White Paper. Storage Intelligence in the Network: EMC s Perspective

Transcription

1 White Paper Storage Intelligence in the Network: EMC s Perspective Date 08/2003

2 Copyright 2003 EMC Corporation. All rights reserved. EMC believes the information in this publication is accurate as of its publication date. The information is subject to change without notice. THE INFORMATION IN THIS PUBLICATION IS PROVIDED AS IS. EMC CORPORATION MAKES NO REPRESENTATIONS OR WARRANTIES OF ANY KIND WITH RESPECT TO THE INFORMATION IN THIS PUBLICATION, AND SPECIFICALLY DISCLAIMS IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Use, copying, and distribution of any EMC software described in this publication requires an applicable software license. EMC 2, EMC, Symmetrix, AViiON, CLARiiON, CLARalert, DG, DG/UX, Navisphere, PowerPath, ResourcePak, VisualSAN, and The EMC Effect are registered trademarks and EMC Automated Networked Storage, EMC ControlCenter, EMC Developers Program, EMC Enterprise Storage, EMC Enterprise Storage Network, EMC Enterprise Storage Specialist, EMCLink, EMC OnCourse, EMC Orbit, EMC Proven, The EMC Effect Alliance, the EMC Information Orb, Access Logix, Application Transparent Failover, AutoIS, Automated Resource Manager, AVALONidm, C-Clip, CacheStorm, Celerra, Celerra Replicator, Centera, CentraStar, CLARevent, Connectrix, CopyCross, CopyPoint, CrosStor, Direct Matrix, Direct Matrix Architecture, EDM, E-Infostructure, E-Lab, Enginuity, FarPoint, FLARE, GeoSpan, HighRoad, InfoMover, MirrorView, OnAlert, PowerVolume, RepliCare, SafeLine, SAN Manager, SDMS, SnapSure, SnapView, SnapView/IP, SRDF, StorageScope, SymmAPI, SymmEnabler, TimeFinder, Universal Data Tone, WideSky, and where information lives are trademarks of EMC Corporation. All other trademarks used herein are the property of their respective owners. H1019 Storage Intelligence in the Network: EMC s Perspective 1

3 Table of Contents Introduction...3 Examining the Storage Software Evolution...3 Intelligence in Today s Storage Network Environment...3 EMC s Perspective on Intelligence in the Network...4 The Network Application Environment...5 What Storage Application Functionality Will Arrive in the Network?...5 Storage Presentation...5 Replication...6 Business Problems Addressed by Intelligent Networks...6 Summary...7 Storage Intelligence in the Network: EMC s Perspective 2

4 Introduction The prospect of moving applications into the storage network has been touted as the next major evolution in the storage industry. Expectations and promises are being created such as cheap and easy replication between any storage device, delivery of true storage virtualization, and various other solutions that provide the answers to all today s storage woes. Given the hype, it is hard for IT managers and architects to sort out the myth from the reality. This paper examines the evolution of intelligence in the network, contrasts today s architectures with emerging intelligent architectures, and presents EMC s view of what application functionality should move into the network. Examining the Storage Software Evolution Looking back at the open systems direct-attached storage model, most storage intelligence was located at the server or host. By the early 1990, however, this model was experiencing challenges in meeting the increasing demands for scale, manageability, and business continuity demanded by IT organizations. Enter intelligent storage arrays that enabled greater consolidation and scale through dramatic increases in storage performance, as well as advanced functions such as local and remote data replications. New capabilities were added to meet the emerging demands of storage infrastructures. As the quantity of information companies stored continued to soar, even these architectures were unable to meet the need for even greater consolidation, even easier management, and more efficient use of resources. Thus, storage area networks (SANs) began to emerge, which soon led to the emergence of intelligence at the network level to meet the new challenges introduced by networking servers to their storage. A key point to note is that each evolution of storage networking involved the addition of new capabilities to solve the emerging challenges of the old architectures. It makes sense to expect the same of intelligent storage networks they will need to add new capabilities (not re-create old ones) in order to solve tomorrow s storage infrastructure challenges. The new intelligent switching and routing products that are starting to appear in the market add application-aware, layer-3 technology to storage networks, providing a platform for even more intelligence to migrate into the network layer. At this point, we have intelligence distributed at all levels of the storage hierarchy in management software, the HBAs, the device drivers, the network, and the storage devices. The next logical question is how to optimize and leverage the placement of intelligence to maximize the benefit to the business. To answer this question, we need to briefly discuss how intelligence is currently distributed. Intelligence in Today s Storage Network Environment Figure 1 depicts today s storage network environment. Today, there is storage-related functionality distributed across the server, network and storage. Storage Network Server Figure 1: Intelligence in Storage Networks Today Storage Intelligence in the Network: EMC s Perspective 3

