionable insights and data-driven products using the growing amounts of information they collect. But few companies have truly operationalized data so it’s usable for the entire organization. With this pragmatic ebook, engineers, architects, and data managers will learn how to build and extract value from a data lake in the cloud and leverage the compute power and scalability of a cloud-native data platform to put your company’s vast data trove into action. Holden Ackerman and Jon King of Qubole take you through the basics of building a data lake operation, from people to technology, employing multiple technologies and frameworks in a cloud-native data platform. You'll dive into the tools and processes you need for the entire lifecycle of a data lake, from data preparation, storage, and management to distributed computing and analytics. You’ll also explore the unique role that each member of your data team needs to play as you migrate to your cloud-native data platform. Leverage your data effectively through a single source of truth Understand the importance of building a self-service culture for your data lake Define the structure you need to build a data lake in the cloud Implement financial governance and data security policies for your data lake through a cloud-native data platform Identify the tools you need to manage your data infrastructure Delineate the scope, usage rights, and best tools for each team working with a data lake—analysts, data scientists, data engineers, and security professionals, among others

When data-driven applications fail, identifying the cause is both challenging and time-consuming—especially as data pipelines become more and more complex. Hunting for the root cause of application failure from messy, raw, and distributed logs is difficult for performance experts and a nightmare for data operations teams. This report examines DataOps processes and tools that enable you to manage modern data pipelines efficiently. Author Ted Malaska describes a data operations framework and shows you the importance of testing and monitoring to plan, rebuild, automate, and then manage robust data pipelines—whether it’s in the cloud, on premises, or in a hybrid configuration. You’ll also learn ways to apply performance monitoring software and AI to your data pipelines in order to keep your applications running reliably. You’ll learn: How performance management software can reduce the risk of running modern data applications Methods for applying AI to provide insights, recommendations, and automation to operationalize big data systems and data applications How to plan, migrate, and operate big data workloads and data pipelines in the cloud and in hybrid deployment models

Professional Azure SQL Database Administration serves as your comprehensive guide to mastering the management and optimization of cloud-based Azure SQL Database solutions. With the differences and unique features of Azure SQL Database compared to the on-premise SQL Server, this book offers a clear roadmap to efficiently migrate, secure, scale, and maintain these databases in the cloud. What this Book will help me do Understand the differences between Azure SQL Database and on-premise SQL Server and their practical implications. Learn techniques to migrate existing SQL Server databases to Azure SQL Database seamlessly. Discover advanced ways to optimize database performance and scalability leveraging cloud capabilities. Master security strategies for Azure SQL databases, including backup, disaster recovery, and automated tasks. Develop proficiency in using tools such as PowerShell to automate and manage routine database administration tasks. Author(s) Ahmad Osama is an experienced database professional and author specializing in SQL Server and Azure SQL Database administration. With a robust background in database migration, maintenance, and performance tuning, Ahmad expertly bridges the gap between theory and practice. His approachable writing style makes complex database topics accessible to professionals seeking to expand their expertise. Who is it for? Professional Azure SQL Database Administration is an essential resource for database administrators, developers, and IT professionals keen on developing their knowledge about Azure SQL Database administration and cloud database solutions. Whether you're transitioning from traditional SQL Server environments or looking to optimize your database strategies in the cloud, this book caters to professionals with intermediate to advanced experience in database management and programming with SQL.

This IBM® Redguide™ publication describes big data and analytics deployments that are built on IBM Spectrum Scale™. IBM Spectrum Scale is a proven enterprise-level distributed file system that is a high-performance and cost-effective alternative to Hadoop Distributed File System (HDFS) for Hadoop analytics services. IBM Spectrum Scale includes NFS, SMB, and Object services and meets the performance that is required by many industry workloads, such as technical computing, big data, analytics, and content management. IBM Spectrum Scale provides world-class, web-based storage management with extreme scalability, flash accelerated performance, and automatic policy-based storage tiering from flash through disk to the cloud, which reduces storage costs up to 90% while improving security and management efficiency in cloud, big data, and analytics environments. This Redguide publication is intended for technical professionals (analytics consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for providing Hadoop analytics services and are interested in learning about the benefits of the use of IBM Spectrum Scale as an alternative to HDFS.

