der server - das neue storage array?! - parallel i/okonferenz-nz.dlr.de/pages/storage2016/present/2....

Copyright © 2015 DataCore Software Corp. – All Rights Reserved.


Der Server - das neue Storage Array?!

Thomas Gempe, Regional Manager Ost DataCore Software GmbH

- Parallel I/O -

Copyright © 2015 DataCore Software Corp. – All Rights Reserved. 2

Über 30.000 Installationen weltweit

Über 10.000 Kunden 1998 gegründet

Kunden in allen Branchen und Größen

konzeptionell: Software-defined Storage Hyper-Converged

technologisch: Speicher-Virtualisierung Parallel I/O

• Australien • Deutschland • Frankreich • Japan • UK • USA

Über uns . . .


We’re just over 11 PB of fiber channel block storage, and we’re at roughly two petabytes of NAS. ... it’s pretty big, and it’s growing.

BEYOND KNOWN DATA-RELATED CHALLENGES

55,4% 34,0%

30,4% 29,3% 29,0%

17,7% 17,1% 16,6%

14,2% 14,2%

13,1% 9,5%

4,5%

Dealing with Data/Capacity GrowthCapacity Planning/Forecasting

High Cost of Storage (Capex)Delivering Adequate Storage PerformanceMeeting Disaster Recovery Requirements

High Cost of Storage (Opex)Meeting Backup Windows

Dealing with Multiple Storage SilosLack of Skilled Staff

Meeting Compliance/Regulatory/Governance…Dealing with Storage Migrations

Dealing with New ApplicationsOther

Source: 451 Research, Voice of the Enterprise Storage, Q4 2015

n = 639

“ ”


https://www.techvalidate.com/product-research/datacore-sansymphony-v

Was unsere Kunden bestätigen









DataCore integriert sämtliche Themen: SAN, Flash, Hyper-converged & Cloud Storage

Existing SAN

Virtual SAN

High-end Arrays

Midrange Appliances

Flash Arrays

Cloud High-end Arrays

Midrange Appliances

Flash Arrays

Cloud


Der Speicher (I/O-Vorgänge) bildet den Engpass, insbesondere bei virtualisierten Infrastrukturen

1990 2000 2010 2020

Leistungsunterschied zwischen

Rechenkapazität & Speicher

Rechenkapazität vs. Speicherleistung Jährliche Leistungssteigerung

Rechenkapazität: 26 %

Speicher: 2%

6


TAM an Servern und Speichern > 100 Milliarden USD


DataCore & Parallel I/O sorgen für große Aufmerksamkeit


Serielle vs. parallele Verarbeitung

Arbeitspotential

9


Üblicher Einsatz von Mehrkern-Prozessoren in virtuellen Servern

VM 1

VM 2

VM 3

VM 4

VM 5

inaktiv I/O inaktiv inaktiv inaktiv

Parallele Berechnungen

Serielle I/O-Verarbeitung

VM = virtuelle Maschine

10


Folge: Viele Server erforderlich um die I/O-Last zu verteilen

Workload

Server 1

Server 2

Server 3

Server 4

Server 5

11


Turbolader ermöglicht Parallelisierung von I/O

I/O-Vorgänge halten mit Rechenanforderungen Schritt

Komplette Auslastung der CPU-Kerne

Hohe Arbeitslasten können in kürzester Zeit verarbeitet werden.

Rechen- kapazität

I/O

Arbeitslast

12


Parallel I/O Durchbruch

Zeit – Ersparnis Kosten - Einsparung

Arbeitslasten werden in 1/5 der Zeit erledigt

2 Maschinen erledigen die Arbeit von 10

13


Schluß mit Glaubensfragen – her mit den Fakten –


SPC ist die Basis für Vergleichstests Criteria SPC Benchmark Industry Standard Independently Verified & Audited Peer Reviewed Covers different types & generations of technology Maps to “real world” performance (OLTP databases) Shows cost for achieving performance level

Führende Storage-Hersteller mit SPC Benchmarks

15


SPC-1 Top Dogs # SPC-1

IOPS™ Tested Storage Product Avg Response @ 100% Load (ms) Price

1 5,120,098 DataCore Parallel Server 2-node 0.28 $ 506,525 2 3,010,007 Huawei OceanStor 18800V3 0.92 $ 2,370,763

