getting the best performance out of your svc v7000 … the best...smart storage sizing storage...

Smart Storage Sizing

Storage intelligence

Getting the best performance out of your SVC, V7000, DS5000

and DS8000

Dr. Gilbert HoutekamerIntelliMagic BV

[email protected]

Storage Intelligence 2

IntelliMagic Overview

A world leader in Storage Performance Management software solutions

Developing SPM solutions since 1991

Private, no debt

Headquarters in Leiden, NLUS office in Dallas, TX


Overview

Introduction to Storage Performance Management

Monitoring Storage Performance with SMI-S

Interpreting Storage Performance Data

IntelliMagic Vision examples for IBM Storage

IntelliMagic Vision and Direction Product Summaries


Storage Performance ManagementIntroduction

© IntelliMagic, 2011


Storage Performance Management (SPM)Definition

Storage Performance Management is the process of ensuring• that users constantly receive required I/O service levels to

avoid performance problems; • that storage assets are efficiently configured and used to

avoid over spending on hardware.

Risk avoidance is more important than saving money.

Storage Intelligence

Over configured: Efficiencyissues

6

Sweet spot:Right performanceRight Cost

size (and cost) of storage configuration

cost

performance

Utilization levels

Underconfigured: Performance issues

lower

higher

Risk is notremoved: Hot spots will still occur from time due to imbalance

The cost difference between these two is often 330% or

more of all storage

Risks


SPM Maturity Stages

Often 30% or more difference in total hardware costs


SPM Drivers - How did we get here? Storage Architecture Evolution

Why are most sites at reactive maturity stages?

Answer: Queuing no longer happens on the host, but inside the storage system where you can’t see what is going on.

8

The Big Shift: The host is rarely I/O constrained anymore – today’s bottlenecks are with specific components inside the storage system

… …

DA DA

DA DAHA

HA

HA

HA

HA

HA

SMP

“Visibility Gap”


Visibility Gap: Looking Inside

To be effective, an SPM solution must:1. Provide visibility into workload measurements inside the

storage system where the bottlenecks occur, and 2. Correlate the workload metrics with the capabilities of

specific hardware components in use.

In particular, visibility of the hardware components:on the front-end (host adapters) and on the back end (the physical devices)

SMI-S data provides this visibility


Front-end and Back-end

© IntelliMagic 2011 10

Storage system performance measurements need to include:

Cache

Front-end Adapter

Front-end Adapter

Back-end Adapter

Back-end Adapter

Disks

Logical Write

Logical Read

Physical Write

Physical Read


Logical and Physical I/Os

Logical I/Os from Servers to LUNs on front-end ports

Physical I/Os to Back-end drives

Large caches reduce read-misses and buffer writes

Sequential I/O always implies back-end I/O

11© IntelliMagic 2011

Back-end array groups

Read hit Read missRandom

WriteSeq.

Write


Monitoring Storage Performance with SMI-S


Server Performance Data


linux iostat system=LG_ABC20 interval=600 01oct2010 14:43

avg-cpu: %user %nice %sys %iowait %idle6.54 0.24 1.53 3.41 88.28

Device: rrqm/s wrqm/s r/s w/s rsec/s wsec/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %utilsda 4.97 10.12 0.84 6.84 31.01 78.23 15.50 39.12 14.23 0.00 0.19 0.45 0.35sda1 0.58 0.00 0.03 0.00 1.21 0.00 0.60 0.00 47.45 0.00 4.57 1.67 0.00sda2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00 0.00 1.33 1.33 0.00sda5 2.48 1.05 0.62 1.12 24.76 17.43 12.38 8.72 24.20 0.00 3.12 1.97 0.34sda6 0.01 2.79 0.00 1.39 0.12 33.45 0.06 16.73 24.05 0.00 1.91 0.47 0.07sda7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10.85 0.00 21.78 14.86 0.00sda8 0.11 0.28 0.01 0.69 0.97 7.78 0.48 3.89 12.39 0.00 0.50 4.46 0.32sda9 0.10 1.72 0.01 1.44 0.23 6.33 0.12 3.17 4.52 0.00 2.12 0.13 0.02sda10 1.69 4.28 0.16 2.19 3.72 13.23 1.86 6.61 7.20 0.00 1.68 0.67 0.16sda11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.51 0.00 8.99 8.84 0.00sda12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10.00 0.00 0.83 0.83 0.00sdb 13.66 25.95 4.56 15.78 145.72 344.50 72.86 172.25 24.10 0.00 0.21 0.09 0.17sdb1 13.66 25.95 4.56 15.78 145.72 344.50 72.86 172.25 24.10 0.00 0.21 0.09 0.17

