SlideShare a Scribd company logo
1 of 41
HITACHI DYNAMIC TIERING
(HDT): AN IN-DEPTH LOOK AT
MANAGING HDT AND BEST
PRACTICES
BRANDON LAMBERT, SR. MANAGER
MICHAEL ROWLEY, PRINCIPAL CONSULTANT
AMERICAS SOLUTIONS AND PRODUCTS
WEBTECH EDUCATIONAL SERIES
HITACHI DYNAMIC TIERING (HDT): AN IN-DEPTH LOOK AT MANAGING
HDT AND BEST PRACTICES, PART 2 OF 2
Hitachi Dynamic Tiering simplifies storage administration by automatically optimizing data
placement in 1, 2, or 3 tiers of storage that can be defined and used within a single virtual
volume. Tiers of storage can be made up of internal or external (virtualized) storage, and
use of HDT can lower capital costs. Simplified and unified management of HDT allows for
lower operational costs and reduces the challenges of ensuring applications are placed
on the appropriate classes of storage.
By attending this webcast, you will

•

Hear about what makes Hitachi Dynamic Tiering a unique storage management tool
that enables storage administrators to meet performance requirements at lower costs
than traditional tiering methods.

•

Understand various strategies to consider when monitoring application performance
and relocating pages to appropriate tiers without manual intervention.

•

Learn how to use Hitachi Command Suite (HCS) to manage, monitor and report on an
HDT environment, and how HCS manages related storage environments.
AGENDA

 The HDT lifecycle

 HDT performance basics
 HDT basic guidelines
 Monitoring HDT with Hitachi Tuning Manager
AGENDA

 The HDT lifecycle

 HDT performance basics
 HDT basic guidelines
 Monitoring HDT with Hitachi Tuning Manager
HDT LIFECYCLE
Plan

Turn on
HDT Heat
Maps

What to
Monitor
and Cycle

Implement

Build HDT
Pools
Add Daily
Monitoring

Design HDT
Environment
Implement

Daily Operations
(Monitor/Report)

Cont.
Daily
Monitor
(Alarm)

Capacity
Trend/Plan

Tune
Configuration
(HW, Cycle, Ap
ps, Policies)

Migrate
Into Pools

Consider
HW Limits
Historical
Performance
Trend

Adjust
Configuration
Basic Trend Report
(Cap./Perf.)

Relocation
Reporting
(Gradual
or Erratic)

Performance
Trend/
Troubleshoot
AGENDA

 The HDT lifecycle

 HDT performance basics
 HDT basic guidelines
 Monitoring HDT with Hitachi Tuning Manager
HDT PERFORMANCE MONITORING
 Back-end I/O (read and write) counted per page
during the monitor period

IOPH

25

 Monitor ignores “RAID I/O” (parity I/O)

20

 Count of IOPH for the cycle (period mode)
or a weighted average (continuous mode)

DP-VOLs

15

 HDT orders pages by counts high to low
to create a distribution function
‒ IOPH vs. terabytes
 Monitor analysis is performed to determine the
IOPH values that separate the tiers

Monitoring

10
5

0
Page 1

25

Page 999

Pool

20

Aggregate the Data
15

SN2

Analysis

10
5
0
Capacity 1

Capacity nnn
POOL TIER PROPERTIES
What is being used
now in the pool in
terms of capacity
and performance
Can display just the
performance graph
for a tiering policy
The I/O
distribution across
all pages in the
pool. Combined
with the tier
range, HDT
decides where the
pages should go
CAUTION ABOUT PERFORMANCE
UTILIZATION (P%)










P% is only an approximation of tier utilization
It is based on assumptions of read/write ratios (50-50)
P% does not factor in RAID I/O (parity I/O)
It should not be used to calculate I/O counts
It should not be used to determine relative utilization at lower P% values
- P% is not accurate enough for comparing small differences
P% is only used to signal that a tier may be overutilized
P% cannot absolutely report that a problem exists
Ignore P% unless it is over 60%
Prior to V04+a continuous modes, P% uses the weighted average IOPH
values. In V04+A continuous mode uses the monitoring result of the last
cycle (period mode value) for calculating P% performance utilization

A better measure of actual tier utilization is to use parity group utilization
TIER RANGE VALUES

 Tier range values dynamically change according to
workload
 Tier range values are always calculated to keep upper
tiers generally full
 Pages compete for upper tiers. Pages can be pushed
down if more aggressive workloads come on the scene

 Pages that do not remain “hot enough” (competitive) will
demote
 Newly active data on dormant (or new) pages or
migrated volumes will need protection

-

Policy settings work well
AGENDA

 The HDT lifecycle

 HDT performance basics
 HDT basic guidelines
 Monitoring HDT with Hitachi Tuning Manager
CHOOSING A MONITOR STRATEGY:
RECOMMENDED START POINT
 Start with continuous mode
 Start with automatic
 Start with 8-hour
 Investigate Hitachi Tiered Storage Manager for custom scheduling of
monitor and relocation cycles
CHOOSING A MONITOR STRATEGY
 Use tiering policies to protect or restrict tier use
 3-tier pool
‒ Liberally use ALL
‒ Use level 4 if Tier 1 use should be restricted (not used) and when Tier 2 is
well configured
‒ Note that incorrectly using level 5 will cause performance issues
‒ Levels 1 and 2 can cause overcommitment (and waste) of Tier 1
‒ Levels 2, 3, and 4 can overcommit Tier 2

 2-tier pool
‒ Liberally use ALL
‒ Liberally use level 4 (or 3 or 5) if Tier 1 use should be restricted (not used)
and when Tier 2 is well configured
RELOCATION RATES

 Standard relocation throughput is about 3TB/day
 Write pending and MP utilization rate influences the
pace of page relocation
‒ When WritePending is 55%, 20-second wait is inserted per page
‒ MP utilization rate influences pacing
‒
‒
‒
‒
‒

60% or more: 6 pages or less in 5 seconds
50-60%: 8 pages or less in 5 seconds
40-50%: 10 pages or less in 5 seconds
30-40%: 12 pages or less in 5 seconds
30% or less: Unlimited

 When SOM904 is ON, only 1 page is relocated per
second
‒ For example, when page migration takes 600 ms, the next page
migration starts after sleep for 400 ms (1,000 ms - 600 ms)

‒ If page migration takes 1 second or more, the next page migration
starts without sleep procedure.
‒ HDT relocate pages in less than 40MB/sec
HDT TUNING SUMMARY
 HDT tunes tier ranges dynamically (neither Hitachi Tuning Manager
((HTnM)) or Hitachi Tiered Storage Manager ((HTSM)) is used)
 If a tier P% approaches 60% utilization, we aim to move I/O down a tier

‒ 60% sustained I/O to accommodate peaks and prevent queuing
‒ Tier range is increased, reducing the tier’s utilized capacity. All of the tier
capacity will not be used – but that is better than overloading the tier
with too much IOPH

 If all tiers are over (60%/60%/60%), the pool is over utilized − tier ranges
are increased again to share the problem
 You can’t “lose storage” but you might put more I/O into a pool than it can
handle

 You should be looking for these situations, evaluating the issues, and
adding capacity
HDT TUNING SUMMARY