3 2,004,941 Hitachi VSP G1000 / HP XP7 0.96 $ 2,003,803

4 1,510,090 DataCore Parallel Server 1-node 0.10 $ 136,759

5 1,239,898 Kaminario K2 (K2F00000700) 2.95 $ 997,348

6 1,201,961 DataCore SANsymphony HA-FC 0.22 $ 115,142

7 1,005,893 Huawei OceanStor 18800 5.17 $ 2,794,971

8 780,081 IBM Power 780 server with SSDs 18.9 $ 3,557,709

9 685,281 NetApp FAS8080 EX All-Flash 1.23 $ 1,897,999

10 650,987 Huawei OceanStor 6800 V3 3.36 $ 1.488,036


SPC-1 IOPS: 5,120,098 Avg. Response Time: 0.28 Milliseconds Total Price: $ 506,525 Price-Performance: $0.10 per SPC-1 IOPS Qty 2 Lenovo X3650 M5 Server, each with:

• 2 – Intel® Xeon® 2.30 GHz E5-2699 V3 processors each with 18 cores • 1,536 GB RAM • Mix of SSDs and HDDs internal & external • RAID Controllers & Avago SAS HBA • Qlogic 16 Gbps Fibre Channel HBAs (host connections) • Brocade Switch • UPS

17

#1 DataCore™ Parallel Server Software


World’s Fastest Storage System

Switch 1

Lenovo x3650 M5 Server

Switch 2

16 Gbps Fibre Channel

DataCore™ Parallel Server DataCore™ Parallel Server

Qty 12 SPC-1 Workload Generators


16 Gbps Fibre Channel


$2,370,764 3,010,007 SPC-1 IOPS $0.79 / SPC-1 IOPS 0.92 millisecond response

#2 Huawei OceanStor 18800 V3

DataCore™ Parallel Server


$2,003,803 2,004,941 SPC-1 IOPS $1.00 / SPC-1 IOPS 0.96 millisecond response

#3 Hitachi VSP G1000 w/ Flash a.k.a. OEM HP XP7

DataCore™ Parallel Server


Overview of DataCore SPC-1 Results

21


Results Based on SANsymphony PSP4 2X or better than previously achieved by any company!

DataCore's SPC-1 Price-PerformanceTM

World Record Results!

PERFORMANCE

459,290.87 SPC-1 IOPSTM in 2U

Smallest Footprint

PRICE-PERFORMANCE

$0.08 Per SPC-1 IOPSTM

Lowest Cost, Maximum I/O

RESPONSE TIME

0.32 milliseconds

Ultra Fast Applications


DataCore™ SANsymphony™ SDS

SANsymphony Single Node Hyper-converged


Windows Server

JVM

JVM

JVM

RAM Cache

SANsymphony Hyper-converged Single Node

Configuration SPC-1 Database Workloads


DataCore™ SANsymphony™ SDS


DataCore™ SANsymphony™ SDS DataCore™ SANsymphony™ SDS

DataCore's SPC-1 Price-PerformanceTM

World Record Hyper-converged Results!

PERFORMANCE

1.2 million SPC-1 IOPSTM

Highest Productivity

PRICE-PERFORMANCE


Unmatched Economics

RESPONSE TIME

0.22 milliseconds


High-Availability / Multi-Node / Fibre Channel

Results Based on latest SANsymphony PSP5 release!

SANsymphony Dual Mirrored Nodes Hyper-converged


Windows Server

JVM

JVM

JVM

RAM Cache

Hyper-converged Dual Node HA Configuration

Windows Server

JVM

JVM

JVM

RAM Cache

SPC-1 Workloads SPC-1 Workloads

FC


DataCore Parallel Server Single Node Hyper-converged


Windows Server

JVM

JVM

JVM

RAM Cache

DataCore Parallel Server Hyper-converged Single Node

Configuration SPC-1 Database Workloads


World Record Results!

PERFORMANCE

5.1 million SPC-1 IOPSTM in 18U

Smallest Footprint

PRICE-PERFORMANCE


Low Cost, Maximum I/O

RESPONSE TIME

0.28 milliseconds


DataCore Parallel Server Dual Node + External Storage


DataCore Parallel Server Hosts over FC Switches to External

SAN Multiple SPC-1 Database Workload Drivers


DataCore Technik (Das offene Geheimnis)

32


One Storage Services Platform Any Storage. Any Hardware. Any Hypervisor.

