Adapted from: TRENDS AND ATTRIBUTES OF HORIZONTAL AND VERTICAL COMPUTING ARCHITECTURES

Similar documents
Sun N1: Storage Virtualization and Oracle

Experience the GRID Today with Oracle9i RAC

Database Services at CERN with Oracle 10g RAC and ASM on Commodity HW

An Oracle White Paper March Consolidation Using the Oracle SPARC M5-32 High End Server

<Insert Picture Here> Exadata MAA Best Practices Series Session 1: E-Business Suite on Exadata

VMware Virtual SAN Technology

Modular Platforms Market Trends & Platform Requirements Presentation for IEEE Backplane Ethernet Study Group Meeting. Gopal Hegde, Intel Corporation

The Right Choice for DR: Data Guard, Stretch Clusters, or Remote Mirroring. Ashish Ray Group Product Manager Oracle Corporation

Hardware and Software solutions for scaling highly threaded processors. Denis Sheahan Distinguished Engineer Sun Microsystems Inc.

HP visoko-performantna OLTP rješenja

An Oracle White Paper April Consolidation Using the Fujitsu M10-4S Server

Oracle Exadata X7. Uwe Kirchhoff Oracle ACS - Delivery Senior Principal Service Delivery Engineer

Storage Optimization with Oracle Database 11g

Virtualizing Oracle on VMware

Improving Blade Economics with Virtualization

PeerStorage Arrays Unequalled Storage Solutions

Server Networking e Virtual Data Center

EMC VMAX 400K SPC-2 Proven Performance. Silverton Consulting, Inc. StorInt Briefing

Got Isilon? Need IOPS? Get Avere.

Mellanox InfiniBand Solutions Accelerate Oracle s Data Center and Cloud Solutions

The Missing Piece of Virtualization. I/O Virtualization on 10 Gb Ethernet For Virtualized Data Centers

Horizontal Scaling Solution using Linux Environment

<Insert Picture Here> Enterprise Data Management using Grid Technology

This presentation is for informational purposes only and may not be incorporated into a contract or agreement.

Copyright 2012 EMC Corporation. All rights reserved.

Sun Lustre Storage System Simplifying and Accelerating Lustre Deployments

Oracle Exadata: The World s Fastest Database Machine

I/O Virtualization: Enabling New Architectures in the Data Center for Server and I/O Connectivity Sujoy Sen Micron

Best Practices for Setting BIOS Parameters for Performance

Microsoft E xchange 2010 on VMware

Isilon Scale Out NAS. Morten Petersen, Senior Systems Engineer, Isilon Division

<Insert Picture Here> Consolidate Oracle Applications on Oracle Exadata

Exadata Implementation Strategy

Data Centers and Cloud Computing

Data Centers and Cloud Computing. Slides courtesy of Tim Wood

Oracle Exadata: Strategy and Roadmap

<Insert Picture Here> Introducing Oracle WebLogic Server on Oracle Database Appliance

Data Centers and Cloud Computing. Data Centers

davidklee.net gplus.to/kleegeek linked.com/a/davidaklee

Software Defined Storage at the Speed of Flash. PRESENTATION TITLE GOES HERE Carlos Carrero Rajagopal Vaideeswaran Symantec

Oracle Database 10G. Lindsey M. Pickle, Jr. Senior Solution Specialist Database Technologies Oracle Corporation

Infrastructure Tuning

SAP HANA IBM x3850 X6

Interface Trends for the Enterprise I/O Highway

Solaris Engineered Systems

Capacity Planning for Application Design

Dell Fluid Data solutions. Powerful self-optimized enterprise storage. Dell Compellent Storage Center: Designed for business results

Scale-up with virtualised Integrity servers

Welcome. Jeremy Poon Territory Manager, VMware

Availability & Resource

SAP Applications on IBM XIV System Storage

Oracle RAC 10g Celerra NS Series NFS

QLogic 2500 Series FC HBAs Accelerate Application Performance

VERITAS SANPoint Storage Appliance Overview of an Open Platform for the Implementation of Intelligent Storage Server

HP NonStop Database Solution

Highly Scalable, Non-RDMA NVMe Fabric. Bob Hansen,, VP System Architecture

davidklee.net heraflux.com linkedin.com/in/davidaklee

Evolving To The Big Data Warehouse

Copyright 2012, Oracle and/or its affiliates. All rights reserved.

