Building All-Flash Software Defined Storages for Datacenters. Ji Hyuck Yun (dr.jhyun@sk.com) Storage Tech. Lab SK Telecom



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Building All-Flash Software Defined Storages for Datacenters Ji Hyuck Yun (dr.jhyun@sk.com) Storage Tech. Lab SK Telecom

Introduction R&D Motivation Synergy between SK Telecom and SK Hynix Service & Solution Provider Mobile & Fixed Broadband Service #1 Carrier in South Korea Develop, Operation, and Management National Network Infrastructure Datacenter IT Infrastructure Reducing TCO, improving delivered QoS SK Hynix merged into SK Telecom at Feb. 2012 Memory Solution Manufacturer R&D on ICT Infra & System Server, Network, Storage, Platform, S/W-defined x Real-world workloads & benchmarks 1 1

Introduction Key Target Areas Cloud Computing, Big Data, and Video Technologies selected to leverage the effectiveness of flash Major Trends Cloud Flexible, Scalable, Workloads, Unmet needs, Pilot Test Cloud, Video, Big Data Infra With Real workloads Agile Infra : Scale-out Storage Vertically Optimized System Enhanced by Flash Tech Big Data Massive Information : Data Analytics Video High Quality Contents : Video Streaming 1 All-flash Scale-out Storage for Cloud Infra S/W-defined Platform System/Infra HW Architecture OS Kernel SW Device (RTL/Firmware) Memory Semiconductor 2 All-flash CDN Server for Video Streaming CEPH CDN 3 Big Data Analytics System Accelerator Spark Hadoop 2 2

1 All-flash Scale-out Storage All-flash Storage Trend In the enterprise, both scale-up & scale-out storage are evolving to all-flash to meet with increasing performance requirements of recent applications HDD or Hybrid All-flash Scale-up Storage EMC, NetApp, etc All-flash Evolution for Performance Maximization Pure Storage, etc Traditional Infra Target Low Cost Scale-out Architecture for Cloud Infra CEPH*, etc SolidFire, etc Targeting to Cloud Infra Target SKT SDDC Infra Scale-out Storage Commodity Server H/W + Scale-out Storage S/W (Minimizing Infra TCO) SKT is optimizing CEPH by customizing storage and network S/W stack for flash Commodity Server H/W w/ All SSD (SKH Commodity 2.5 ) (Openstack based Private Cloud) Infra Cost Scalability *CEPH: Open-source scale-out storage S/W to present object, block, and file storage from distributed servers 3 3

1 All-flash Scale-out Storage CEPH Architecture CEPH provides scale-out capacity expansion but performance is inherently restricted because of its HDD centric design Operation : Data Write Applications (VM) Data Server Pool (Server Virtualization) Hypervisor Hypervisor Ceph Client Ceph Client Hypervisor Ceph Client RBD Lib. @Client Object 1. Data Striping (Default 4MB) 2. Data Deployment : CRUSH Algorithm Mgmt. Pool Ceph Node (Monitor Node) - Node Fail Mgmt. - Node Expd. Mgmt. Storage (OSD Node) Pool Ceph Node Ceph Node Service Network Map Info, Min 3 Nodes Ceph Node Data Storage Ceph Node PG#0 OSD Service @OSD Node OSD OSD #0 PG #0 PG #3 PG#1 PG#2 PG#3 Storage Pool 1 st Write for ACK OSD #3 PG #1 PG #3 OSD #5 PG #2 PG #3 Read Write Service Network (Ethernet/Infiniband) 3. Replica for Reliability 4. a) Journaling b) Data Storage Storage Network Journal PG#0 CEPH Scale-out Storage System PG#3 4 4

