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Proibida cópia ou divulgação sem permissão escrita do CMG Brasil. © Copyright IBM Corporation, 2008
Relative Capacity
Joseph Temple – Distinguished EngineerEduardo Oliveira – Executive IT Specialist
© Copyright IBM Corporation, 2008
Proibida cópia ou divulgação sem permissão escrita do CMG Brasil. © Copyright IBM Corporation, 2008
TrademarksThe following are trademarks of the International Business Machines Corporation in the United States, other countries, or both.
The following are trademarks or registered trademarks of other companies.
* All other products may be trademarks or registered trademarks of their respective companies.
Notes: Performance is in Internal Throughput Rate (ITR) ratio based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput that any user will experience will vary depending upon considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve throughput improvements equivalent to the performance ratios stated here. IBM hardware products are manufactured from new parts, or new and serviceable used parts. Regardless, our warranty terms apply.All customer examples cited or described in this presentation are presented as illustrations of the manner in which some customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics will vary depending on individual customer configurations and conditions.This publication was produced in the United States. IBM may not offer the products, services or features discussed in this document in other countries, and the information may be subject to change without notice. Consult your local IBM business contact for information on the product or services available in your area.All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.Information about non-IBM products is obtained from the manufacturers of those products or their published announcements. IBM has not tested those products and cannot confirm the performance, compatibility, or any other claims related to non-IBM products. Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products.Prices subject to change without notice. Contact your IBM representative or Business Partner for the most current pricing in your geography.
Adobe, the Adobe logo, PostScript, and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States, and/or other countries.Cell Broadband Engine is a trademark of Sony Computer Entertainment, Inc. in the United States, other countries, or both and is used under license therefrom. Java and all Java-based trademarks are trademarks of Sun Microsystems, Inc. in the United States, other countries, or both. Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both.Intel, Intel logo, Intel Inside, Intel Inside logo, Intel Centrino, Intel Centrino logo, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries.UNIX is a registered trademark of The Open Group in the United States and other countries. Linux is a registered trademark of Linus Torvalds in the United States, other countries, or both. ITIL is a registered trademark, and a registered community trademark of the Office of Government Commerce, and is registered in the U.S. Patent and Trademark Office.IT Infrastructure Library is a registered trademark of the Central Computer and Telecommunications Agency, which is now part of the Office of Government Commerce.
For a complete list of IBM Trademarks, see www.ibm.com/legal/copytrade.shtml:
*, AS/400®, e business(logo)®, DBE, ESCO, eServer, FICON, IBM®, IBM (logo)®, iSeries®, MVS, OS/390®, pSeries®, RS/6000®, S/30, VM/ESA®, VSE/ESA, WebSphere®, xSeries®, z/OS®, zSeries®, z/VM®, System i, System i5, System p, System p5, System x, System z, System z9®, BladeCenter®
Not all common law marks used by IBM are listed on this page. Failure of a mark to appear does not mean that IBM does not use the mark nor does it mean that the product is not actively marketed or is not significant within its relevant market.
Those trademarks followed by ® are registered trademarks of IBM in the United States; all others are trademarks or common law marks of IBM in the United States.
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Agenda
• General Ideas• Pfister’s Diagram• Workload Type/Characteristics• Workload Factor• Benchmarks• White Space• Virtualization and Utilization• Relative Capacity• Ideas International/Performance Comparison• Non-Functional requirements• Total Cost of Ownership (TCO)• Consolidation: Case Study• Platform Choices
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General Ideas• It is the nature of computers that any
computer can be programmed to accomplish any task.
• Conversely, functionality is not enough.