Processor Architecture and Interconnect

Disk-to-Disk backup. customer experience. Harald Burose. Architect Hewlett-Packard

Planning & Installing a RAC Database

Sun Fire V880 System Architecture. Sun Microsystems Product & Technology Group SE

Oracle IaaS, a modern felhő infrastruktúra

HP solutions for mission critical SQL Server Data Management environments

Dell Reference Configuration for Large Oracle Database Deployments on Dell EqualLogic Storage

Cisco HyperFlex All-Flash Systems for Oracle Real Application Clusters Reference Architecture

The Optimal CPU and Interconnect for an HPC Cluster

Copyright 2011, Oracle and/or its affiliates. All rights reserved.

THE EMC ISILON STORY. Big Data In The Enterprise. Deya Bassiouni Isilon Regional Sales Manager Emerging Africa, Egypt & Lebanon.

Performance & Scalability Testing in Virtual Environment Hemant Gaidhani, Senior Technical Marketing Manager, VMware

1 Copyright 2011, Oracle and/or its affiliates. All rights reserved. reserved. Insert Information Protection Policy Classification from Slide 8

IBM System p5 510 and 510Q Express Servers

Vblock Architecture. Andrew Smallridge DC Technology Solutions Architect

Future Routing Schemes in Petascale clusters

Increasing Performance of Existing Oracle RAC up to 10X

Pre-Bid Queries for NIT No. RECPDCL/TECH/SERVER-GED/e-Tender/ /186 Dated:

Power your planet. Optimizing the Enterprise Data Center POWER7 Powers a Smarter Infrastructure

Oracle Exadata. Smart Database Platforms - Dramatic Performance and Cost Advantages. Juan Loaiza Senior Vice President Oracle Database Systems

Oracle Database 11g Direct NFS Client Oracle Open World - November 2007

vsphere 4 The Best Platform for Business-Critical Applications Gaetan Castelein Sr Product Marketing Manager VMware, Inc.

Cold Storage: The Road to Enterprise Ilya Kuznetsov YADRO

Private Cloud Database Consolidation Name, Title

Network Design Considerations for Grid Computing

Hitachi Virtual Storage Platform Family

White Paper. EonStor GS Family Best Practices Guide. Version: 1.1 Updated: Apr., 2018

Oracle #1 for Data Warehousing. Data Warehouses Growing Rapidly Tripling In Size Every Two Years

Isilon Performance. Name

Mission Critical Storage and Data Protection in the Financial Services Industry

IBM FlashSystem. IBM FLiP Tool Wie viel schneller kann Ihr IBM i Power Server mit IBM FlashSystem 900 / V9000 Storage sein?

Design a Remote-Office or Branch-Office Data Center with Cisco UCS Mini

TRANSFORM YOUR APPLICATIONS

STORAGE CONSOLIDATION WITH IP STORAGE. David Dale, NetApp

HIGH PERFORMANCE COMPUTING FROM SUN

Agenda. AWS Database Services Traditional vs AWS Data services model Amazon RDS Redshift DynamoDB ElastiCache

Aurora, RDS, or On-Prem, Which is right for you

Storage Designed to Support an Oracle Database. White Paper

Conceptual Modeling on Tencent s Distributed Database Systems. Pan Anqun, Wang Xiaoyu, Li Haixiang Tencent Inc.

Introduction to Database Services

PACS and Its Components

Transcription:

Adapted from: TRENDS AND ATTRIBUTES OF HORIZONTAL AND VERTICAL COMPUTING ARCHITECTURES Tom Atwood Business Development Manager Sun Microsystems, Inc.

Takeaways Understand the technical differences between horizontal and vertical architectures Understand the difference between cluster for performance and cluster for availability Understand the financial impact of cluster databases (e.g., Oracle 9i RAC) 2

Agenda Industry trends Architectural definitions Performance issues TCO issues for database clusters Availability issues 3

N-tier Architecture Databases OLTP CRM/SCM/ERP App Servers Directory Servers Email Servers Web Services Firewall/VPN Proxy/Cache Tier 3 Tier 2 Tier 1 Tier 0 4

Customer Investment in Vertical and Horizontal Servers 5 Source: IDC, 2003

Server Usage by CPU Capacity 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 1-way 2-way 4-way 8-way 16-way 32-way 64-way+ Edge Application Database 6 Source: IDC, 2003

SMP Definition Symmetric multi-processing Or: shared memory multi-processing Shared pool of CPUs Single-large memory space One copy of the OS 7

Vertical and Horizontal Attributes Vertical Scaling Proc Mem Proc Mem I/O Memory Switch I/O Cache-coherent sharedmemory multi-processors (SMP) Tightly-coupled: high bandwidth, low latency Large, workloads: ad-hoc trans proc, data warehousing Shared pool processors Single large memory Single OS Instance Multiple OS Instances Cluster multi-processor Loosely coupled Standard H/W & S/W Highly parallel (web, some HPTC) Proc Mem I/O Proc Mem I/O Network Switch Proc Mem I/O 8 Horizontal Scaling