Today's global organizations depend on the ability to unlock business insights from massive volumes of data. Now, with IBM® FlashSystem 900 Model AE3, they can make faster decisions based on real-time insights. Thus, they unleash the power of demanding applications, including these: Online transaction processing (OLTP) and analytical databases Virtual desktop infrastructures (VDIs) Technical computing applications Cloud environments Easy to deploy and manage, IBM FlashSystem® 900 Model AE3 is designed to accelerate the applications that drive your business. Powered by IBM FlashCore® Technology, IBM FlashSystem Model AE3 provides the following characteristics: Accelerate business-critical workloads, real-time analytics, and cognitive applications with the consistent microsecond latency and extreme reliability of IBM FlashCore technology Improve performance and help lower cost with new inline data compression Help reduce capital and operational expenses with IBM enhanced 3D triple-level cell (3D TLC) flash Protect critical data assets with patented IBM Variable Stripe RAID™ Power faster insights with IBM FlashCore including hardware-accelerated nonvolatile memory (NVM) architecture, purpose-engineered IBM MicroLatency® modules and advanced flash management FlashSystem 900 Model AE3 can be configured in capacity points as low as 14.4 TB to 180 TB usable and up to 360 TB effective capacity after RAID 5 protection and compression. You can couple this product with either 16 Gbps, 8 Gbps Fibre Channel, 16 Gbps NVMe over Fibre Channel, or 40 Gbps InfiniBand connectivity. Thus, the IBM FlashSystem 900 Model AE3 provides extreme performance to existing and next generation infrastructure.

This document is intended to facilitate the deployment of the scalable hybrid cloud solution for data agility and collaboration using IBM® Spectrum Scale across multiple public clouds. To complete the tasks it describes, you must understand IBM Spectrum Scale and IBM Spectrum Scale Active File Management (AFM). The information in this document is distributed on an 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 Scale Active File Management are supported and entitled, and where the issues are specific to a blueprint implementation.

This document is intended to facilitate the deployment of the Multicloud Solution for Business Continuity and Storage as service by using IBM Spectrum Virtualize for Public Cloud on Amazon Web Services (AWS). To complete the tasks it describes, you must understand IBM FlashSystem 9100, IBM Spectrum Virtualize for Public Cloud, IBM Spectrum Connect, VMware vRealize Orchestrator, and vRealize Automation and AWS Cloud. 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 Storwize or IBM FlashSystem storage devices are supported and entitled and where the issues are specific to a blueprint implementation.

Managers and staff responsible for planning, hiring, and allocating resources need to understand how streaming data can fundamentally change their organizations. Companies everywhere are disrupting business, government, and society by using data and analytics to shape their business. Even if you don’t have deep knowledge of programming or digital technology, this high-level introduction brings data streaming into focus. You won’t find math or programming details here, or recommendations for particular tools in this rapidly evolving space. But you will explore the decision-making technologies and practices that organizations need to process streaming data and respond to fast-changing events. By describing the principles and activities behind this new phenomenon, author Andy Oram shows you how streaming data provides hidden gems of information that can transform the way your business works. Learn where streaming data comes from and how companies put it to work Follow a simple data processing project from ingesting and analyzing data to presenting results Explore how (and why) big data processing tools have evolved from MapReduce to Kubernetes Understand why streaming data is particularly useful for machine learning projects Learn how containers, microservices, and cloud computing led to continuous integration and DevOps

This Blueprint is intended to define the infrastructure that is required for a blockchain remote peer and to facilitate the deployment of IBM Blockchain Platform on IBM Cloud Private using that infrastructure. This infrastructure includes the necessary document handler components, such as IBM Blockchain Document Store, and covers the required storage for on-chain and off-chain blockchain data. To complete these tasks, you must have a basic understanding of each of the used components or have access the correct educational material to gain that knowledge.