• Rational Platform Selection is based on the solution’s “non functional requirements”
Proibida cópia ou divulgação sem permissão escrita do CMG Brasil. © Copyright IBM Corporation, 2008
Syn
chro
niza
tion
Tim
e
Bulk Data Traffic
Shared NothingHigh LatencyBlades, Clusters,SquadronsHVRead Only Webserving, some DSS
Shared MemoryLow Medium LatencyF6800,rx8400,rp8400P670, Squadrons MLOLTP, Legacy SMP
Shared MemoryHigh Medium LatencyF12000,F15000, SuperDome,P690Data Warehouse, some DSS
From: In Search of Clusters, The ongoing battle in lowly parallel computingby Greg Pfister, p461
Shared EverythingLow LatencyzSeries, Squadrons HE OLTP, Mixed Workload
Price/
Perfo
rman
ce
Tot
al C
apac
ity
WLM
& B
I Fun
ctio
n
Virtua
lizat
ion
ArchitecturalDivide
Blades
Midrange Client Server
MainframesArchitecturalDivide
High End UNIX Severs
Simplifying the Client Server Build Out
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From: In Search of Clusters, The ongoing battle in lowly parallel computing by Greg Pfister, p461
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Workload Characterization
2. I/O Bound – e.g. high I/O content applications
9. Protocol Serving – e.g. static HTTP, firewall, etc.
3. Mixed Low – e.g. multiple, data-intense applications or skewed OLTP, MQ
1. Data Intensive – large working set and/or high I/O content applications
4. Mixed High – e.g. multiple, cpu-intense simple applications
8. Skewless OTLP – e.g. simple and predictable transaction processing
7. Java Heavy – e.g. cpu intensive java applications
6. Java Light – e.g. data intensive java applications
5. Database – e.g. Oracle DBMS or dynamic HTTP server
10. CPU Intensive – e.g. numerically intensive, etc.
I/O Driven
CPU Driven
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From: In Search of Clusters, The ongoing battle in lowly parallel computing by Greg Pfister, p461
z
p
Large Processors
Distributed Processing
Industry Benchmarks
TPC-C, TPCE??
Parallel Hell positioning is empirical and folklore driven
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Workload ConsiderationsWorkloads may benefit from being physically close to the data
Most servers run in low to medium utilization
High I/O workloads Vs. High CPU workloads
Workloads may require high availability• Mission critical applications
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Comparing servers using relative capacity:
Given system B with capacity CB processing a workload at utilization UB
capacity CA needed by system A to process the same workload is given
by:
WLF
UCC BB
A
where WLF is the Workload Factor.
With WLF we try to compensate for all the architectural differences between system A and system B. It is simplified: Actually WLF = f(UB)
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Parallel
Syn
chro
niza
tion
Tim
e
Bulk Data Traffic
Shared NothingHigh LatencyBlades, Clusters,Squadrons HVRead Only Webserving, some DSS
Shared MemoryLow Medium LatencyF6800,rx8400,rp8400P670, Squadrons MLOLTP, Legacy SMP
Shared MemoryHigh Medium LatencyF12000,F15000, SuperDome,P690
Data Warehouse, some DSS
From: In Search of Clusters, The ongoing battle in lowly parallel computing by Greg Pfister, p461
Shared EverythingLow LatencyzSeries, Squadrons HE OLTP, Mixed Workload
Pfister’s Paradigm and Core Design
Tot
al C
apac
ity
WLM
& B
I Fun
ctio
n
Serial
Processor
SpeedCache
RAS
Processor
SpeedCache
RAS
Processor
Speed
Cache
RAS
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Industry Standard Benchmarks System Level Characteristics• No disk I/O• No network I/O• No database• Data sharing• Global memory• Interconnect important
Examples• SPEC OMPL2001• SPEC OMPM2001
Component
Characteristics• No disk I/O• No network I/O• No database• No data sharing• Cache / local memory• Scales w/QTY of cores
Examples• SPECint2000• SPECint_rate2000/2006• SPECfp2000/2006• SPECfp_rate2000• SPECjbb2000/2005