 Do not underestimate the importance of Tier-3
performance
‒ HDT will relocate dormant pages to Tier 3. If these pages
become active, Tier 3 must perform well enough to cope with
some host I/O and relocation I/O

 Tiering policy can be used to help or hinder
‒ Helps
 Use level 3 or 4 to stage data into Tier 2 before it is needed
 Use level 1 or 2 to stage important data before “Mondays”
‒ Hinders
 When using level 1-4 on dormant data
 Leaving level 1 or 2 set too long

 T% and R% should not be changed unless needed to
artificially reduce capacity
TIER SIZE MATTERS
POOL CONSUMPTION MATTERS
AGENDA

 The HDT lifecycle

 HDT performance basics
 HDT basic guidelines
 Monitoring HDT with Hitachi Tuning Manager
HDT AND HTNM
WHAT'S AVAILABLE TODAY

 All HDT-level reporting in HTnM is in Performance
Reporter
‒ Some point-in-time metrics are fed into Mobility

 All HDT reports are custom created
 A set of custom reports are included with this
presentation
HDT AND HTNM
WHAT'S AVAILABLE TODAY

 Nine tables in Performance Reporter for HDP/HDT are
‒ VVOL Tier Type Configuration (Individual DP-VOL capacity info by
tier)
‒ VVOL Tier Type I/O Information (Individual DP-VOL performance
metrics by tier)
‒ HDP Pool Configuration (Design and Capacity Info)
‒ Pool Summary (Total Pool Performance Info)
‒ Pool Tier Type Configuration (HDT Pool Design and Capacity)
‒ Pool Page Relocation (HDT Pool Relocation Info)

‒ Pool Tier Page Relocation (HDT Tier Relocation Info)
‒ Pool Tier Type IO Information (HDT Tier Performance Info)
‒ Pool Tier Type Operation Status (HDT Tier Performance Info)
HDT CAPACITY MANAGEMENT AT THE POOL
HDP/HDT POOL UTILIZATION – USEFUL FIELDS

Physical Used
Time Stamp Type of Pool (HDP/HDT) Provisioned Physical Capacity
for Collection Pool Physical Capacity Capacity
Total Free Physical Capacity %
Used
(Collected Every 8 Hours by
Default)
HDT CAPACITY MANAGEMENT AT THE POOL
HDP/HDT POOL UTILIZATION – NOTES

 Reports on both HDP and HDT pools
 Capacity metrics are in gigabytes
 Using historical information in HTnM, reports detailing
growth of the pool can be used for capacity trend
analysis
 Alerts can be set for pools including usage percentage
and status as warnings for out-of-space conditions
beyond alerts set in HDvM and SN2
HDT CAPACITY MANAGEMENT AT THE POOL
HDT POOL UTILIZATION BY TIER– USEFUL FIELDS

Physical Physical Tier Capacity Used
Tier Capacity Used
Media composition Used Tier Physical Capacity
Free Tier Physical TierTotal Tier Physical Capacity
by Capacity
as % ofPercentage of Tier
as Pool
HDT CAPACITY MANAGEMENT AT THE POOL
HDT POOL UTILIZATION BY TIER – NOTES

 Capacity metrics are in gigabytes
 Trend of size and usage of storage tiers can be obtained
by trending total capacity, used capacity, usage
percentage in pool, or usage percentage in tier
 Alerts can be set for lower tiers to flag high capacity
usage percentage for review. Low tiers by default have
lowest utilization percentage due to HDT standard of
writing to higher tiers first
HDT CAPACITY AT THE DP-VOL
HDT V-VOL UTILIZATION BY TIER – USEFUL FIELDS

LDEV NumberPercent of in tierV-VOL
Size of volume used (in MB)
Tier Number
capacity on each tier.
HDT CAPACITY AT THE DP-VOL
HDT V-VOL UTILIZATION BY TIER - NOTES

 Large capacity proportion (85+%) in single tier may
indicate HDT is not suitable for data type. Investigation of
data workload/type and comparison to other workloads in
pool is suggested
 Large capacity proportion in high tier may indicate a need
for verification of data type on volume
‒ If high-performing but low-value data, use of tiering policy
may eliminate waste

 A historical trend of capacity movement between tiers on
V-VOL may indicate a poor candidate for HDT or a
different HDT architecture required for volume
HDT PERFORMANCE AT THE POOL
HDT POOL IOPS BY TIER – USEFUL FIELDS

Average IOPS Per Tier
HDT PERFORMANCE AT THE POOL
HDT POOL IOPS BY TIER – NOTES

 Data is collected every 15 minutes
 IOPS per tier can be used for historical data analysis and
trending
‒ View IOPS growth per tier over time
‒ Find tiers that are busy during specific cycles
‒ Batch vs. transaction
‒ Backups
‒ Database maintenance
‒ Business vs. after hours
HDT PERFORMANCE AT THE POOL
HDT POOL PERFORMANCE BY TIER – USEFUL FIELDS

Average IOPS PerIOPS Percentage
Average Tier
Utilization Per Tier
HDT PERFORMANCE AT THE POOL
HDT POOL PERFORMANCE BY TIER – NOTES

 Data is collected every monitoring period
 Average IOPS utilization percentage per tier is number of
IOPS processed per tier compared with total IOPS per
tier possible as defined by storage array (same as
performance utilization (P%) in SN2)

 Allows trending of IOPS and tier utilization over time
 Alerts can be set on utilization to monitor when tier gets
to standard load-sharing thresholds (60%) or
overutilization point
HDT PERFORMANCE AT THE POOL
HDT POOL PERFORMANCE BY TIER – NOTES

 Average IOPS utilization percentage provides general insight on
whether HDT design is correct

‒ High IOPS utilization in Tier 1 or 2 indicates Tier 1 may need
additional drives/parity groups to support additional performance
needs
‒ High IOPS utilization in Tier 3 indicates Tier 1 and/or 2 may need
additional drives/parity groups to support additional performance
needs
‒ Low IOPS utilization in a single tier indicates tier may be too large
and can be maintained/reduced in subsequent pool changes
‒ Balanced IOPS utilization under 60% indicates a well-designed
HDT pool
‒ Balanced IOPS utilization over 60% indicates a pool running low
on performance growth capability
HDT PERFORMANCE AT THE DP-VOL
HDT V-VOL PERFORMANCE BY TIER – USEFUL FIELDS

Average IOPS Per Tier Per
V-VOL
HDT PERFORMANCE AT THE DP-VOL
HDT V-VOL PERFORMANCE BY TIER – NOTES

 Metrics collected every 15 minutes
 Provides insight into how IOPS count is broken out by tier
of storage per V-VOL
 Can be used to look at specific V-VOL or application use
of tiers of storage over historical periods
 High IOPS count in low tier of storage with high
concentration of pages in same tier may indicate
additional research to determine if volume or application
is good candidate for HDT
‒ Assuming tiering policy is not in place for V-VOL
HDT RELOCATION MONITORING
HDT POOL RELOCATION STATUS – USEFUL FIELDS

Pages Moved During
Relocation Progress
Relocation Cycle
Percentage During
Relocation Cycle

