Hypervisors and Server Flash Satyam Vaghani

Transcription

1 Hypervisors and Server Flash Satyam Vaghani

2 Agenda r Case for server flash in SDDC r Technology implications of marrying hypervisors with server flash r Empirical data r Conclusion and open issues 2

3 Reference setup Hypervisor Hypervisor Storage system 3

4 Calculator or watch? 4

5 Performance or capacity? 5

6 Virtualization Flash Current state Desired state + Low perf at high cost High quality capacity and data services High quality capacity and data services High perf at low cost But, how? 6

7 Storage system flash has limits r Using storage system flash r Many are rip-and-replace solutions r Higher latency: SAN Flash is too far across the network r Loss of application/vm identity r Higher cost, lower scalability, depends on intermediate moving parts 7

8 Server flash with hypervisors r Limited to niche use cases with r Local datastores, or r Single host read only cache r Not clustered, breaks cross-host hypervisor functions r Need custom applications or in-vm changes r Low performance, less available virtual appliances Hypervisor Hypervisor Storage system 8

9 Time for a brand new data tier? Software DATA-IN-MOTION TIER + + Data Services DATA-AT-REST TIER + 9

10 Scope of the problem r Form factor and placement of software r Optimal flash format r Clustering of flash resources r Expanding beyond niche use cases 10

11 How to leverage server flash r Form factor r Local datastore, or r Acceleration tier Hypervisor r Placement 1. Inside guest OS 2. Virtual appliance 3. Inside hypervisor 11

12 Scale out Server flash beats SAN IOPS even in small clusters! IOPS 12

13 Read heavy (VDI) results 10 writethrough Win 7 Linked Clones running 80% Read, 80% Random for 6 minutes [including boot up and shut down] 13

14 Flash format considerations r Hypervisors need something else from flash r VM QoS mgmt required, not capacity mgmt r Performance isolation between VMs r Write intensive: even read intensive workloads cause (false) writes. Eg 4KB workload READ latency sensitive to OIO, presence of WRITES! 300us 100% read, 80% random, 16 OIOs 3200us 67% read, 80% random, 64 OIOs 14

15 Clustering considerations r What: Transparent remote flash footprint access on behalf of VMs Hypervisor Hypervisor Storage system 15

16 Clustering considerations - 2 r Why r More efficient use of precious flash r Server-2-server network more scalable r Compatibility with clustered hypervisor features r Challenges r Network cache coherency performance and scale undoes flash performance 16

17 Latency advantage 17

18 Write problem - 1 r What: Use server flash to accelerate VM writes just like reads r Why r Make this applicable to most workloads r Fundamentally change storage infra design r Deploy storage systems for new worst case Hypervisor Delayed writes Storage system 18

19 Write problem - 2 r Challenges r Failure handling r Crash consistency r SAN replication r Solution Hypervisor data replicas Hypervisor r Fault tolerant write back acceleration Delayed writes Storage system 19

20 Effect of writeback on databases 20

21 The big deal with write acceleration 21

22 Summary r These are the beginnings of a data-in-motion tier via a Flash Hypervisor r What is that? r Scale-out acceleration: No disruption to existing VMs and storage systems r Hypervisor-resident resource manager: Virtualizes flash just like hypervisors virtualize CPU, memory, network r Clustered: Allows cross-server access of hot data, and support for clustered hypervisor features (eg vmotion) r Fault Tolerant: Solves write acceleration problem for wide (infrastructure-level) applicability 22

23 Example: PernixData FVP r FVP is software to aggregate server-side flash into a scale out data acceleration tier r Non-intrusive acceleration r Transparent remote flash access r Fault tolerant write acceleration 23

24 Other open issues r Storage protocol between data-in-motion tier and data-at-rest tier r Effect on server hardware architecture r Storage policy interface for flash hypervisors r Storage stack changes to accommodate flash r and many more 24

25 Thank More resources: 25