5 Examples of some of today s intelligent storage functions found on the server, network, and storage array include the following: Server Network Storage Array Path optimization Trunking Homogeneous data replication Volume management Performance Analysis Local and remote replication Path Failover Address scaling Heterogeneous Host Attach Zoning Name Server RAID Cache Storage optimization Storage virtualization EMC s Perspective on Intelligence in the Network Going forward then, where should intelligence ultimately reside? There are some approaches that are headed down the wrong path by taking all the storage functionality that exists today and moving it to the network. These approaches are suboptimal because in many cases they are purporting to solve problems that have already been solved, and in most cases they fail to leverage existing technology. The proper guiding principal for distributing intelligence is actually quite simple and intuitive: intelligence belongs in a storage network closest to what it controls: STORAGE: The intelligence to manage and manipulate data at the LUN or the volume level should reside closest to the storage array. NETWORK: Intelligence to perform functions across the whole network should reside near network switching points. SERVER: Application intelligence should reside in the server, while simultaneously reaching out to all other points of intelligence in the network to ensure service levels. Figure 2 summarizes the statements above and depicts how over time, intelligence will move from servers to the network. Storage Data Preservation Functions Network Data Delivery Functions Figure 2: Intelligence Moves Closer to What It Controls Server Application Functions Storage Intelligence in the Network: EMC s Perspective 4

6 The Network Application Environment So as we have seen, some intelligence will relocate to the network and some new functionality will appear in the network. New platforms and innovative software development will make that possible. Figure 3 depicts the intelligent network application environment. Software Network Hosted Storage Applications Network Application Infrastructure Storage Delivery Services Open Intelligent Network API Intelligent Switch Base Network Services Multi-protocol Connectivity Trunking, Diagnostics, Performance Analysis, Nameserver Fibre Channel, iscsi, FCIP Figure 3: Network Application Environment The bottom three layers in Figure 3, Multi-protocol Connectivity, Base Network Services, and the Network Application Infrastructure represent the architecture of the intelligent network platform emerging from companies like Cisco and Brocade. The development plans of the Cisco MDS 9000 series of directors and switches and Brocade s Silkworm Fabric Application Platform are examples of platforms for the future that promise storage network application capabilities. Such intelligent storage platforms enable EMC to extend the value and capabilities of its storage solutions. Cisco and Brocade will be delivering multi-protocol connectivity in the same box along with basic network services like ISL Trunking, VSANs, performance monitoring, zoning, etc. The Network Application Infrastructure is where the intelligent applications will reside. Such platforms provide the ability for a company like EMC and other ISVs to program these devices to manage the routing, classification, and delivery of data. On top of that infrastructure, network-based storage applications are created. These storage applications will control and dynamically modify what s happening within the network. What Storage Application Functionality Will Arrive in the Network? Storage application functionality that will arrive in the network falls into two basic categories:! Storage Presentation (sometimes called virtualization )! Replication Storage Presentation Storage presentation essentially means the way LUNs get presented to the host and the ability to aggregate or split them. A great deal of industry discussion has been generated on this topic under the heading of virtualization. This capability can be accomplished today within a single storage array. Virtualization is already being done by EMC s Symmetrix and CLARiiON storage arrays today. These arrays create virtual disks out of physical disks, hiding from the user physical details in order to improve performance, manageability, and availability at a subsystem level. Doing virtualization at the network level would add a new layer of abstraction that will span storage subsystems. The important point to note is that the ideal implementation of functionality in the network both complements and extends the capabilities present in the arrays themselves. Storage Intelligence in the Network: EMC s Perspective 5