Relocation Start and Stop
Time
HDT RELOCATION MONITORING
HDT POOL RELOCATION STATUS - NOTES

 Collected after each relocation period
 Progress percentage can be used in alerting customer if
relocation didn’t complete
 Relocation start and end times define how long a
relocation cycle takes
 Relocation cycles that barely finish during relocation
window may indicate collection/relocation configuration
needs adjustment

 Time between relocation start and end divided by number
of pages moved indicates page movement speed (rule of
thumb is ~35 MB/sec)
HDT RELOCATION MONITORING
HDT POOL TIER RELOCATION INFORMATION – USEFUL FIELDS

Promoted and Demoted
Pages by Tier
HDT RELOCATION MONITORING
HDT POOL TIER RELOCATION INFORMATION − NOTES

 Collected after each relocation period
 Promoted pages defines how many pages were
promoted out of this tier
 Demoted pages defines how many pages were demoted
out of this tier
QUESTIONS AND
DISCUSSION
UPCOMING WEBTECHS
 2013 WebTechs
‒ Upgrade Your Enterprise with Hitachi Data Systems, December
4, 9 a.m. PT, noon ET

‒ 2014 schedule to be published soon.

Check www.hds.com/webtech for
 Links to the recording, the presentation, and Q&A (available next
week)
 Schedule and registration for upcoming WebTech sessions
 Questions will be posted in the HDS Community:
http://community.hds.com/groups/webtech
THANK YOU

More Related Content

What's hot

Linux Kernel Cryptographic API and Use Cases
Linux Kernel Cryptographic API and Use CasesLinux Kernel Cryptographic API and Use Cases
Linux Kernel Cryptographic API and Use CasesKernel TLV
 
Dealing with Merge Conflicts in Git
Dealing with Merge Conflicts in GitDealing with Merge Conflicts in Git
Dealing with Merge Conflicts in Gitgittower
 
검은사막 역기획서 - UI편집기
검은사막 역기획서 - UI편집기검은사막 역기획서 - UI편집기
검은사막 역기획서 - UI편집기SeungminBaik1
 
Kernel I/O subsystem
Kernel I/O subsystemKernel I/O subsystem
Kernel I/O subsystemAtiKa Bhatti
 
MySQL Audit using Percona audit plugin and ELK
MySQL Audit using Percona audit plugin and ELKMySQL Audit using Percona audit plugin and ELK
MySQL Audit using Percona audit plugin and ELKYoungHeon (Roy) Kim
 
Operating System 3
Operating System 3Operating System 3
Operating System 3tech2click
 
Linux Memory Management with CMA (Contiguous Memory Allocator)
Linux Memory Management with CMA (Contiguous Memory Allocator)Linux Memory Management with CMA (Contiguous Memory Allocator)
Linux Memory Management with CMA (Contiguous Memory Allocator)Pankaj Suryawanshi
 
Advanced Git Presentation By Swawibe
Advanced Git Presentation By SwawibeAdvanced Git Presentation By Swawibe
Advanced Git Presentation By SwawibeMd Swawibe Ul Alam
 
LLVM Instruction Selection
LLVM Instruction SelectionLLVM Instruction Selection
LLVM Instruction SelectionShiva Chen
 
Asynchronous Python A Gentle Introduction
Asynchronous Python A Gentle IntroductionAsynchronous Python A Gentle Introduction
Asynchronous Python A Gentle IntroductionPyData
 
Git-flow workflow and pull-requests
Git-flow workflow and pull-requestsGit-flow workflow and pull-requests
Git-flow workflow and pull-requestsBartosz Kosarzycki
 
LLVM Backend の紹介
LLVM Backend の紹介LLVM Backend の紹介
LLVM Backend の紹介Akira Maruoka
 
Memory Management
Memory ManagementMemory Management
Memory ManagementVisakh V
 
Lecture 6
Lecture  6Lecture  6
Lecture 6Mr SMAK
 
Launching a BPT Process on Entity Update
Launching a BPT Process on Entity UpdateLaunching a BPT Process on Entity Update
Launching a BPT Process on Entity UpdateOutSystems
 

What's hot (20)

Linux Kernel Cryptographic API and Use Cases
Linux Kernel Cryptographic API and Use CasesLinux Kernel Cryptographic API and Use Cases
Linux Kernel Cryptographic API and Use Cases
 
Dealing with Merge Conflicts in Git
Dealing with Merge Conflicts in GitDealing with Merge Conflicts in Git
Dealing with Merge Conflicts in Git
 
검은사막 역기획서 - UI편집기
검은사막 역기획서 - UI편집기검은사막 역기획서 - UI편집기
검은사막 역기획서 - UI편집기
 
Kernel I/O subsystem
Kernel I/O subsystemKernel I/O subsystem
Kernel I/O subsystem
 
Git Tutorial 教學
Git Tutorial 教學Git Tutorial 教學
Git Tutorial 教學
 
MySQL Audit using Percona audit plugin and ELK
MySQL Audit using Percona audit plugin and ELKMySQL Audit using Percona audit plugin and ELK
MySQL Audit using Percona audit plugin and ELK
 
Operating System 3
Operating System 3Operating System 3
Operating System 3
 
Unit 6
Unit 6Unit 6
Unit 6
 
Linux Memory Management with CMA (Contiguous Memory Allocator)
Linux Memory Management with CMA (Contiguous Memory Allocator)Linux Memory Management with CMA (Contiguous Memory Allocator)
Linux Memory Management with CMA (Contiguous Memory Allocator)
 
Introduction to Git
Introduction to GitIntroduction to Git
Introduction to Git
 
Advanced Git Presentation By Swawibe
Advanced Git Presentation By SwawibeAdvanced Git Presentation By Swawibe
Advanced Git Presentation By Swawibe
 
LLVM Instruction Selection
LLVM Instruction SelectionLLVM Instruction Selection
LLVM Instruction Selection
 
Introducción a GitFlow
Introducción a GitFlowIntroducción a GitFlow
Introducción a GitFlow
 
Asynchronous Python A Gentle Introduction
Asynchronous Python A Gentle IntroductionAsynchronous Python A Gentle Introduction
Asynchronous Python A Gentle Introduction
 
Git-flow workflow and pull-requests
Git-flow workflow and pull-requestsGit-flow workflow and pull-requests
Git-flow workflow and pull-requests
 
LLVM Backend の紹介
LLVM Backend の紹介LLVM Backend の紹介
LLVM Backend の紹介
 
Memory Management
Memory ManagementMemory Management
Memory Management
 
Memory Management
Memory ManagementMemory Management
Memory Management
 
Lecture 6
Lecture  6Lecture  6
Lecture 6
 
Launching a BPT Process on Entity Update
Launching a BPT Process on Entity UpdateLaunching a BPT Process on Entity Update
Launching a BPT Process on Entity Update
 

Similar to Hitachi Dynamic Tiering: An In-Depth Look at Managing HDT and Best Practices, Part 2 of 2

Overview of Hitachi Dynamic Tiering, Part 1 of 2
Overview of Hitachi Dynamic Tiering, Part 1 of 2Overview of Hitachi Dynamic Tiering, Part 1 of 2
Overview of Hitachi Dynamic Tiering, Part 1 of 2Hitachi Vantara
 
