Flash Hypervisor: The Savior to Storage I/O Bottlenecks? Bala Narasimhan

Transcription

1 Flash Hypervisr: The Savir t Strage I/O Bttlenecks? Bala Narasimhan

2 Agenda Case fr server flash in SDDC Technlgy implicatins f marrying hypervisrs with server flash Empirical data Cnclusin and pen issues 2

3 Reference setup Hypervisr Hypervisr Strage system 3

4 Perfrmance r capacity? 4

5 Virtualizatin Flash Current state Desired state + Lw perf at high cst High quality capacity and data services High quality capacity and data services High perf at lw cst But, hw? 5

6 Strage system flash has limits Using strage system flash Many are rip-and-replace slutins Higher latency: SAN Flash is t far acrss the netwrk Lss f applicatin/vm identity Higher cst, lwer scalability, depends n intermediate mving parts 6

7 Server flash with hypervisrs Limited t niche use cases with Lcal datastres, r Single hst read nly cache Nt clustered, breaks crss-hst hypervisr functins Need custm applicatins r in-vm changes Lw perfrmance, less available virtual appliances Hypervisr Hypervisr Strage system 7

8 Time fr a brand new data tier? Sftware + PERFORMANCE TIER + CAPACITY TIER + Data Services 8

9 Scpe f the prblem Frm factr and placement f sftware Optimal flash frmat Clustering f flash resurces Expanding beynd niche use cases 9

10 Hw t leverage server flash Frm factr Lcal datastre, r Acceleratin tier Placement 1. Inside guest OS 2. Virtual appliance 3. Inside hypervisr Hypervisr 10

11 Scale ut Server flash beats SAN IOPS even in small clusters! IOPS 11

12 Read heavy (VDI) results 10 write thrugh Win 7 Linked Clnes running 80% Read, 80% Randm fr 6 minutes [including bt up and shut dwn] 12

13 Flash frmat cnsideratins Hypervisrs need smething else frm flash VM QS management required, nt capacity management Perfrmance islatin between VMs Write intensive: even read intensive wrklads cause (false) writes. E.g 4KB wrklad READ latency sensitive t OIO, presence f WRITES! 300us 100% read, 80% randm, 16 OIOs 3200us 67% read, 80% randm, 64 OIOs 13

14 Clustering cnsideratins What: Transparent remte flash ftprint access n behalf f VMs Hypervisr Hypervisr Strage system 14

15 Clustering cnsideratins - 2 Why Mre efficient use f precius flash Server-2-server netwrk mre scalable Cmpatibility with clustered hypervisr features Challenges Netwrk cache cherency perfrmance and scale undes flash perfrmance 15

16 Latency advantage 16

17 Write prblem - 1 What: Use server flash t accelerate VM writes just like reads Why Make this applicable t mst wrklads Fundamentally change strage infrastructure design Deply strage systems fr new wrst case Hypervisr Delayed writes Strage system 17

18 Write prblem - 2 Challenges Slutin Failure handling Crash cnsistency SAN replicatin Fault tlerant write back acceleratin Hypervisr data replicas Hypervisr Delayed writes Strage system 18

19 Effect f writeback n databases 19

20 The big deal with write acceleratin 20

21 Summary These are the beginnings f a data-in-mtin tier via a Flash Hypervisr What is that? Scale-ut acceleratin: N disruptin t existing VMs and strage systems Hypervisr-resident resurce manager: Virtualizes flash just like hypervisrs virtualize CPU, memry, netwrk Clustered: Allws crss-server access f ht data, and supprt fr clustered hypervisr features (e.g. vmtin) Fault Tlerant: Slves write acceleratin prblem fr wide (infrastructure-level) applicability 21

22 Example: PernixData FVP FVP is sftware t aggregate server-side flash int a scale ut data acceleratin tier Nn-intrusive acceleratin Transparent remte flash access Fault tlerant write acceleratin 22

23 Other pen issues Strage prtcl between data-in-mtin tier and dataat-rest tier Effect n server hardware architecture Strage plicy interface fr flash hypervisrs Strage stack changes t accmmdate flash and many mre 23

24 Thank Mre resurces: 24