Most UNIX and Windows servers do have end to end response times and disk transfers/sec available for each LUN that can be used for identifying if a disk problem exists.

Unfortunately they do not have the insight into the backend storage components required to identify root cause of backend storage issues.


Storage Performance Data


Storage system performance measurements need to include:

Cache

Front-end Adapter

Front-end Adapter

Back-end Adapter

Back-end Adapter

Disks

Logical Write

Logical Read

Physical Write

Physical Read


SMI-S Defines Components that are monitored

ElementType Component Vendor Specific

ElementType2 Cumulative statistics for the storage system

ElementType3 Front-end Controllers

ElementType4 Peer Storage System (Mirroring)

ElementType5 Back-end Controllers

ElementType6 Front-end FC ports

ElementType7 Back-end Ports

ElementType8 Volumes

ElementType9 Extent – Intermediate storage

ElementType10 Disk Drive

ElementType11 Arbitrary Logical Units – Controller commands

ElementType12 Remote Replica Group – Remote Mirror

15

Same element types are used by all vendors, although the statistics collected to differ. In general, Enterprise Storage Systems from IBM and EMC collect more detail than the midrange systems


SMI-S allows for vendor extensions

© IntelliMagic 2011

16

IBMSpecific

EMC SpecificOther

vendors

SMI-Sminimu

m set

SMI-S Standard

First time ever to have storage performancedata across vendors in generic standard.

Response time for DS5000 is an example of an extension

Note that TPC only supports SMI-S extensions for DS8000 and SVC


SMI-S Data Collection Comparison(including IntelliMagic Vision enriched data)

Component

IBM EMC HDS

DS8X00 DS5000 V7000 SVC DMXVMAX

CLARiiON

VNX(SAN)

USP VVSP

Top Level Computer System

Front-end Adapter

Peer-to-peer Back-end Adapter

Front-end Ports 1 1

Back-end Ports Volume

Storage Pool/RankDisk Drive

Replication2

17

1 For SVC/V7000 some of the information is obtained from XML files 2 DS8000 replication link usage, DMX/VMAX SRDF/A usage, CLARiiON Snap Sessions


DS5000 Architecture Overviewwith SMI-S representation


SMI-S: Top Level

Computer System

Front-end Adapter

Front-end Port

Disk Drive

volumes

Not every item from the

hardware is represented in

an SMI-S concept.


Not only Performance Data

SMI-S is a rich source of configuration data• Which LUNs are defined on which extent pool• Which physical drives make up an array group• Which port (types) are connected to each (host adapter)

19

Disks

Extent/Raid Group

Volume

Front End


SMI-S: Cross-Vendor Storage-Centric Measurements

SMI-S is standard like SNMP, supported by IBM, EMC, Hitachi/HP etcThe SMI-S provider communicates with hardware to publish data.Implementations vary, eg separate provider for EMC Clariion or embedded for EMC V-Max or IBM DS8800Detailed information on at least logical and physical volumesUsually more information eg ports, component utilization, even replication


SPM Technology: Vendor Specific Versus Vendor Neutral


Feature Vendor Specific SMI-S (Vendor Neutral)Communication between tool and storage device

Vendor proprietary fast protocol

Standard XML based communication for all exchanges

Support for platform specific metrics

No distinction between standard and platform specific metrics

Requires minimum number of fields, but supports vendor extensions for extra fields and components

Compatibility with other hardware

Specific to one hardware platform

Any hardware supporting SMI-S

Third party access

Few documented interfaces, different interfaces for each platform

Open specification to any tool vendor

Provisioning SupportDesigned for specific hardware

Difficult to support with SMI-S due to hardware specific implementations


Interpreting Storage Performance Data


IntelliMagic Vision Data Base

Repository with storage performance data (DB2 or SQL Server)

Daily automated Health Check & Dashboard for quick assessment

All data for performance problem diagnosis readily available in case of problems

Tracking of early warning information will avoid future application performance issues


How Do I Know if Any DSS’s Have a Problem?