VSP Mainframe Dynamic Tiering Performance Considerations
VSP Mainframe Dynamic Tiering Performance ConsiderationsVSP Mainframe Dynamic Tiering Performance Considerations
VSP Mainframe Dynamic Tiering Performance ConsiderationsHitachi Vantara
 
Maximize Operational Efficiency in a Tiered Storage Environment
Maximize Operational Efficiency in a Tiered Storage EnvironmentMaximize Operational Efficiency in a Tiered Storage Environment
Maximize Operational Efficiency in a Tiered Storage EnvironmentHitachi Vantara
 
HDT for Mainframe Considerations: Simplified Tiered Storage
HDT for Mainframe Considerations: Simplified Tiered StorageHDT for Mainframe Considerations: Simplified Tiered Storage
HDT for Mainframe Considerations: Simplified Tiered StorageHitachi Vantara
 
Storage Analytics: Transform Storage Infrastructure Into a Business Enabler
Storage Analytics: Transform Storage Infrastructure Into a Business EnablerStorage Analytics: Transform Storage Infrastructure Into a Business Enabler
Storage Analytics: Transform Storage Infrastructure Into a Business EnablerHitachi Vantara
 
Hitachi command-suite-data-mobility-datasheet
Hitachi command-suite-data-mobility-datasheetHitachi command-suite-data-mobility-datasheet
Hitachi command-suite-data-mobility-datasheetHitachi Vantara
 
Information storage and management
Information storage and managementInformation storage and management
Information storage and managementAkash Badone
 
Meet the Data Processing Workflow Challenges of Oil and Gas Exploration with ...
Meet the Data Processing Workflow Challenges of Oil and Gas Exploration with ...Meet the Data Processing Workflow Challenges of Oil and Gas Exploration with ...
Meet the Data Processing Workflow Challenges of Oil and Gas Exploration with ...Hitachi Vantara
 
Global Financial Leader Consolidates Mainframe Storage and Reduces Costs with...
Global Financial Leader Consolidates Mainframe Storage and Reduces Costs with...Global Financial Leader Consolidates Mainframe Storage and Reduces Costs with...
Global Financial Leader Consolidates Mainframe Storage and Reduces Costs with...Hitachi Vantara
 
Big Data - Hadoop and MapReduce for QA and testing by Aditya Garg
Big Data - Hadoop and MapReduce for QA and testing by Aditya GargBig Data - Hadoop and MapReduce for QA and testing by Aditya Garg
Big Data - Hadoop and MapReduce for QA and testing by Aditya GargQA or the Highway
 
Presto At Arm Treasure Data - 2019 Updates
Presto At Arm Treasure Data - 2019 UpdatesPresto At Arm Treasure Data - 2019 Updates
Presto At Arm Treasure Data - 2019 UpdatesTaro L. Saito
 
S de0882 new-generation-tiering-edge2015-v3
S de0882 new-generation-tiering-edge2015-v3S de0882 new-generation-tiering-edge2015-v3
S de0882 new-generation-tiering-edge2015-v3Tony Pearson
 
Leveraging smart meter data for electric utilities: Comparison of Spark SQL w...
Leveraging smart meter data for electric utilities: Comparison of Spark SQL w...Leveraging smart meter data for electric utilities: Comparison of Spark SQL w...
Leveraging smart meter data for electric utilities: Comparison of Spark SQL w...DataWorks Summit/Hadoop Summit
 
Hitachi Command Suite Overview
Hitachi Command Suite Overview Hitachi Command Suite Overview
Hitachi Command Suite Overview Hitachi Vantara
 
Introduction to Apache Apex - CoDS 2016
Introduction to Apache Apex - CoDS 2016Introduction to Apache Apex - CoDS 2016
Introduction to Apache Apex - CoDS 2016Bhupesh Chawda
 
Real-time Stream Processing using Apache Apex
Real-time Stream Processing using Apache ApexReal-time Stream Processing using Apache Apex
Real-time Stream Processing using Apache ApexApache Apex
 
Low memory footprint programs-iSeries
Low memory footprint programs-iSeriesLow memory footprint programs-iSeries
Low memory footprint programs-iSeriesPrithiviraj Damodaran
 
times ten in-memory database for extreme performance
times ten in-memory database for extreme performancetimes ten in-memory database for extreme performance
times ten in-memory database for extreme performanceOracle Korea
 
Parallel Processing in TM1 - QueBIT Consulting
Parallel Processing in TM1 - QueBIT ConsultingParallel Processing in TM1 - QueBIT Consulting
Parallel Processing in TM1 - QueBIT ConsultingQueBIT Consulting
 

Similar to Hitachi Dynamic Tiering: An In-Depth Look at Managing HDT and Best Practices, Part 2 of 2 (20)

Overview of Hitachi Dynamic Tiering, Part 1 of 2
Overview of Hitachi Dynamic Tiering, Part 1 of 2Overview of Hitachi Dynamic Tiering, Part 1 of 2
Overview of Hitachi Dynamic Tiering, Part 1 of 2
 
VSP Mainframe Dynamic Tiering Performance Considerations
VSP Mainframe Dynamic Tiering Performance ConsiderationsVSP Mainframe Dynamic Tiering Performance Considerations
VSP Mainframe Dynamic Tiering Performance Considerations
 
Maximize Operational Efficiency in a Tiered Storage Environment
Maximize Operational Efficiency in a Tiered Storage EnvironmentMaximize Operational Efficiency in a Tiered Storage Environment
Maximize Operational Efficiency in a Tiered Storage Environment
 
HDT for Mainframe Considerations: Simplified Tiered Storage
HDT for Mainframe Considerations: Simplified Tiered StorageHDT for Mainframe Considerations: Simplified Tiered Storage
HDT for Mainframe Considerations: Simplified Tiered Storage
 
Storage Analytics: Transform Storage Infrastructure Into a Business Enabler
Storage Analytics: Transform Storage Infrastructure Into a Business EnablerStorage Analytics: Transform Storage Infrastructure Into a Business Enabler
Storage Analytics: Transform Storage Infrastructure Into a Business Enabler
 
Hitachi command-suite-data-mobility-datasheet
Hitachi command-suite-data-mobility-datasheetHitachi command-suite-data-mobility-datasheet
Hitachi command-suite-data-mobility-datasheet
 
Information storage and management
Information storage and managementInformation storage and management
Information storage and management
 
Meet the Data Processing Workflow Challenges of Oil and Gas Exploration with ...
Meet the Data Processing Workflow Challenges of Oil and Gas Exploration with ...Meet the Data Processing Workflow Challenges of Oil and Gas Exploration with ...
Meet the Data Processing Workflow Challenges of Oil and Gas Exploration with ...
 