Specialty
Characteristics• Disk I/O• Network I/O• No data sharing• Local memory• Scales w/QTY of cores
Examples• SPECweb2005• NotesBench• SPECjAppServer 2004• SPECsfs97_R1.v3
Database Examples• TPC/H (Read Only)• SAP SD 2-Tier (Limited I/O)
System Level Database
Characteristics• Disk I/O• Network (except batch)• Global memory• Data sharing• Read/Write database
Examples• TPC/C• SAP SD 3-Tier• Oracle Apps• Oracle RAC• Oracle Batch• PeopleSoft Financials
Memory Memory I/O
CPU
Cache
CPU
Cache I/O
Local Interconnect
Memory Memory I/O
CPU
Cache
CPU
Cache I/O
Local Interconnect
Global Interconnect
Memory Memory I/O
CPU
Cache
CPU
Cache I/O
Local Interconnect
Memory Memory I/O
CPU
Cache
CPU
Cache I/O
Local Interconnect
Global Interconnect
Memory Memory I/O
CPU
Cache
CPU
Cache I/O
Local Interconnect
Memory Memory I/O
CPU
Cache
CPU
Cache I/O
Local Interconnect
Global Interconnect
Memory Memory I/O
CPU
Cache
CPU
Cache I/O
Local Interconnect
Memory Memory I/O
CPU
Cache
CPU
Cache I/O
Local Interconnect
Global Interconnect
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System Design and Benchmarks
• Industry standard benchmarks are used by vendors to establish performance or price/performance leadership.
– Benchmarks are chosen to show off a platform not to allow comparisons
• Benchmarks frequently do not match real customer workloads
– Small – very limited stress on data delivery infrastructure
– Throughput oriented with highly paralyzed processing – scales with quantity of processors for all vendors
• Real workloads (including virtualization and mixed workloads) place tremendous stress on cache and system interconnect.
Wo
rklo
ad /
Ser
ver
Siz
e
Data Sharing / Workload Complexity
On-Chip CacheQty of Threads
(1-2 Sockets)Any Benchmark
Quantity ofCores / threads
Parallelization
ThroughputResults
TPC-HSAP SD 2-TierSPECJBB2005SPECintRateSPECfpRate
SPECweb
System Interconnect Cache Architecture
Schedulers # of Processors
TPC-C SAP SD 3-Tier
InterconnectCache
Schedulers# Processors
VirtualizationMixed Workload
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'White space' = wasted capacity
Shared SystemsSeparate Dedicated Systems
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Peak and Average
• The desired peak utilization is the “Utilization at Saturation design point”, Usd
• Average Utilization is:
sAP
Usd
sAPU
)1/(1)1/(1
1
Where:P is the Peak Load A is the Average Loads is the number of servers used to implement the capacity
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Virtualization enables higher CPU Utilization
• Single workload model assumptions:– Average Utilization: 20.7%– Peak: 79%
• As more copies of this workload are added, average utilization approaches peak
– 8:1 39% Average, peak 76%– 16:1 48% Average, peak 78%– 64:1 61% Average, peak 78%
• As workload is added the number of CPUs required for the work grows at a much lower rate.
Single Appliation Server (2 CPUs)
0%
10%
20%
30%
40%
50%
60%
70%
80%
8 to 1 Consolidation (8 CPUs)
0%
10%
20%
30%
40%
50%
60%
70%
80%
16 to 1 Consolidation (12 CPUs)
0%
10%
20%
30%
40%
50%
60%
70%
80%
64 to 1 Consolidation (36 CPUs)
0%
10%
20%
30%
40%
50%
60%
70%
80%
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Why Larger Servers for Virtualization?
• Hardware Advantages– Higher utilization due to shared headroom.– More internal bandwidth to improve performance– Fewer disk & network adapters and ports– Able to share memory more effectively– More fault tolerant features
• People Advantages– Fewer servers to order, install, track, maintain,
and retire– Fewer Hypervisor instances to manage– Fewer firmware patches to apply
• Data Center Advantages– Better power utilization– Reduced floor space
Hardware CapacityUsable VM Capacity
Smaller Servers
Medium Peak to Avg. Utilization Gap
Larger Servers
Small to Very Small Peak to Avg.