7 For example, a CLARiiON array can logically combine and split physical disks to present a completely different (logical) mapping of LUNs to the servers connected to it. In smaller or departmentalized environments, this is typically sufficient since a single storage array may be able to carry enough capacity to meet the needs of the department. Thus, virtualization within the array in many cases is good enough. However, as information storage needs grow and the need to greater centralize and consolidate storage infrastructures continues, there is a growing demand to create a broader scale for LUN presentation. Network-based storage presentation services offer the ability to extend the LUN presentation currently being accomplished within arrays today and expand it across the entire fabric. In this scenario, LUNs could be aggregated across different arrays to better utilize the storage capacity available in the infrastructure. Network-based storage presentation makes storage pooling achievable. Storage arrays could be combined logically such that they function as a single pool of storage. Replication Replication can be divided into two basic classes:! Local replication of data occurs within a given storage array! Remote replication of data occurs from one storage array to another Focusing on local replication, today s storage arrays have both physical and logical volume replication functions. Physical volume replication (e.g., EMC s TimeFinder for Symmetrix) creates a full copy of the volume that can either be separated and synchronized, or separated from the original to operate and be modified stand-alone (and resynchronized back if desired). Logical volume replication (e.g., EMC s SnapView for CLARiiON) creates a logical view of a point-in-time copy of the original volume by combining the original data with tracked changes since the creation (or snap) of the logical volume. While these capabilities are offered in storage arrays today, through a network implementation, this concept could be extended to provide logical volume replication across arrays. Again, this would be used to more efficiently utilize the available storage capacity. For example, if multiple logical copies are required to enable easy restoration of files between full backups, this logical copy data could be stored on a separate, less-expensive, lower service-level array, thereby matching infrastructure spending to the service level required. Remote replication (between arrays) is available on storage arrays today typically in homogeneous configurations (i.e., both ends of the replication are the same type of storage array) in either synchronous or asynchronous modes. However, as environments scale and the need to fine tune service levels with business need increases, new capabilities are being demanded by data center and storage administrators. Network-based remote replication offers the potential to extend today s capabilities. In one such example, network-based replication could enable replication between arrays of different types (heterogeneous replication) in order to reduce costs at a disaster recovery site by using less-expensive (lower service-level) storage where the data is there only for emergencies and not primary operation. Another example is the ability to transparently migrate data between arrays to enable seamless operation during technology upgrades. In both cases, network-based replication provides a more cost-efficient infrastructure that matches the technology spend with the business need. Business Problems Addressed by Intelligent Networks With the relentless growth of data and increasing demands for application availability and performance, customers aren t asking for intelligent network applications per se, rather, they want solutions to their problems. From a customer s perspective, the value resulting from moving the storage intelligence into the network is threefold: 1. An extended choice of application, network, and storage platforms. 2. Improved capabilities around storage delivery services that will provide dynamic utilization of network bandwidth and network capabilities 3. Reduced TCO via reduced points of management, optimized storage, and offloaded servers. Storage Intelligence in the Network: EMC s Perspective 6

8 Summary As storage functionality starts to move out into the network, the network becomes more intelligent and the server s storage-related functionality diminishes. As the server becomes less aware of what s happening within the storage environment, this allows for much more flexibility within the SAN infrastructure. Expect EMC to continue to deliver new and evolutionary storage software that is built from a base of proven technology and utilizes standards where applicable. To begin laying the groundwork for intelligent storage networking, savvy storage administrators know to continue SAN deployments, implement comprehensive management to enable successful utilization of intelligent network capabilities, and partner with a company that has a proven track record and can deliver a complete solution. Storage Intelligence in the Network: EMC s Perspective 7