Global Financial Leader Consolidates Mainframe Storage and Reduces Costs with...
Global Financial Leader Consolidates Mainframe Storage and Reduces Costs with...Global Financial Leader Consolidates Mainframe Storage and Reduces Costs with...
Global Financial Leader Consolidates Mainframe Storage and Reduces Costs with...
 
nZDM.ppt
nZDM.pptnZDM.ppt
nZDM.ppt
 
Big Data - Hadoop and MapReduce for QA and testing by Aditya Garg
Big Data - Hadoop and MapReduce for QA and testing by Aditya GargBig Data - Hadoop and MapReduce for QA and testing by Aditya Garg
Big Data - Hadoop and MapReduce for QA and testing by Aditya Garg
 
Presto At Arm Treasure Data - 2019 Updates
Presto At Arm Treasure Data - 2019 UpdatesPresto At Arm Treasure Data - 2019 Updates
Presto At Arm Treasure Data - 2019 Updates
 
S de0882 new-generation-tiering-edge2015-v3
S de0882 new-generation-tiering-edge2015-v3S de0882 new-generation-tiering-edge2015-v3
S de0882 new-generation-tiering-edge2015-v3
 
Leveraging smart meter data for electric utilities: Comparison of Spark SQL w...
Leveraging smart meter data for electric utilities: Comparison of Spark SQL w...Leveraging smart meter data for electric utilities: Comparison of Spark SQL w...
Leveraging smart meter data for electric utilities: Comparison of Spark SQL w...
 
Hitachi Command Suite Overview
Hitachi Command Suite Overview Hitachi Command Suite Overview
Hitachi Command Suite Overview
 
Introduction to Apache Apex - CoDS 2016
Introduction to Apache Apex - CoDS 2016Introduction to Apache Apex - CoDS 2016
Introduction to Apache Apex - CoDS 2016
 
Real-time Stream Processing using Apache Apex
Real-time Stream Processing using Apache ApexReal-time Stream Processing using Apache Apex
Real-time Stream Processing using Apache Apex
 
Low memory footprint programs-iSeries
Low memory footprint programs-iSeriesLow memory footprint programs-iSeries
Low memory footprint programs-iSeries
 
times ten in-memory database for extreme performance
times ten in-memory database for extreme performancetimes ten in-memory database for extreme performance
times ten in-memory database for extreme performance
 
Parallel Processing in TM1 - QueBIT Consulting
Parallel Processing in TM1 - QueBIT ConsultingParallel Processing in TM1 - QueBIT Consulting
Parallel Processing in TM1 - QueBIT Consulting
 

More from Hitachi Vantara

Webinar: What Makes a Smart City Smart
Webinar: What Makes a Smart City SmartWebinar: What Makes a Smart City Smart
Webinar: What Makes a Smart City SmartHitachi Vantara
 
Hyperconverged Systems for Digital Transformation
Hyperconverged Systems for Digital TransformationHyperconverged Systems for Digital Transformation
Hyperconverged Systems for Digital TransformationHitachi Vantara
 
Powering the Enterprise Cloud with CSC and Hitachi Data Systems
Powering the Enterprise Cloud with CSC and Hitachi Data SystemsPowering the Enterprise Cloud with CSC and Hitachi Data Systems
Powering the Enterprise Cloud with CSC and Hitachi Data SystemsHitachi Vantara
 
Virtualizing SAP HANA with Hitachi Unified Compute Platform Solutions: Bring...
Virtualizing SAP HANA with Hitachi Unified Compute Platform Solutions: Bring...Virtualizing SAP HANA with Hitachi Unified Compute Platform Solutions: Bring...
Virtualizing SAP HANA with Hitachi Unified Compute Platform Solutions: Bring...Hitachi Vantara
 
Virtual Infrastructure Integrator Overview Presentation
Virtual Infrastructure Integrator Overview PresentationVirtual Infrastructure Integrator Overview Presentation
Virtual Infrastructure Integrator Overview PresentationHitachi Vantara
 
HDS and VMware vSphere Virtual Volumes (VVol)
HDS and VMware vSphere Virtual Volumes (VVol) HDS and VMware vSphere Virtual Volumes (VVol)
HDS and VMware vSphere Virtual Volumes (VVol) Hitachi Vantara
 
Cloud Adoption, Risks and Rewards Infographic
Cloud Adoption, Risks and Rewards InfographicCloud Adoption, Risks and Rewards Infographic
Cloud Adoption, Risks and Rewards InfographicHitachi Vantara
 
Five Best Practices for Improving the Cloud Experience
Five Best Practices for Improving the Cloud ExperienceFive Best Practices for Improving the Cloud Experience
Five Best Practices for Improving the Cloud ExperienceHitachi Vantara
 
Economist Intelligence Unit: Preparing for Next-Generation Cloud
Economist Intelligence Unit: Preparing for Next-Generation CloudEconomist Intelligence Unit: Preparing for Next-Generation Cloud
Economist Intelligence Unit: Preparing for Next-Generation CloudHitachi Vantara
 
HDS Influencer Summit 2014: Innovating with Information to Address Business N...
HDS Influencer Summit 2014: Innovating with Information to Address Business N...HDS Influencer Summit 2014: Innovating with Information to Address Business N...
HDS Influencer Summit 2014: Innovating with Information to Address Business N...Hitachi Vantara
 
Information Innovation Index 2014 UK Research Results
Information Innovation Index 2014 UK Research ResultsInformation Innovation Index 2014 UK Research Results
Information Innovation Index 2014 UK Research ResultsHitachi Vantara
 
Redefine Your IT Future With Continuous Cloud Infrastructure
Redefine Your IT Future With Continuous Cloud InfrastructureRedefine Your IT Future With Continuous Cloud Infrastructure
Redefine Your IT Future With Continuous Cloud InfrastructureHitachi Vantara
 
Hu Yoshida's Point of View: Competing In An Always On World
Hu Yoshida's Point of View: Competing In An Always On WorldHu Yoshida's Point of View: Competing In An Always On World
Hu Yoshida's Point of View: Competing In An Always On WorldHitachi Vantara
 
Define Your Future with Continuous Cloud Infrastructure Checklist Infographic
Define Your Future with Continuous Cloud Infrastructure Checklist InfographicDefine Your Future with Continuous Cloud Infrastructure Checklist Infographic
Define Your Future with Continuous Cloud Infrastructure Checklist InfographicHitachi Vantara
 
Hitachi white-paper-future-proof-your-datacenter-with-the-right-nas-platform
Hitachi white-paper-future-proof-your-datacenter-with-the-right-nas-platformHitachi white-paper-future-proof-your-datacenter-with-the-right-nas-platform
Hitachi white-paper-future-proof-your-datacenter-with-the-right-nas-platformHitachi Vantara
 
IDC Analyst Connection: Flash, Cloud, and Software-Defined Storage: Trends Di...
IDC Analyst Connection: Flash, Cloud, and Software-Defined Storage: Trends Di...IDC Analyst Connection: Flash, Cloud, and Software-Defined Storage: Trends Di...
IDC Analyst Connection: Flash, Cloud, and Software-Defined Storage: Trends Di...Hitachi Vantara
 
Solve the Top 6 Enterprise Storage Issues White Paper
Solve the Top 6 Enterprise Storage Issues White PaperSolve the Top 6 Enterprise Storage Issues White Paper
Solve the Top 6 Enterprise Storage Issues White PaperHitachi Vantara
 