Utilization Gap
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Relative Capacity Criteria
• What is the number and utilization of servers? – How big is this? What is the potential for virtualization or workload
management? Need to profile utilization by intervals.• How Parallel is the work?
– Read only partitioned data, mostly read minimum sharing, mostly read shared data, read/write partitioned data, read/write shared data, etc. (Leverage of shared v. partitioned resources)
• How large are the working sets for the DB, Memory, and Cache? – What is the "Workload Factor?" Need throughput v. utilization by
intervals• What are the testing and QA practices?
– How much nonproduction hardware is there as a result?
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Relative capacity (cont’d)• Capacity Metric can vary (MIPS, MHz, tpm, tpc-c, n° engines, ...)
• Utilization (%) can be measured with various tools (vmstat, top, Task Manager, ...)
• WLF is measured in [CB]/[CA] units– i.e., LSPR values are MIPS/MIPS workload factors for two zSeries machines at same
utilization
• WLF difficult to measure!– not enough benchmarks to cover all the cases– driven by cache miss rate, which cannot be directly measured– “Cloud of uncertainty” around measured values
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Ideas International
• Independent Organization• Publishes the Consolidated Analysis Report
(CAR)• CAR contains the RPE2 performance index• RPE2 index can be used into cross-platform
selection• Requires a License
• http://www.ideasinternational.com/ • RPE2 = Relative Performance Estimate 2 (Copyright © 2008 - Ideas
International Limited)
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Performance Comparison
• Server Utilization
• Workload Type
• I/O Latency
• Cache
• Clock Speed
• Architecture
• Non-functional requirements
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Cost is a quantification of Non functional requirements
• Costs go way beyond Hardware, Software, Maintenance• There are different ways to surface them• Here is one way to organize things:
– Cost of outages– Prioritization– Growth– Administration Costs– Time to Market v Code Quality– Project Costs– Environmental Costs
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A full range of TCO factors considerations – often ignored
• Integration– Integrated Functionality vs. Functionality to be
implemented (possibly with 3rd party tools)– Balanced System– Integration of / into Standards
• Further Availability Aspects
– Planned outages
– Unplanned outages
– Automated Take Over
– Uninterrupted Take Over (especially for DB)
– Workload Management across physical borders
– Business continuity
– Availability effects for other applications / projects
– End User Service
– End User Productivity
– Virtualization
• Skills and Resources
– Personnel Education
– Availability of Resources
• Availability– High availability– Hours of operation
• Backup / Restore / Site Recovery– Backup– Disaster Scenario– Restore– Effort for Complete Site Recovery– SAN effort
• Infrastructure Cost– Space– Power– Network Infrastructure– Storage Infrastructure
• Additional development and implementation
– Investment for one platform – reproduction for others
• Controlling and Accounting– Analyzing the systems– Cost
• Operations Effort– Monitoring, Operating– Problem Determination– Server Management Tools– Integrated Server Management –
Enterprise Wide
• Security– Authentication / Authorization– User Administration– Data Security– Server and OS Security– RACF vs. other solutions
• Deployment and Support
– System Programming• Keeping consistent OS and SW Level• Database Effort
– Middleware• SW Maintenance• SW Distribution (across firewall)
– Application• Technology Upgrade• System Release change without interrupts
• Operating Concept– Development of an operating procedure– Feasibility of the developed procedure– Automation
• Resource Utilization and Performance– Mixed Workload / Batch– Resource Sharing
• shared nothing vs. shared everything– Parallel Sysplex vs. Other Concepts– Response Time– Performance Management– Peak handling / scalability
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Overview of Techline’s case study
SAR Reports
WebserverWebserver
Webserver Server Consolidation Tool
Projected Util.
VMXT
z/VM
zLinux
Apache
Capacity Tool
= Actual Util. ?
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Platform Choices
Legacy
Quality of Service
Total CostApplication Platform Support
Application Structure
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