© IntelliMagic 2011 24Red – Bad!

DS4800


Match Hardware Capability to KPIs and Measurement


DS4800


DSS SLA for Disk Response Time


DS5000DS8000


Host Adapter Utilization


DS5300


SPM Technology: DSS -> RAID Group Drill Down


DS8000


SPM Technology: RAID Group to Volume Drill Down


DS8000


SPM Technology: Time Normalization



I/O Rate vs. Response TimeExamples based on SMI-S data


Correlating I/O rate and response time doesn’t really tell us anything


HDD Response Service Levels


Interpreted data from SMI-S

DS8000


I/O Rate and Response Time Correlation


Response time (as seen by the application on Fibre ports)

Lack of correlation (20:30 – 22:30) indicates possible DSS component over utilization

DS8000


Cache Over Utilization?


FW Bypass are I/O operations that are delayed because of lack of write cache resources in the disk storage system.DS8000


Closer look at Extent Pool 25


Cache bypass is not significant when viewed at a DSS level, but comprises approximately 45% of write I/Os for this extent pool!

FW bypass seriously affects I/O response timeDS8000


SVC Back-End


Configuration drill-down

SVC Configuration


How is IntelliMagic Vision implemented


IntelliMagic Vision Architecture (Open)

41

IntelliMagicVision

SMI Providers

Arrays

Windows

Vision SMI-S Collector

Data Store

DB2

SQL Server


Installation process

ProcessIntelliMagic Consulting servicesRequirement analysisDeterminen type of reporting

Implementation stepsSet up SMI-S agentsDaily reporting run on last loadWeekly/Monthly reporting run on trending data base

Separate version for z/OS usersRMF/SMF data input


PDF Export

Reporter:Indexed PDF for

standardand

user report sets


HTML Export

Dashboard, Charts,Tables


PPT Export

Annotated PowerPoint

Classic Reporter andReporter

All charts

Ready to publish or present


Raw data in CSV format

Raw data for further analysis


IntelliMagic Direction


Storage Intelligence © IntelliMagic 2011 48

SPM Technology - Predictive Process Requirements

Modeling

Design-ing Tiers

Data Layout

What if we grow or change hardware?

What is the best tier for each application

How can I optimizemy volume layout?

Storage Intelligence © IntelliMagic 2011

Direction Overview

Files with workload measurements from the Servers and/or the DSS’s

Set Base Line:Set reference pointReport on utilizations

Predict effects of:Configuration changesWorkload growthCache behaviorMigrationsConsolidation

Tabular andGraphical output

Disk Subsystem Configuration

input

Direction

Cache

FED FED

BED BED


Supports All Mainline Hardware and Software Platforms

DMC

UNIX / AIX LINUX IOSTAT

I5/OS PT Reports

Windows Perfmon

IBM Disk Subsystem TPC

DirectionIBM

EMC

DSS, SMI-S & Vision CSV

MFO

HDSHP

MFO = Multi-File OpenDMC = Disk Magic Control

PT = Performance ToolTPC = TotalStorage Productivity Center

z/OS RMFIntelliMagic

Vision

Storage Intelligence © IntelliMagic 2011 51

Forecasting Performance Requirements and Modeling

Workloads


SVC Utilizations Inside



How are the utilizations of the Backend Controllers?

Utilizations inside the DS5300.

What happens inside the backend DS8100?

53© IntelliMagic 2011


What Happens to Utilization if We Add Additional an HBA to DS5300?


HA Utilization drops!


What Happens to HA Utilization with Additional HBAs on DS8100?


HA Utilization drops!


Thank YouQuestions?


[email protected]

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