HitVirtualized Tiered Storage Solution Profile
HitVirtualized Tiered Storage Solution ProfileHitVirtualized Tiered Storage Solution Profile
HitVirtualized Tiered Storage Solution ProfileHitachi Vantara
 
Use Case: Large Biotech Firm Expands Data Center and Reduces Overheating with...
Use Case: Large Biotech Firm Expands Data Center and Reduces Overheating with...Use Case: Large Biotech Firm Expands Data Center and Reduces Overheating with...
Use Case: Large Biotech Firm Expands Data Center and Reduces Overheating with...Hitachi Vantara
 
The Next Evolution in Storage Virtualization Management White Paper
The Next Evolution in Storage Virtualization Management White PaperThe Next Evolution in Storage Virtualization Management White Paper
The Next Evolution in Storage Virtualization Management White PaperHitachi Vantara
 

More from Hitachi Vantara (20)

Webinar: What Makes a Smart City Smart
Webinar: What Makes a Smart City SmartWebinar: What Makes a Smart City Smart
Webinar: What Makes a Smart City Smart
 
Hyperconverged Systems for Digital Transformation
Hyperconverged Systems for Digital TransformationHyperconverged Systems for Digital Transformation
Hyperconverged Systems for Digital Transformation
 
Powering the Enterprise Cloud with CSC and Hitachi Data Systems
Powering the Enterprise Cloud with CSC and Hitachi Data SystemsPowering the Enterprise Cloud with CSC and Hitachi Data Systems
Powering the Enterprise Cloud with CSC and Hitachi Data Systems
 
Virtualizing SAP HANA with Hitachi Unified Compute Platform Solutions: Bring...
Virtualizing SAP HANA with Hitachi Unified Compute Platform Solutions: Bring...Virtualizing SAP HANA with Hitachi Unified Compute Platform Solutions: Bring...
Virtualizing SAP HANA with Hitachi Unified Compute Platform Solutions: Bring...
 
Virtual Infrastructure Integrator Overview Presentation
Virtual Infrastructure Integrator Overview PresentationVirtual Infrastructure Integrator Overview Presentation
Virtual Infrastructure Integrator Overview Presentation
 
HDS and VMware vSphere Virtual Volumes (VVol)
HDS and VMware vSphere Virtual Volumes (VVol) HDS and VMware vSphere Virtual Volumes (VVol)
HDS and VMware vSphere Virtual Volumes (VVol)
 
Cloud Adoption, Risks and Rewards Infographic
Cloud Adoption, Risks and Rewards InfographicCloud Adoption, Risks and Rewards Infographic
Cloud Adoption, Risks and Rewards Infographic
 
Five Best Practices for Improving the Cloud Experience
Five Best Practices for Improving the Cloud ExperienceFive Best Practices for Improving the Cloud Experience
Five Best Practices for Improving the Cloud Experience
 
Economist Intelligence Unit: Preparing for Next-Generation Cloud
Economist Intelligence Unit: Preparing for Next-Generation CloudEconomist Intelligence Unit: Preparing for Next-Generation Cloud
Economist Intelligence Unit: Preparing for Next-Generation Cloud
 
HDS Influencer Summit 2014: Innovating with Information to Address Business N...
HDS Influencer Summit 2014: Innovating with Information to Address Business N...HDS Influencer Summit 2014: Innovating with Information to Address Business N...
HDS Influencer Summit 2014: Innovating with Information to Address Business N...
 
Information Innovation Index 2014 UK Research Results
Information Innovation Index 2014 UK Research ResultsInformation Innovation Index 2014 UK Research Results
Information Innovation Index 2014 UK Research Results
 
Redefine Your IT Future With Continuous Cloud Infrastructure
Redefine Your IT Future With Continuous Cloud InfrastructureRedefine Your IT Future With Continuous Cloud Infrastructure
Redefine Your IT Future With Continuous Cloud Infrastructure
 
Hu Yoshida's Point of View: Competing In An Always On World
Hu Yoshida's Point of View: Competing In An Always On WorldHu Yoshida's Point of View: Competing In An Always On World
Hu Yoshida's Point of View: Competing In An Always On World
 
Define Your Future with Continuous Cloud Infrastructure Checklist Infographic
Define Your Future with Continuous Cloud Infrastructure Checklist InfographicDefine Your Future with Continuous Cloud Infrastructure Checklist Infographic
Define Your Future with Continuous Cloud Infrastructure Checklist Infographic
 
Hitachi white-paper-future-proof-your-datacenter-with-the-right-nas-platform
Hitachi white-paper-future-proof-your-datacenter-with-the-right-nas-platformHitachi white-paper-future-proof-your-datacenter-with-the-right-nas-platform
Hitachi white-paper-future-proof-your-datacenter-with-the-right-nas-platform
 
IDC Analyst Connection: Flash, Cloud, and Software-Defined Storage: Trends Di...
IDC Analyst Connection: Flash, Cloud, and Software-Defined Storage: Trends Di...IDC Analyst Connection: Flash, Cloud, and Software-Defined Storage: Trends Di...
IDC Analyst Connection: Flash, Cloud, and Software-Defined Storage: Trends Di...
 
Solve the Top 6 Enterprise Storage Issues White Paper
Solve the Top 6 Enterprise Storage Issues White PaperSolve the Top 6 Enterprise Storage Issues White Paper
Solve the Top 6 Enterprise Storage Issues White Paper
 
HitVirtualized Tiered Storage Solution Profile
HitVirtualized Tiered Storage Solution ProfileHitVirtualized Tiered Storage Solution Profile
HitVirtualized Tiered Storage Solution Profile
 
Use Case: Large Biotech Firm Expands Data Center and Reduces Overheating with...
Use Case: Large Biotech Firm Expands Data Center and Reduces Overheating with...Use Case: Large Biotech Firm Expands Data Center and Reduces Overheating with...
Use Case: Large Biotech Firm Expands Data Center and Reduces Overheating with...
 
The Next Evolution in Storage Virtualization Management White Paper
The Next Evolution in Storage Virtualization Management White PaperThe Next Evolution in Storage Virtualization Management White Paper
The Next Evolution in Storage Virtualization Management White Paper
 

Recently uploaded

08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 

Recently uploaded (20)

08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 

Hitachi Dynamic Tiering: An In-Depth Look at Managing HDT and Best Practices, Part 2 of 2

