IBM Spectrum Scale Erasure Code Edition: Planning and Implementation Guide


Book Description

This IBM® Redpaper introduces the IBM Spectrum® Scale Erasure Code Edition (ECE) as a scalable, high-performance data and file management solution. ECE is designed to run on any commodity server that meets the ECE minimum hardware requirements. ECE provides all the functionality, reliability, scalability, and performance of IBM Spectrum Scale with the added benefit of network-dispersed IBM Spectrum Scale RAID, which provides data protection, storage efficiency, and the ability to manage storage in hyperscale environments that are composed from commodity hardware. In this publication, we explain the benefits of ECE and the use cases where we believe it fits best. We also provide a technical introduction to IBM Spectrum Scale RAID. Next, we explain the key aspects of planning an installation, provide an example of an installation scenario, and describe the key aspects of day-to-day management and a process for problem determination. We conclude with an overview of possible enhancements that are being considered for future versions of IBM Spectrum Scale Erasure Code Edition. Overall knowledge of IBM Spectrum Scale Erasure Code Edition is critical to planning a successful storage system deployment. This paper is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for delivering cost effective storage solutions. The goal of this paper is to describe the benefits of using IBM Spectrum Scale Erasure Code Edition for the creation of high performing storage systems.




IBM Spectrum Scale and IBM Elastic Storage System Network Guide


Book Description

High-speed I/O workloads are moving away from the SAN to Ethernet and IBM® Spectrum Scale is pushing the network limits. The IBM Spectrum® Scale team discovered that many infrastructure Ethernet networks that were used for years to support various applications are not designed to provide a high-performance data path concurrently to many clients from many servers. IBM Spectrum Scale is not the first product to use Ethernet for storage access. Technologies, such as Fibre Channel over Ethernet (FCoE), scale out NAS, and IP connected storage (iSCSI and others) use Ethernet though IBM Spectrum Scale as the leader in parallel I/O performance, which provides the best performance and value when used on a high-performance network. This IBM Redpaper publication is based on lessons that were learned in the field by deploying IBM Spectrum Scale on Ethernet and InfiniBand networks. This IBM Redpaper® publication answers several questions, such as, "How can I prepare my network for high performance storage?", "How do I know when I am ready?", and "How can I tell what is wrong?" when deploying IBM Spectrum Scale and IBM Elastic Storage® Server (ESS). This document can help IT architects get the design correct from the beginning of the process. It also can help the IBM Spectrum Scale administrator work effectively with the networking team to quickly resolve issues.




Implementation Guide for IBM Elastic Storage System 3000


Book Description

This IBM® Redbooks publication introduces and describes the IBM Elastic Storage® Server 3000 (ESS 3000) as a scalable, high-performance data and file management solution. The solution is built on proven IBM Spectrum® Scale technology, formerly IBM General Parallel File System (IBM GPFS). IBM Elastic Storage System 3000 is an all-Flash array platform. This storage platform uses NVMe-attached drives in ESS 3000 to provide significant performance improvements as compared to SAS-attached flash drives. This book provides a technical overview of the ESS 3000 solution and helps you to plan the installation of the environment. We also explain the use cases where we believe it fits best. Our goal is to position this book as the starting point document for customers that would use ESS 3000 as part of their IBM Spectrum Scale setups. This book is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for delivering cost-effective storage solutions with ESS 3000.




Implementation Guide for IBM Elastic Storage System 5000


Book Description

This IBM® Redbooks® publication introduces and describes the IBM Elastic Storage® Server 5000 (ESS 5000) as a scalable, high-performance data and file management solution. The solution is built on proven IBM Spectrum® Scale technology, formerly IBM General Parallel File System (IBM GPFS). ESS is a modern implementation of software-defined storage, making it easier for you to deploy fast, highly scalable storage for AI and big data. With the lightning-fast NVMe storage technology and industry-leading file management capabilities of IBM Spectrum Scale, the ESS 3000 and ESS 5000 nodes can grow to over YB scalability and can be integrated into a federated global storage system. By consolidating storage requirements from the edge to the core data center — including kubernetes and Red Hat OpenShift — IBM ESS can reduce inefficiency, lower acquisition costs, simplify storage management, eliminate data silos, support multiple demanding workloads, and deliver high performance throughout your organization. This book provides a technical overview of the ESS 5000 solution and helps you to plan the installation of the environment. We also explain the use cases where we believe it fits best. Our goal is to position this book as the starting point document for customers that would use the ESS 5000 as part of their IBM Spectrum Scale setups. This book is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for delivering cost-effective storage solutions with ESS 5000.




A Deployment Guide for IBM Spectrum Scale Unified File and Object Storage


Book Description

Because of the explosion of unstructured data that is generated by individuals and organizations, a new storage paradigm that is called object storage has been developed. Object storage stores data in a flat namespace that scales to trillions of objects. The design of object storage also simplifies how users access data, supporting new types of applications and allowing users to access data by using various methods, including mobile devices and web applications. Data distribution and management are also simplified, allowing greater collaboration across the globe. OpenStack Swift is an emerging open source object storage software platform that is widely used for cloud storage. IBM® Spectrum Scale, which is based on IBM General Parallel File System (IBM GPFSTM) technology, is a high-performance and proven product that is used to store data for thousands of mission-critical commercial installations worldwide. Throughout this IBM RedpaperTM publication, IBM SpectrumTM Scale is used to refer to GPFS. The examples in this paper are based on IBM Spectrum ScaleTM V4.2.2. IBM Spectrum Scale also automates common storage management tasks, such as tiering and archiving at scale. Together, IBM Spectrum Scale and OpenStack Swift provide an enterprise-class object storage solution that efficiently stores, distributes, and retains critical data. This paper provides instructions about setting up and configuring IBM Spectrum Scale Object Storage that is based on OpenStack Swift. It also provides an initial set of preferred practices that ensure optimal performance and reliability. This paper is intended for administrators who are familiar with IBM Spectrum Scale and OpenStack Swift components.