Vertical vs. Horizontal System Types Vertical Large SMPs Clusters of large SMPs Horizontal Blades Clusters Large MPPs 9

Vertical vs. Horizontal Characteristics Vertical Large shared memory space Many dependent threads Tightly-coupled internal interconnect High single-system RAS Many standard CPUs Single OS with many CPUs Single-box packaging Many CPUs/floor tile Commodity and proprietary h/w Single-box headroom/growth In-box enhancements/upgrades 64-bit Horizontal Small non-shared memory space Many independent threads Loosely-coupled external interconnect High RAS via replication Many standard CPUs Many OS s with 1 4 CPUs/OS Rack and stack packaging Many cpus/floor tile Commodity hardware Multi-box headroom/growth New-node enhancements 32-bit and 64-bit 10

Vertical vs. Horizontal Applications Vertical Large databases Transactional databases Datawarehouses Data mining Application servers HPTC applications (non-partitionable) Horizontal Web servers Firewalls Proxy servers Media streaming Directories XML processing JSP applications SSL VPN Application servers HPTC applications (partitionable) 11

Critical Factors in System Performance Processor Capacity and throughput System Interconnect Low latency High bandwidth Input and output Network and storage, sequential and transactional Operating system Required for H/W to scale Optimized applications System availability 12

Interconnect Specifications Network vs. Centerplane/Backplane Gigabit ethernet 125MB/sec bandwidth 200,000ns latency SCI 200MB/sec bandwidth 4,000ns latency Infiniband 250MB/sec-3GB/sec b/w?? Sun Fire SMPs 9.6GB/sec to 172GB/sec bandwidth 200ns to 450ns latency M M M M PCI PCI P P P P I I P P P P I I M M M M PCI PCI 13

Distributed Memory Large Workloads Not Handled Effectively CPUs p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p RAM Mem Mem Mem Mem Mem Mem Mem Mem Mem Mem Mem Disk Workload 14

Shared Memory Large Workloads Handled Effectively CPUs Up to 100 CPUs p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p RAM Up to 576GB Shared of Memory Shared Memory Disk E The r n et Workload 15

Database Layer Performance Horizontal needs to cluster for performance Oracle 9i RAC is most common cluster database RAC is Real Application Clusters Vertical does not need to cluster for performance 16

What Scaling Means SMP speedup = x faster than one CPU Cluster speedup = x faster than one node SMP scaling = speedup/(no. CPUs) Cluster scaling = speedup/(no of nodes) 17 Scaling depends on number of CPUs/nodes used to calculate 90% scaling on 2 nodes not the same as 90% scaling on 4 nodes

Scaling Examples 1 node to 2 nodes: Scaling factor is.8 or 80% Speedup is 1.8 (1.0, 1.8) Cluster scaling is: 1.8/2 =.9 or 90% 4 nodes: Scaling factor is.8 or 80% Speedup is 3.4 (1.0, 1.8, 2.6, 3.4) Cluster scaling is: 3.4/4 =.85 or 85% 18

Scaling of Clusters 90% Scaling on 2-way Cluster of 4-way servers gives 23x Speedup at 52 CPUs (Oracle 91 RAC)* 95% Scaling gives 23x speedup on 24 CPU SMP (Oracle)** Speedup is how much faster than one CPU 18 72 Linear scaling 16 14 64 56 95% SMP scaling (.95=23/24CPUs) 12 48 Speed-up 10 8 6 40 32 24 90% cluster scaling (.90=1.8/2-servers) CPUs 4-way nodes 19 4 2 0 16 8 0 0 8 16 24 32 40 48 56 64 72 0 2 4 6 8 10 12 14 16 18 * 90% scaling f rom two benchmarks: www.sap.com/benchmark/others.htm#round%robin www.oracle.com/ip/deploy/database/theme_pages/index. html?rac_01242003.html ** 95% scaling from Internal Sun benchmarks

Application Layer Performance Application layer is normally stateless Data resides in database layer Consolidates connections to the database More processors needed than DB layer SAP R/3 uses about 10 app CPUs per each DB CPU Oracle Apps uses about 5 app CPUs per each DB CPU Scaling is not an issue Replication of instances meets performance requirements Acquisition costs not affected by different software licenses 20