  • 1. HITACHI DYNAMIC TIERING (HDT): AN IN-DEPTH LOOK AT MANAGING HDT AND BEST PRACTICES BRANDON LAMBERT, SR. MANAGER MICHAEL ROWLEY, PRINCIPAL CONSULTANT AMERICAS SOLUTIONS AND PRODUCTS
  • 2. WEBTECH EDUCATIONAL SERIES HITACHI DYNAMIC TIERING (HDT): AN IN-DEPTH LOOK AT MANAGING HDT AND BEST PRACTICES, PART 2 OF 2 Hitachi Dynamic Tiering simplifies storage administration by automatically optimizing data placement in 1, 2, or 3 tiers of storage that can be defined and used within a single virtual volume. Tiers of storage can be made up of internal or external (virtualized) storage, and use of HDT can lower capital costs. Simplified and unified management of HDT allows for lower operational costs and reduces the challenges of ensuring applications are placed on the appropriate classes of storage. By attending this webcast, you will • Hear about what makes Hitachi Dynamic Tiering a unique storage management tool that enables storage administrators to meet performance requirements at lower costs than traditional tiering methods. • Understand various strategies to consider when monitoring application performance and relocating pages to appropriate tiers without manual intervention. • Learn how to use Hitachi Command Suite (HCS) to manage, monitor and report on an HDT environment, and how HCS manages related storage environments.
  • 3. AGENDA  The HDT lifecycle  HDT performance basics  HDT basic guidelines  Monitoring HDT with Hitachi Tuning Manager
  • 4. AGENDA  The HDT lifecycle  HDT performance basics  HDT basic guidelines  Monitoring HDT with Hitachi Tuning Manager
  • 5. HDT LIFECYCLE Plan Turn on HDT Heat Maps What to Monitor and Cycle Implement Build HDT Pools Add Daily Monitoring Design HDT Environment Implement Daily Operations (Monitor/Report) Cont. Daily Monitor (Alarm) Capacity Trend/Plan Tune Configuration (HW, Cycle, Ap ps, Policies) Migrate Into Pools Consider HW Limits Historical Performance Trend Adjust Configuration Basic Trend Report (Cap./Perf.) Relocation Reporting (Gradual or Erratic) Performance Trend/ Troubleshoot
  • 6. AGENDA  The HDT lifecycle  HDT performance basics  HDT basic guidelines  Monitoring HDT with Hitachi Tuning Manager
  • 7. HDT PERFORMANCE MONITORING  Back-end I/O (read and write) counted per page during the monitor period IOPH 25  Monitor ignores “RAID I/O” (parity I/O) 20  Count of IOPH for the cycle (period mode) or a weighted average (continuous mode) DP-VOLs 15  HDT orders pages by counts high to low to create a distribution function ‒ IOPH vs. terabytes  Monitor analysis is performed to determine the IOPH values that separate the tiers Monitoring 10 5 0 Page 1 25 Page 999 Pool 20 Aggregate the Data 15 SN2 Analysis 10 5 0 Capacity 1 Capacity nnn
  • 8. POOL TIER PROPERTIES What is being used now in the pool in terms of capacity and performance Can display just the performance graph for a tiering policy The I/O distribution across all pages in the pool. Combined with the tier range, HDT decides where the pages should go
  • 9. CAUTION ABOUT PERFORMANCE UTILIZATION (P%)          P% is only an approximation of tier utilization It is based on assumptions of read/write ratios (50-50) P% does not factor in RAID I/O (parity I/O) It should not be used to calculate I/O counts It should not be used to determine relative utilization at lower P% values - P% is not accurate enough for comparing small differences P% is only used to signal that a tier may be overutilized P% cannot absolutely report that a problem exists Ignore P% unless it is over 60% Prior to V04+a continuous modes, P% uses the weighted average IOPH values. In V04+A continuous mode uses the monitoring result of the last cycle (period mode value) for calculating P% performance utilization A better measure of actual tier utilization is to use parity group utilization
  • 10. TIER RANGE VALUES  Tier range values dynamically change according to workload  Tier range values are always calculated to keep upper tiers generally full  Pages compete for upper tiers. Pages can be pushed down if more aggressive workloads come on the scene  Pages that do not remain “hot enough” (competitive) will demote  Newly active data on dormant (or new) pages or migrated volumes will need protection - Policy settings work well
  • 11. AGENDA  The HDT lifecycle  HDT performance basics  HDT basic guidelines  Monitoring HDT with Hitachi Tuning Manager
  • 12. CHOOSING A MONITOR STRATEGY: RECOMMENDED START POINT  Start with continuous mode  Start with automatic  Start with 8-hour  Investigate Hitachi Tiered Storage Manager for custom scheduling of monitor and relocation cycles
  • 13. CHOOSING A MONITOR STRATEGY  Use tiering policies to protect or restrict tier use  3-tier pool ‒ Liberally use ALL ‒ Use level 4 if Tier 1 use should be restricted (not used) and when Tier 2 is well configured ‒ Note that incorrectly using level 5 will cause performance issues ‒ Levels 1 and 2 can cause overcommitment (and waste) of Tier 1 ‒ Levels 2, 3, and 4 can overcommit Tier 2  2-tier pool ‒ Liberally use ALL ‒ Liberally use level 4 (or 3 or 5) if Tier 1 use should be restricted (not used) and when Tier 2 is well configured
  • 14. RELOCATION RATES  Standard relocation throughput is about 3TB/day  Write pending and MP utilization rate influences the pace of page relocation ‒ When WritePending is 55%, 20-second wait is inserted per page ‒ MP utilization rate influences pacing ‒ ‒ ‒ ‒ ‒ 60% or more: 6 pages or less in 5 seconds 50-60%: 8 pages or less in 5 seconds 40-50%: 10 pages or less in 5 seconds 30-40%: 12 pages or less in 5 seconds 30% or less: Unlimited  When SOM904 is ON, only 1 page is relocated per second ‒ For example, when page migration takes 600 ms, the next page migration starts after sleep for 400 ms (1,000 ms - 600 ms) ‒ If page migration takes 1 second or more, the next page migration starts without sleep procedure. ‒ HDT relocate pages in less than 40MB/sec
  • 15. HDT TUNING SUMMARY  HDT tunes tier ranges dynamically (neither Hitachi Tuning Manager ((HTnM)) or Hitachi Tiered Storage Manager ((HTSM)) is used)  If a tier P% approaches 60% utilization, we aim to move I/O down a tier ‒ 60% sustained I/O to accommodate peaks and prevent queuing ‒ Tier range is increased, reducing the tier’s utilized capacity. All of the tier capacity will not be used – but that is better than overloading the tier with too much IOPH  If all tiers are over (60%/60%/60%), the pool is over utilized − tier ranges are increased again to share the problem  You can’t “lose storage” but you might put more I/O into a pool than it can handle  You should be looking for these situations, evaluating the issues, and adding capacity
  • 16. HDT TUNING SUMMARY  Do not underestimate the importance of Tier-3 performance ‒ HDT will relocate dormant pages to Tier 3. If these pages become active, Tier 3 must perform well enough to cope with some host I/O and relocation I/O  Tiering policy can be used to help or hinder ‒ Helps  Use level 3 or 4 to stage data into Tier 2 before it is needed  Use level 1 or 2 to stage important data before “Mondays” ‒ Hinders  When using level 1-4 on dormant data  Leaving level 1 or 2 set too long  T% and R% should not be changed unless needed to artificially reduce capacity
