From Rack Scale to Network Scale: NVMe Over Fabrics Enables Exabyte Applica>ons. Zivan Ori, CEO & Co-founder, E8 Storage

Transcription

1 From Rack Scale to Network Scale: NVMe Over Fabrics Enables Exabyte Applica>ons Zivan Ori, CEO & Co-founder, E8 Storage

2 NVMe Over Fabrics Who? Why? How? Who is using NVMe over fabrics? Why do they need it? How do they use it? 2

3 Who needs NVMe over Fabrics Scalability without sacrificing performance Hyperscale Data Center Real-Time Analy-cs Faster >me to results at 70% beter TCO Parallel processing of shared RW data Business Intelligence Transac-onal Processing Low latency for financial transac>ons 3

4 NVMe Enables New Applica>ons Anyone using local SSDs would benefit from NVMe Ideal for: SQL & NoSQL databases Real->me analy>cs High performance distributed KV stores HPC Enables new applica>ons: Machine learning Internet of Things databases and analy>cs Real->me Applica>on Performance Monitoring Real->me Security Audits 4

5 Storage Growth is Data Growth 60% 00% 5% Business volume grows 5% a year The size of their database grows 60% a year Performance load on that database grows 00% year 5

6 SSDs are Becoming Faster 750, (SATA 3Gbps) (SAS 6Gbps) 35,000 57, (NVMe) IOPS read) Read Bandwidth (MB/s) Read Latency 6

7 All-Flash Arrays Lagging Behind NVMe A single NVMe SSD has more performance than an All-flash-array! 750K 3, AFA with 24 SSDs 2,400 Single NVMe (PCIe x4) 300K 00 IOPS (@4K read) Read Bandwidth (MB/s) Read Latency (us)(@4k) 7

8 Classic Scale-Up BoTleneck The all-flash array botleneck is the dual controller itself Server Server Server Server Server Server AFA controller AFA controller SSD SSD SSD SSD SSD SSD SSD SSD SSD SSD SSD 8

9 Customers are Facing a Tough Choice Use SSDs as local storage in their servers to get high performance OR Put those SSDs in AFAs to gain manageability and provisioning Inevitably more and more customers choose to use SSDs as local storage 9

10 The Problem: Using SSDs as Persistent Local Storage The provisioning problem Islands of storage Inefficient capacity u>liza>on Cannot share SSD content between servers Cannot grow storage capacity 0

11 The Problem: Using SSDs as Persistent Local Storage Coupling of storage and compute Up front purchasing decision Repair / upgrade challenges Lifecycle decisions

12 End-to-end NVMe Over Fabrics To the Rescue 0M 40, AFA with 24 SSDs Single NVMe (PCIe x4) E8 D24 (00G NVMf) K 750K IOPS read) Read Bandwidth (MB/s) Read Latency 2

13 Real->me Analy>cs Customer (Financial) Perform decisions at real->me, e.g. market price adjustments Before 576 SSDs in 72 servers Copy nightly the data to all servers AGer 24 SSDs in E8-D24 Share the data from E8 to all 72 servers Shared NVMe reduces the number of replicas needed by 0X - 00X 3

14 In-memory DB Replacement using Storage Class Memory Applica>on example: real->me market price adjustments Before 20TB RAM on 3 servers 20us latency over 40G IB AGer 24 SCM TB SSDs in E8 Share the data from E8 to all database nodes Shared SCM increases storage density and reduces power by over 0: 4

15 Economic Argument for Disaggregated Flash When used as local persistent storage Need to buy SSD with the server Example: 4Y cost of SSDs $60 $80 SSD gradually fills up: but already paid for on day $40 Future projected capacity is paid for in today s price $20 $20 $26 $30 $2 Year Year 2 Year 3 Year 4 E8 Local Save $50M over the 4-year life of a data-center 5

16 Hyperscale Customer: Top-of-the-rack Storage Before 96 servers in a rack 96 * 2.2TB SSDs in servers AGer 92 servers in a rack 24 * 4TB SSDs in E8 box Local SSD Central SSD U-liza-on: 30% U-liza-on: 88% 6

17 Converged Ethernet vs. Segregated Network Converged Ethernet Uses the exis>ng network Reduces equipment and cabling Allows flash to be accessible by all nodes in the network. 7

18 From Rack Scale to Network Scale 200GbE / 400GbE fuels network scale storage High Speed Ethernet On Demand Storage Easily add NVMe capacity to Ethernet Network New enhancements for network growth RoCE Fabric Performance at Network Scale Clustered storage with centralized management 8

19 E8 Performance and Latency LATENCY USEC K 00% RR IOPS/LATENCY 0 2,000,000 4,000,000 6,000,000 8,000,000 0,000,000 2,000,000 IOPS 9

20 E8 Performance and Latency LATENCY USEC K 00% RR BANDWIDTH/LATENCY 0 0,000 20,000 30,000 40,000 50,000 THROUGHPUT (MB/S) 2 0

21 E8 Performance and Latency LATENCY USEC % 8K RR IOPS / LATENCY (RAID6) 0 500,000,000,000,500,0002,000,0002,500,0003,000,0003,500,0004,000,0004,500,000 IOPS 2

22 E8 Storage Rack Scale Flash. No Compromise. PCIe SSD Performance Centralized Storage Reliability Hyperscalability Affordable 00% COTS 2 2