Monitoring Overview For Ibm Spectrum Scale And Ibm Elastic Storage Server

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.

The IBM® Elastic Storage Server GUI provides an easy way to configure and monitor various features that are available with the IBM ESS system. It is a web application that runs on common web browsers, such as Chrome, Firefox, and Edge. The ESS GUI uses Java Script and Ajax technologies to enable smooth and desktop-like interfacing. This IBM Redpaper publication provides a broad understanding of the architecture and features of the ESS GUI. It includes information about how to install and configure the GUI and in-depth information about the use of the GUI options. The primary audience for this paper includes experienced and new users of the ESS system.

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.

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.

This IBM® RedpaperTM publication introduces and describes the IBM Elastic StorageTM Server as a scalable, high-performance data and file management solution. The solution is built on proven IBM SpectrumTM Scale technology, formerly IBM General Parallel File System (GPFSTM). IBM Elastic Storage Servers can be implemented for a range of diverse requirements, providing reliability, performance, and scalability. This publication helps you to understand the solution and its architecture and helps you to plan the installation and integration of the environment. The following combination of physical and logical components are required: Hardware Operating system Storage Network Applications This paper provides guidelines for several usage and integration scenarios. Typical scenarios include Cluster Export Services (CES) integration, disaster recovery, and multicluster integration. This paper addresses the needs of technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who must deliver cost-effective cloud services and big data solutions.

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.

Advancing the science of medicine by targeting a disease more precisely with treatment specific to each patient relies on access to that patient's genomics information and the ability to process massive amounts of genomics data quickly. Although genomics data is becoming a critical source for precision medicine, it is expected to create an expanding data ecosystem. Therefore, hospitals, genome centers, medical research centers, and other clinical institutes need to explore new methods of storing, accessing, securing, managing, sharing, and analyzing significant amounts of data. Healthcare and life sciences organizations that are running data-intensive genomics workloads on an IT infrastructure that lacks scalability, flexibility, performance, management, and cognitive capabilities also need to modernize and transform their infrastructure to support current and future requirements. IBM® offers an integrated solution for genomics that is based on composable infrastructure. This solution enables administrators to build an IT environment in a way that disaggregates the underlying compute, storage, and network resources. Such a composable building block based solution for genomics addresses the most complex data management aspect and allows organizations to store, access, manage, and share huge volumes of genome sequencing data. IBM SpectrumTM Scale is software-defined storage that is used to manage storage and provide massive scale, a global namespace, and high-performance data access with many enterprise features. IBM Spectrum ScaleTM is used in clustered environments, provides unified access to data via file protocols (POSIX, NFS, and SMB) and object protocols (Swift and S3), and supports analytic workloads via HDFS connectors. Deploying IBM Spectrum Scale and IBM Elastic StorageTM Server (IBM ESS) as a composable storage building block in a Genomics Next Generation Sequencing deployment offers key benefits of performance, scalability, analytics, and collaboration via multiple protocols. This IBM RedpaperTM publication describes a composable solution with detailed architecture definitions for storage, compute, and networking services for genomics next generation sequencing that enable solution architects to benefit from tried-and-tested deployments, to quickly plan and design an end-to-end infrastructure deployment. The preferred practices and fully tested recommendations described in this paper are derived from running GATK Best Practices work flow from the Broad Institute. The scenarios provide all that is required, including ready-to-use configuration and tuning templates for the different building blocks (compute, network, and storage), that can enable simpler deployment and that can enlarge the level of assurance over the performance for genomics workloads. The solution is designed to be elastic in nature, and the disaggregation of the building blocks allows IT administrators to easily and optimally configure the solution with maximum flexibility. The intended audience for this paper is technical decision makers, IT architects, deployment engineers, and administrators who are working in the healthcare domain and who are working on genomics-based workloads.

This IBM® Redbooks® publication provides information to help you with the sizing, configuration, and monitoring of hybrid cloud solutions using the transparent cloud tiering (TCT) functionality of IBM SpectrumTM Scale. IBM Spectrum ScaleTM is a scalable data, file, and object management solution that provides a global namespace for large data sets and several enterprise features. The IBM Spectrum Scale feature called transparent cloud tiering allows cloud object storage providers, such as IBM CloudTM Object Storage, IBM Cloud, and Amazon S3, to be used as a storage tier for IBM Spectrum Scale. Transparent cloud tiering can help cut storage capital and operating costs by moving data that does not require local performance to an on-premise or off-premise cloud object storage provider. Transparent cloud tiering reduces the complexity of cloud object storage by making data transfers transparent to the user or application. This capability can help you adapt to a hybrid cloud deployment model where active data remains directly accessible to your applications and inactive data is placed in the correct cloud (private or public) automatically through IBM Spectrum Scale policies. This publication is intended for IT architects, IT administrators, storage administrators, and those wanting to learn more about sizing, configuration, and monitoring of hybrid cloud solutions using IBM Spectrum Scale and transparent cloud tiering.