  • 19. AGENDA  The HDT lifecycle  HDT performance basics  HDT basic guidelines  Monitoring HDT with Hitachi Tuning Manager
  • 20. HDT AND HTNM WHAT'S AVAILABLE TODAY  All HDT-level reporting in HTnM is in Performance Reporter ‒ Some point-in-time metrics are fed into Mobility  All HDT reports are custom created  A set of custom reports are included with this presentation
  • 21. HDT AND HTNM WHAT'S AVAILABLE TODAY  Nine tables in Performance Reporter for HDP/HDT are ‒ VVOL Tier Type Configuration (Individual DP-VOL capacity info by tier) ‒ VVOL Tier Type I/O Information (Individual DP-VOL performance metrics by tier) ‒ HDP Pool Configuration (Design and Capacity Info) ‒ Pool Summary (Total Pool Performance Info) ‒ Pool Tier Type Configuration (HDT Pool Design and Capacity) ‒ Pool Page Relocation (HDT Pool Relocation Info) ‒ Pool Tier Page Relocation (HDT Tier Relocation Info) ‒ Pool Tier Type IO Information (HDT Tier Performance Info) ‒ Pool Tier Type Operation Status (HDT Tier Performance Info)
  • 22. HDT CAPACITY MANAGEMENT AT THE POOL HDP/HDT POOL UTILIZATION – USEFUL FIELDS Physical Used Time Stamp Type of Pool (HDP/HDT) Provisioned Physical Capacity for Collection Pool Physical Capacity Capacity Total Free Physical Capacity % Used (Collected Every 8 Hours by Default)
  • 23. HDT CAPACITY MANAGEMENT AT THE POOL HDP/HDT POOL UTILIZATION – NOTES  Reports on both HDP and HDT pools  Capacity metrics are in gigabytes  Using historical information in HTnM, reports detailing growth of the pool can be used for capacity trend analysis  Alerts can be set for pools including usage percentage and status as warnings for out-of-space conditions beyond alerts set in HDvM and SN2
  • 24. HDT CAPACITY MANAGEMENT AT THE POOL HDT POOL UTILIZATION BY TIER– USEFUL FIELDS Physical Physical Tier Capacity Used Tier Capacity Used Media composition Used Tier Physical Capacity Free Tier Physical TierTotal Tier Physical Capacity by Capacity as % ofPercentage of Tier as Pool
  • 25. HDT CAPACITY MANAGEMENT AT THE POOL HDT POOL UTILIZATION BY TIER – NOTES  Capacity metrics are in gigabytes  Trend of size and usage of storage tiers can be obtained by trending total capacity, used capacity, usage percentage in pool, or usage percentage in tier  Alerts can be set for lower tiers to flag high capacity usage percentage for review. Low tiers by default have lowest utilization percentage due to HDT standard of writing to higher tiers first
  • 26. HDT CAPACITY AT THE DP-VOL HDT V-VOL UTILIZATION BY TIER – USEFUL FIELDS LDEV NumberPercent of in tierV-VOL Size of volume used (in MB) Tier Number capacity on each tier.
  • 27. HDT CAPACITY AT THE DP-VOL HDT V-VOL UTILIZATION BY TIER - NOTES  Large capacity proportion (85+%) in single tier may indicate HDT is not suitable for data type. Investigation of data workload/type and comparison to other workloads in pool is suggested  Large capacity proportion in high tier may indicate a need for verification of data type on volume ‒ If high-performing but low-value data, use of tiering policy may eliminate waste  A historical trend of capacity movement between tiers on V-VOL may indicate a poor candidate for HDT or a different HDT architecture required for volume
  • 28. HDT PERFORMANCE AT THE POOL HDT POOL IOPS BY TIER – USEFUL FIELDS Average IOPS Per Tier
  • 29. HDT PERFORMANCE AT THE POOL HDT POOL IOPS BY TIER – NOTES  Data is collected every 15 minutes  IOPS per tier can be used for historical data analysis and trending ‒ View IOPS growth per tier over time ‒ Find tiers that are busy during specific cycles ‒ Batch vs. transaction ‒ Backups ‒ Database maintenance ‒ Business vs. after hours
  • 30. HDT PERFORMANCE AT THE POOL HDT POOL PERFORMANCE BY TIER – USEFUL FIELDS Average IOPS PerIOPS Percentage Average Tier Utilization Per Tier
  • 31. HDT PERFORMANCE AT THE POOL HDT POOL PERFORMANCE BY TIER – NOTES  Data is collected every monitoring period  Average IOPS utilization percentage per tier is number of IOPS processed per tier compared with total IOPS per tier possible as defined by storage array (same as performance utilization (P%) in SN2)  Allows trending of IOPS and tier utilization over time  Alerts can be set on utilization to monitor when tier gets to standard load-sharing thresholds (60%) or overutilization point
  • 32. HDT PERFORMANCE AT THE POOL HDT POOL PERFORMANCE BY TIER – NOTES  Average IOPS utilization percentage provides general insight on whether HDT design is correct ‒ High IOPS utilization in Tier 1 or 2 indicates Tier 1 may need additional drives/parity groups to support additional performance needs ‒ High IOPS utilization in Tier 3 indicates Tier 1 and/or 2 may need additional drives/parity groups to support additional performance needs ‒ Low IOPS utilization in a single tier indicates tier may be too large and can be maintained/reduced in subsequent pool changes ‒ Balanced IOPS utilization under 60% indicates a well-designed HDT pool ‒ Balanced IOPS utilization over 60% indicates a pool running low on performance growth capability
  • 33. HDT PERFORMANCE AT THE DP-VOL HDT V-VOL PERFORMANCE BY TIER – USEFUL FIELDS Average IOPS Per Tier Per V-VOL
  • 34. HDT PERFORMANCE AT THE DP-VOL HDT V-VOL PERFORMANCE BY TIER – NOTES  Metrics collected every 15 minutes  Provides insight into how IOPS count is broken out by tier of storage per V-VOL  Can be used to look at specific V-VOL or application use of tiers of storage over historical periods  High IOPS count in low tier of storage with high concentration of pages in same tier may indicate additional research to determine if volume or application is good candidate for HDT ‒ Assuming tiering policy is not in place for V-VOL
  • 35. HDT RELOCATION MONITORING HDT POOL RELOCATION STATUS – USEFUL FIELDS Pages Moved During Relocation Progress Relocation Cycle Percentage During Relocation Cycle Relocation Start and Stop Time
  • 36. HDT RELOCATION MONITORING HDT POOL RELOCATION STATUS - NOTES  Collected after each relocation period  Progress percentage can be used in alerting customer if relocation didn’t complete  Relocation start and end times define how long a relocation cycle takes  Relocation cycles that barely finish during relocation window may indicate collection/relocation configuration needs adjustment  Time between relocation start and end divided by number of pages moved indicates page movement speed (rule of thumb is ~35 MB/sec)
  • 37. HDT RELOCATION MONITORING HDT POOL TIER RELOCATION INFORMATION – USEFUL FIELDS Promoted and Demoted Pages by Tier
  • 38. HDT RELOCATION MONITORING HDT POOL TIER RELOCATION INFORMATION − NOTES  Collected after each relocation period  Promoted pages defines how many pages were promoted out of this tier  Demoted pages defines how many pages were demoted out of this tier
  • 40. UPCOMING WEBTECHS  2013 WebTechs ‒ Upgrade Your Enterprise with Hitachi Data Systems, December 4, 9 a.m. PT, noon ET ‒ 2014 schedule to be published soon. Check www.hds.com/webtech for  Links to the recording, the presentation, and Q&A (available next week)  Schedule and registration for upcoming WebTech sessions  Questions will be posted in the HDS Community: http://community.hds.com/groups/webtech