33


RAM is Fast & Inexpensive. Cache uses RAM

What does cache do? I/O Accelerator

Read cache Write Buffer

absorbs bursts I/O Throttling when BE

too slow Read Pre-fetch caching Write Coalesce Fewer

larger BE writes Designed for Multiple

hosts I/O to multiple Vdisks

Memory Requirements, See: FAQ 1543

Average response in µs DataCore L1 Cache < 20 Array L2 Cache 250-300 Disk Drive 4000 - 6000

What Cache Does

Write Read

128M IO Ordering Read Pre-fetch

Write Coalesce

L.R.U. Last Recently Used

Read cache Write cache

PERFORMANCE

http://datacore.custhelp.com/app/answers/detail/a_id/1543/


Auto-Tiering

Up to 15 tiers

Hosts

NL SAS 15k SAS Cloud Storage

Flash

Virtual disks

TIER 1 TIER 2 TIER 3 TIER 4 TIER n

Storage Pool

SATA

RAM Cache

Frequently Accessed

Infrequently Accessed

Moderately Accessed

VIRTUAL DISK

Less Active Data Placed on Slower Storage

SAS SATA Flash Cloud

Hot Cold Warm Archive

More Active Data Placed on Faster Storage

PERFORMANCE

https://www.youtube.com/watch?v=1FQo8ENFb1M





Serial vs. Parallel I/O


Actually it is very different

37

What? I/O Processing is different than Compute work?

And even more different with DataCore !

Lets have a look behind the scene


The CPU – a micro DataCenter

PC

I - B

US

Every single I/O request outside of the CPU needs to ask for an interrupt to process the I/O through the PCI-BUS to a PCI Card

Hey Mr. HBA

May I ask you something?

Yes, Sure, I‘m idle and happy to

help


From / To 1 CPU without DataCore

I/O

I/O Processing using interrupt


Serial I/O Bottleneck in Virtualized Server

Compute waits on I/O CPU cores are wasted Very little work gets done

Compute

I/O

Workload


Impact: Many servers needed to spread I/O

Workload

Server 1

Server 2

Server 3

Server 4

Server 5


DataCore’s so called scheduler is an Interrupt free technology! It handles I/O, based on available CPU / Core speed; limited by the amount of CPU’s available to use

42

DataCore Uses NO Interrupt


I/O

I/O

From / To 1 CPU with DataCore

DataCore: I/O Processing, one available Core no usage of interrupts!

I/O I/O I/O

I/O I/O I/O


This technology already has improved I/O Processing a lot!

44

Already a huge Improvement


While Compute can be done much faster and spread load around different Cores, there is a bottleneck of available Interrupts to process I/O as fast as the Compute work.

45

Today‘s MultiCore CPU‘s are challenged in doing I/O processing


MultiCore - now it gets messy in here

PC

I - B

US

May I ask something?






Hang on!

Wait!

Who was next?

Me! Me!

I‘m busy

Processing Data

OK, Ready


Not only that, DataCore has implemented an interrupt free I/O processing mechanism and it also can allocate up to 256 Cores to parallelize I/O Processing significantly.

47

DataCore‘s Adaptive Parallel I/O is solving the lack of available Interrupts


I/O

I/O

From / to multiple Cores

DataCore Scheduler I/O I/O I/O

I/O I/O I/O

I/O

I/O

I/O I/O I/O

I/O I/O I/O

I/O

I/O

I/O I/O I/O

I/O I/O I/O

I/O

I/O P

roce

ssin

g us

ing

inte

rrup

t


50

Adaptive Parallel I/O

Workload

Response

Time (millisec)

IOPS

No more load

400,000 IOPS < 1 millisec


Worker 1

Worker 2

Worker 3

Worker 4

Worker 5

Worker 6

Worker 7

Worker 8

Worker 9

Worker 10

DataCore’s Adaptive use of Multi-core CPUs in Virtual Servers

VM 1

VM 2

VM 3

VM 4

VM 5

I/O

Parallel Compute

Parallel I/O

VM = Virtual Machine

I/O I/O I/O I/O

VM 6

I/O


The Combination of DataCore’s Multiple Unique Functionalities is the Secret Sauce for delivering the lowest latency and therefore fastest response times in the world!

52

It‘s Not Just a DataCore I/O Scheduler


Path to Solution:

53

Without Limits: DataCore Parallel I/O

Adaptive Caching Auto Tiering

Storage Pooling Adaptive Core

Allocation Interrupt Free Processing

Parallel I/O Thin Provisioning

I/O Scheduling


Parallel I/O changes the storage equation Independent benchmark prove DataCore has

► More IOPS ► Lower Price ► Better Value ► Lower Latency

Run Mission-Critical applications on DataCore

54

Summary


Ihre Wünsche? Performance 24h Betrieb / HA (HW) Unabhängigkeit Konsolidierung Datensicherheit Site-Site distributed LUN

1 PB LUN size 15 Tier (auto sub-LUN) 32 Gbit FC-HBA CDP (SNIA konform) 64 node grid VMware VVol 2.0 cert. Cinder (openstack)


offene Diskussionsrunde… - vielen Dank!

56

der server - das neue storage array?! - parallel i/okonferenz-nz.dlr.de/pages/storage2016/present/2....

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