SAP App Layer Example Fewer Large App Servers (%Use) Server Consolidation: Higher initial costs Less Complexity Fewer Boxes 46% Headroom Possible app contention For Peak Possibly lower admin costs Possibly fewer licenses,... DB Server Many Little App Servers (%Use) Overload 15% Overload Overload 40% 10% 5% 5% Overload 5% Lots Network Connections! Server Replication: Lower initial costs Hot spots Less predictable Possibly higher management costs DB Server Customer Evaluation: SAP Application Servers 50% Less HW 24-way vs. 2-ways Load Balancing on SAP Sessions at Login Static Larger servers had more headroom for peak workloads Batch Jobs (Payroll, MRP...) can't span several app servers 21

Application Layer Management If database requires 20 processors Oracle Apps application layer: 100 processors SAP R3 application layer: 200 processors 50 100 2-way servers or 5 10 20-way servers? More OS instances may increase costs More application instances may increase costs Horizontal solution may have lower TCA but higher TCO 22

Consolidated Solutions Database 20 CPUs Database 20 CPUs HR app server 12 CPUs SD app server 4 CPUs Test and Develop 8 CPUs 23

Presentation Layer Performance Applications rarely scale Applications cannot use multiple CPUs Applications are not data intensive Commonly stateless Internode communication minimal Cluster costs are not an issue Horizontal has lower acquisition cost Horizontal has sufficient performance 24

How to Lower TCO Lower acquisition costs Use commodity components Lower complexity Fewer OS flavors Fewer OS instances Better utilize resources Virtualize resources Automate resource migration Centralize Data centers Disaster recovery Backup 25

Application Lifecycle TCO TCO must be managed over entire application lifecycle Less than 20% is hardware acquisition 26

TCO Implications of Cluster Scalability 27 Oracle 9i RAC needs more CPUs than Oracle 9i Oracle 9i RAC per CPU pricing higher than Oracle 9i Acquisition costs (h/w and s/w) may be higher for horizontal scaling E.g., Need 13 x 4-CPU servers to equal 24-way SMP server 52 CPUs vs. 24 CPUs

5.2 mins Availability Continuum 99.95% 99.975% 99.999% 100.0% 4.4 hrs 2.2 hrs Cost & Complexity 99.5% 99.0% 44 hrs 8.6 hrs 98.5% 88 hrs 98.0% Servers with Auto-reboot Servers w/ On-line Repair/Reconfig Failover Clustered systems Active-Active Clusters 28

Availability Strategies Different for Horizontal and Vertical 29 Large SMPs: High single system RAS Full hardware redundancy Online serviceability Error checking and correction HA failover (standby server) Cluster for highest availability requirements Horizontal nodes: Clusters and Replication Cluster for availability for databases Replicate workload for non-db applications

TCO Implications of Availability Level of Availability Affects TCO 99.95% single SMP may be sufficient Greater than 99.95% requires cluster Standby failover (HA) may be sufficient Database active on only one node, other standby Database needs to start up For Oracle does not require RAC licenses Highest avail. level requires active cluster 2 or more nodes active Fast failover For Oracle RAC licenses required 30

Large vs. Small Clusters Hardware and Software Acquisition Costs 1 x 6800 20-way server: $826,360 Oracle 9i licenses 2 x 6800 12-way servers: $1,461,360 Same performance as 1 x 20-way 6800 With Oracle 9i RAC licenses 8 x 480 4-way servers: $1,465,600 Same performance as 1 x 20-way 6800 With Oracle 9i RAC licenses RAC Calculator Parameters: 90% scaling, 10% decay, 50% Oracle discount, 40% 6800 discount, 20% 480 discount 31

Clustering for Scalability vs. Clustering for Availability IDC Survey Data: 74% of all clusters are deployed for Availability Even customers most familiar with clustering software and clustered systems continue to be very cautious regarding the replacement of large scale-up systems with clusters of scaleout systems. Matthew Eastwood, IDC Source: IDC, 2003 32

Availability Summary For highest availability: (<99.975) Horizontal or vertical clustering Two large-node clusters similar cost as multiple small node clusters For lower availability Vertical with HA failover will cost less Single vertical node may be sufficient 33

Vertical and Horizontal Summary Vertical scaling Big memory Big disk I/O bandwidth Big RAS Protect state Data Facing Tier 3 Tier 2 Tier 1 Tier 0 SAN Network Facing Horizontal scaling Med memory Big network I/O bandwidth Replication Stateless NAS 34

Horizontal vs. Vertical Summary Horizontal ideal for web-tier Performance and acquisition cost Vertical well-suited for database tier Performance and acquisition cost Both can be used for application tier Clustering good for availability but not for performance 35