This IBM® Redbooks® Product Guide is an overview of the main characteristics, features, and technology that are used in IBM FlashSystem® A9000Model 425, with IBM FlashSystem A9000 Software V12.3.2. Software version 12.3.2, with Hyper-Scale Manager version 5.6 or later, introduces support for VLAN tagging and port trunking. IBM FlashSystem A9000 storage system uses the IBM FlashCore® technology to help realize higher capacity and improved response times over disk-based systems and other competing flash and solid-state drive (SSD)-based storage. The extreme performance of IBM FlashCore technology with a grid architecture and comprehensive data reduction creates one powerful solution. Whether you are a service provider who requires highly efficient management or an enterprise that is implementing cloud on a budget, FlashSystem A9000 provides consistent and predictable microsecond response times and the simplicity that you need. The A9000 features always on data reduction and now offers intelligent capacity management for deduplication. As a cloud optimized solution, FlashSystem A9000 suits the requirements of public and private cloud providers who require features, such as inline data deduplication, multi-tenancy, and quality of service. It also uses powerful software-defined storage capabilities from IBM Spectrum™ Accelerate, such as Hyper-Scale technology, VMware, and storage container integration.

This IBM® Redbooks® Product Guide is an overview of the main characteristics, features, and technology that are used in IBM FlashSystem® A9000R Model 415 and Model 425, with IBM FlashSystem A9000R Software V12.3.2. Software version 12.3.2, with Hyper-Scale Manager version 5.6 or later, introduces support for VLAN tagging and port trunking.. IBM FlashSystem A9000R is a grid-scale, all-flash storage platform designed for industry leaders with rapidly growing cloud storage and mixed workload environments to help drive your business into the cognitive era. FlashSystem A9000R provides consistent, extreme performance for dynamic data at scale, integrating the microsecond latency and high availability of IBM FlashCore® technology. The rack-based offering comes integrated with the world class software features that are built with IBM Spectrum™ Accelerate. For example, comprehensive data reduction, including inline pattern removal, data deduplication, and compression, helps lower total cost of ownership (TCO) while the grid architecture and IBM Hyper-Scale framework simplify and automate storage administration. The A9000R features always on data reduction and now offers intelligent capacity management for deduplication. Ready for the cloud and well-suited for large deployments, FlashSystem A9000R delivers predictable high performance and ultra-low latency, even under heavy workloads with full data reduction enabled. As a result, the grid-scale architecture maintains this performance by automatically self-optimizing workloads across all storage resources without manual intervention.

"Learning Elastic Stack 7.0" introduces you to the tools and techniques of Elastic Stack, covering Elasticsearch, Logstash, Beats, and Kibana. With clear explanations and practical examples, this book helps you grasp the 7.0 version's new features and capabilities, empowering you to build and deploy robust, real-time data processing applications. What this Book will help me do Gain the necessary skills to install and configure Elastic Stack for professional use. Master the data handling capabilities of Elasticsearch for distributed search and analytics. Develop expertise in creating data pipelines with Logstash and other ingestion tools. Learn to utilize Kibana to visualize and interpret complex datasets. Acquire knowledge of deploying Elastic Stack solutions both on-premise and in cloud environments. Author(s) Pranav Shukla and Sharath Kumar M N are experienced software engineers and data professionals with a profound knowledge of databases, distributed systems, and cloud architectures. They specialize in educating developers through structured guidance and proven methodologies related to data handling and visualization. Who is it for? This book is designed for software engineers, data analysts, and technical architects interested in learning the Elastic Stack tools from the ground up. Readers familiar with database concepts but new to Elastic Stack will find this book particularly helpful. Advanced users seeking to understand the updates in Elastic Stack 7.0 are also a complementary audience. If you wish to apply Elastic Stack to real-time data processing and analytics, this book provides a strong foundation.

