Transcript
Page 1: Achieving Best Price/Performance for Enterprise Grade …… · Achieving Best Price/Performance for Enterprise Grade SDS with SPDK ... SSD Linux/SPDK Scale out Scale Up Scale out

Copyright 2017 FUJITSU LIMITED

Achieving Best Price/Performance for Enterprise Grade SDS with SPDK

Paul von Stamwitz

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Page 2: Achieving Best Price/Performance for Enterprise Grade …… · Achieving Best Price/Performance for Enterprise Grade SDS with SPDK ... SSD Linux/SPDK Scale out Scale Up Scale out

Synopsis

The Enterprise Storage market is rapidly migrating to NVMe-based all-flash configurations.

However, CPU processing power is falling behind the performance gains in storage, creating inefficiencies in both performance and cost.

To address this, Fujitsu is using SPDK toward the goal of achieving both higher performance and an overall lower cost per IOP for mission-critical workloads.

Copyright 2017 FUJITSU LIMITED1

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Agenda

Background

Why SPDK

How Fujitsu is using SPDK

What are we interested in

Copyright 2017 FUJITSU LIMITED2

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ETERNUS protects customer assets forever and ensures continuous business operation

Accelerating data flows with flash storage

Effectively consolidating storage systems

Managing unpredictable data growth with software defined storage

Radically simplifying backup infrastructures

Fujitsu Storage ETERNUS lineup

All-flash system

ETERNUS AF

Hybrid RAID Storage

ETERNUS DX

Software defined hyper-scale storage

ETERNUS CD10000

Backup Appliances

ETERNUS CS

Tape Libraries

ETERNUS LT

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Enterprise SANs transitioning to SDS

Advantages of SDS:

•Easy to take advantage of latest hardware features

•Easy to change hardware generation without changing operations

External storage configurations changing to AFA

Hybrid will continue to be a significant part of the overall market

Market Trends

All-flash arrays (AFAs)

Hybrid flash arrays (HFAs)

HDD only

Source: IDC, Oct. 2016

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But... CPU/DRAM is the New BottleneckCPU/DRAM not keeping

pace with storage/network

What to do?

Throw more CPU/DRAM at the problem?

Can work

But adds cost

Make the CPU/DRAM more efficient

SPDK

•User space

•Polling

•Zero Copy?

Copyright 2017 FUJITSU LIMITED

$

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SPDK is More Efficient

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Linear scaling for 4 NVMe devices on 1 SPDK core for 4K random reads

0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

1 2 4 8 16 32 64 128 256 512 1024

IOP

S

Queue Depth

1 DEV 2 DEV 4 DEV Kernel

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Target Market

Use Cases

Mission critical, high availability

DB/OLTP acceleration

Business decision acceleration

Virtualized server infrastructure and VDI

Goals:

Ultimate performance

• Best in class IOPS/latency

Cost efficient

• NVMe – best in class $/IOP

• Further cost reduction via inexpensive SSDs or hybrid configurations

Copyright 2017 FUJITSU LIMITED7

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Multiple Hardware Configurations on Same SPDK-based software

AFA Configuration

•More performance

SSDs & Nearline HDDsHybrid Configuration

•Comparable price withHDD systems

Scalability

•Scale out & Scale up

Connectivity

•Frontend: FC, iSCSI and NVM over Fabric

•Backend: NVMe & SAS

•Interconnect:Omni-Path, etc.

NVMeSSD

Linux/SPDK

Scale out

Scale Up

Scale out

Node 0

Node 0

Various Configurations by Common Architecture

NVMeSSD

Linux/SPDK

Node n

Linux/SPDK

SASSSD

NL HDD

Node n

Linux/SPDK

SASSSD

NL HDD

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How Are We Using SPDK

Copyright 2017 FUJITSU LIMITED

Now

Future Interest

Drivers

Storage

Services

Storage

Protocols

iSCSI

Target

NVMe-oF*

Target

SCSI

vhost-scsi

Target

NVMe

NVMe Devices

Blobstore

NVMe-oF*

Initiator

Intel® QuickData

Technology Driver

Block Device Abstraction (BDEV)

Ceph

RBD

Linux

Async IO

Blob

bdevFujitsu

NVMe

NVMe* PCIe

Driver

Released

Q2’17

Pathfinding

vhost-blk

TargetObject

BlobFS

Integration

RocksDB

Ceph

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Thread Model and DPDK

Minimal dependence on DPDK

Currently rely on rte_timer

Copyright 2017 FUJITSU LIMITED

SSD

SSD

SSD

SSD

SSD

SSD

SSD

SSD

SSD

SSD

SSD

SSD

Storage Services

+

Inter-Node Comm.

Host I/F

Host I/F

Dedicated threads

Thread pool

bdev channels

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What Are We Interested In

Bdev

Optimize for NVMe

Need ability to support for SAS/SATA

Robust Error Recovery

Timeouts

Aborts

Monitoring

Performance

Health

Hot-plug

User space TCP

Future

Vhost and NVMeF (target)

Copyright 2017 FUJITSU LIMITED

Enterprise

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Contributions

SPDK community contributions

30+ pull requests

20+ merges

•NVMe-to-SCSI error code translation

•Register callback in the event of a timeout

•Consistent naming

•Abort option in timeout callback

•Etc..

Copyright 2017 FUJITSU LIMITED12

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What are we working on now

NVMe “passthrough” command

IOCTL like interface to obtain Health/SMART log pages

Performance Monitoring

PCIe Hot-plug

FW download

Copyright 2017 FUJITSU LIMITED13

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Conclusion

SPDK is a compelling architecture for Enterprise Grade SDS solutions

Copyright 2017 FUJITSU LIMITED14

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Thank you!

Questions?

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