Cloud Data Sharing with IBM Spectrum Scale


Book Description

This IBM® RedpaperTM publication provides information to help you with the sizing, configuration, and monitoring of hybrid cloud solutions using the Cloud data sharing feature of IBM Spectrum ScaleTM. IBM Spectrum Scale, formerly IBM General Parallel File System (IBM GPFSTM), is a scalable data and file management solution that provides a global namespace for large data sets along with several enterprise features. Cloud data sharing allows for the sharing and use of data between various cloud object storage types and IBM Spectrum Scale. Cloud data sharing can help with the movement of data in both directions, between file systems and cloud object storage, so that data is where it needs to be, when it needs to be there. This paper is intended for IT architects, IT administrators, storage administrators, and those who want to learn more about sizing, configuration, and monitoring of hybrid cloud solutions using IBM Spectrum Scale and Cloud data sharing.




IBM Software-Defined Storage Guide


Book Description

Today, new business models in the marketplace coexist with traditional ones and their well-established IT architectures. They generate new business needs and new IT requirements that can only be satisfied by new service models and new technological approaches. These changes are reshaping traditional IT concepts. Cloud in its three main variants (Public, Hybrid, and Private) represents the major and most viable answer to those IT requirements, and software-defined infrastructure (SDI) is its major technological enabler. IBM® technology, with its rich and complete set of storage hardware and software products, supports SDI both in an open standard framework and in other vendors' environments. IBM services are able to deliver solutions to the customers with their extensive knowledge of the topic and the experiences gained in partnership with clients. This IBM RedpaperTM publication focuses on software-defined storage (SDS) and IBM Storage Systems product offerings for software-defined environments (SDEs). It also provides use case examples across various industries that cover different client needs, proposed solutions, and results. This paper can help you to understand current organizational capabilities and challenges, and to identify specific business objectives to be achieved by implementing an SDS solution in your enterprise.




Monitoring Overview for IBM Spectrum Scale and IBM Elastic Storage Server


Book Description

IBM® Spectrum Scale is software-defined storage for high-performance, large-scale workloads. IBM SpectrumTM Scale (formerly IBM General parallel file system or GPFS) is a scalable data and file management solution that provides a global namespace for large data sets along with several enterprise features. IBM Spectrum ScaleTM is used in clustered environments and provides file protocol (POSIX, NFS, and SMB) and object protocol (Swift and S3) access methods. IBM Elastic StorageTM Server (ESS) is a software-defined storage system that is built upon proven IBM Power SystemsTM, IBM Spectrum Scale software, and storage enclosures. ESS allows for capacity scale up or scale out for performance in modular building blocks, which enables sharing for large data sets across workloads with unified storage pool for file, object, and Hadoop workloads. ESS uses erasure coding-based declustered RAID technology that was developed by IBM to rebuild failed disks in few minutes instead of days. IBM ESS and IBM Spectrum Scale are implemented in scalable environments that are running enterprise workloads. ESS and IBM Spectrum Scale are key components of the enterprise infrastructure. With growing expectations of availability on enterprise infrastructures, monitoring IBM Spectrum Scale, ESS health, and performance is an important function for any IT administrator. This IBM RedpaperTM publication provides an overview of key parameters and methods of IBM Spectrum Scale and ESS monitoring. The audience for this document is IT architects, IT administrators, storage administrators, and users who want to learn more about the administration of an IBM Spectrum Scale and ESS system. This document can be used to monitorfor the environments with IBM Spectrum Scale version 4.2.2.X0 or later. The examples in the document are based on IBM Spectrum Scale 4.2.2.X and ESS 5.0.X.X versions.




IBM Spectrum Discover: Metadata Management for Deep Insight of Unstructured Storage


Book Description

This IBM® Redpaper publication provides a comprehensive overview of the IBM Spectrum® Discover metadata management software platform. We give a detailed explanation of how the product creates, collects, and analyzes metadata. Several in-depth use cases are used that show examples of analytics, governance, and optimization. We also provide step-by-step information to install and set up the IBM Spectrum Discover trial environment. More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data such as: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.




Enterprise Cloud Strategy


Book Description

How do you start? How should you build a plan for cloud migration for your entire portfolio? How will your organization be affected by these changes? This book, based on real-world cloud experiences by enterprise IT teams, seeks to provide the answers to these questions. Here, you’ll see what makes the cloud so compelling to enterprises; with which applications you should start your cloud journey; how your organization will change, and how skill sets will evolve; how to measure progress; how to think about security, compliance, and business buy-in; and how to exploit the ever-growing feature set that the cloud offers to gain strategic and competitive advantage.