Every decade since the 1960s, researchers at companies like IBM, Amazon, and many others have introduced major new frameworks and techniques to handle rising data management problems. This concise ebook explains how these new systems helped data science evolve quickly—from hierarchical and relational databases to big data and cloud computing to streaming and graph data. Computer scientist Paco Nathan shows members of your data science team how major companies created each of these data management systems not just to deal with new data types but also to take full advantage of the opportunities the data presented. Their efforts over the years have propelled an entire industry. This report covers the historical progression of data management topics including: Hierarchical databases—1960s mainframe batch systems are still used in finance, healthcare, manufacturing, energy, and other industries. Relational databases—these enabled faster transactions, mathematical optimization, and budgeting guarantees for many businesses. Big data—this includes relatively cheap horizontal scale-out systems for collecting huge amounts of customer data. Cloud computing—large companies began managing reliable, scalable, cost-effective data centers; Amazon turned the concept into a business. Cluster schedulers—managing horizontal clusters was difficult before schedulers such as Apache Mesos appeared. Streaming data—data continuously generated by different sources requires responses in "real time"—generally milliseconds.

This IBM® Redbooks® publication covers IBM TS7700 R4.2. 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 TS7760 now supports the ability to store virtual tape volumes in an object store. The TS7700 has 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. Using the same hierarchical storage techniques, the TS7700 can also off load to object storage. Given object storage is cloud based and accessible from different regions, the TS7760 Cloud Storage Tier support essentially allows the cloud to be an extension of the grid. As of the release of this document, the TS7760C supports the ability to off load to IBM Cloud Object Storage as well as Amazon S3. To learn about the TS7760 cloud storage tier function, planning, implementation, best practices, and support see IBM Redpaper IBM TS7760 R4.2 Cloud Storage Tier Guide, redp-5514 at: http://www.redbooks.ibm.com/abstracts/redp5514.html The IBM TS7700 offers a modular, scalable, and high-performance architecture for mainframe tape virtualization for the IBM Z® environment. It is a fully integrated, tiered storage hierarchy of disk and tape. This storage hierarchy is managed by robust storage management microcode with extensive self-management capability. It includes the following advanced functions: 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 More efficient procedures for managing daily backup and restore processing Infrastructure simplification through reduction of the number of physical tape libraries, drives, and media TS7700 delivers the following new capabilities: TS7760C supports the ability to off load to IBM Cloud Object Storage as well as Amazon S3 8-way Grid Cloud consisting of any generation of TS7700 Synchronous and asynchronous replication Tight integration with IBM Z and DFSMS policy management Optional Transparent Cloud Tiering Optional integration with physical tape Cumulative 16Gb FICON throughput up to 4.8GB/s 8 IBM Z hosts view up to 496 8 equivalent devices Grid access to all data independent of where it exists The TS7760T writes data by policy to physical tape through attachment to high-capacity, high-performance IBM TS1150 and IBM TS1140 tape drives installed in an IBM TS4500 or TS3500 tape library. The TS7760 models are based on high-performance and redundant IBM POWER8® technology. They provide improved performance for most IBM Z tape workloads when compared to the previous generations of IBM TS7700.

-update for Release 8.5 - IBM experts recognize the need for data protection, both from hardware or software failures, and also from physical relocation of hardware, theft, and retasking of existing hardware. The IBM DS8880 supports encryption-capable hard disk drives (HDDs) and flash drives. These Full Disk Encryption (FDE) drive sets are used with key management services that are provided by IBM Security Key Lifecycle Manager software or Gemalto SafeNet KeySecure to allow encryption for data at rest on a DS8880. Use of encryption technology involves several considerations that are critical for you to understand to maintain the security and accessibility of encrypted data. The IBM Security Key Lifecycle Manager software also supports Transparent Cloud Tiering (TCT) data object encryption, which is part of this publication. With TCT encryption, data is encrypted before it is transmitted to the Cloud. The data remains encrypted in cloud storage and is decrypted after it is transmitted back to the DS8000®. This IBM Redpaper™ publication contains information that can help storage administrators plan for disk and TCT data object encryption. It also explains how to install and manage the encrypted storage and how to comply with IBM requirements for using the IBM DS8000 encrypted disk storage system. This edition focuses on IBM Security Key Lifecycle Manager Version 3.0 which enables support Key Management Interoperability Protocol (KMIP) with the DS8000 Release 8.5 code or later and updated GUI for encryption functions. The publication also discusses support for data at rest encryption with Gemalto SafeNet KeySecure Version 8.3.2.