1 All-flash Scale-out Storage System Configurations ( 15.8) SK Telecom CEPH system consists of 1U servers for a small footprint, and employs an NVRAM SSD hierarchy to achieve high performance. Configurations : 4 Node + Microserver 1 set Monitor Node (3ea) 2U OSD Node SKT Microserver - CPU: Intel Rangeley C2738 (2.4GHz/8C) - DRAM: 32GB/1600MHz - Network: 10GbE/1GbE NVRAM (8GB) SW RAID0 (Striping) `15.12 Target CEPH Node H/W Spec. - CPU: 2x E5-2690v3 - DRAM: 128GB /2133 MHz - Network: 10GbE for Service, 10 or 40GbE for Storage - Replication: 2 - Storage: NVDIMM (8GB) for Journal, SSD for File Store SSD#0 SSD#1 SKH SATA SSD - 1TB (or 2TB) capacity based - Physical Capacity per Node: 10TB Journal Data Storage OSD Configuration 5 5

1 All-flash Scale-out Storage R&D Progress SK Telecom has done an in-depth analysis of CEPH, and has implemented customizations and optimizations to better exploit the performance of flash `15 CEPH OSD Node 1 Optimizations OSD Optimizations Lock, thread, priority. OSD OSD Service Service #0 #1 OSD Service #k Light-weight Ceph Service NVRAM/NVDIMM Deployment High Performance Network & Protocol 40GbE, infiniband, RDMA, etc. N/W Stack + NIC File System (Ext4, BTRFS,XFS) Block Device Driver SSD SSD SSD 2 Efficient Object Storage `16~ Non-File System Key/Value Storage (Key/Value APIs, Proprietary SSD) - File-system Overhead Elimination - Efficient meta-data mgmt. Introducing NVMe Flash SSD 6 6

1 All-flash Scale-out Storage Evaluation Results <Read Performance> <Write Performance> 134K 255K (Random 4K IOPS) 37K 55K (Random 4K IOPS) We are open to collaboration with the goal of achieving maximum performance in all-flash CEPH systems 7 7

2 All-flash VoD Streaming System CDN Infrastructure Trends Example of Content Delivery Network Infra Hot contents are cached geographically at local sites to reduce overall network traffic and to guarantee on QoS of VoD Streaming. To cache video contents, each local site has CDN server clusters. The number of CDN servers is determined in order to meet the maximum required service bandwidth of customers living in that area. As the number of customers increases and video contents quality become better, the number of CDN servers and capacity of CDN servers grow simultaneously. CDN Server R&D Target Infra TCO Reduction can be achieved by Service Bandwidth Increase Server BOM Reduction Power consumption reduction Footprint reduction 8 8

2 All-flash VoD Streaming System System Architecture Optimization High performance, high density, low power, and low cost are achieved by eliminating redundant components in I/O path, PCIe connected flash, and utilizing an optimal CPU. Legacy CDN Server Architecture SKT STOM CDN Server Architecture Intel 2.6GHz E5 CPU 2EA PCIe FC HBA FC HBA Optimization High Density Server (Only Essential Components for VoD) Intel ATOM Rangeley PCIe Server FC 8Gbps FC 8Gbps Storage FC HBA FC HBA PCIe Storage Controller Elimination PCIe Switch RAID Controller PCIe RAID Controller Disk Array (SAS 70ea) Optimization PCIe Flash Flash PCIe Card PCIe Card SSD Array (16 ea) STOM_P1, STOM_P2 STOM_S16 In-service CDN (Edge) Server Architecture (3.3Gbps Service) 9 9

2 All-flash VoD Streaming System Product Portfolio SKT STOM series consists of P1(5TB), P2(10TB), S16(14TB) models, supporting various requirements: high performance/high density/low power/low cost. Model Form factor Storage Support Main Features (For Each Node) High performance of all-flash Fast Retrieval of Video Contents Capacity: 5TB~16TB STOM_P1 (Performance Density) 4 Server Nodes in 2U (0.5U Server effectively) Flash PCIe Card 1EA / Each Node Storage Capacity: - 5TB (w/ 1x 5TB PCIe Card) Network Interface: - 4 x 1Gbe Copper ports - 2 x 10Gbe Fiber ports Max. Bandwidth: - HTTP: >18Gbps Dedicated appliance for VoD Component optimization for VoD Flexibility of density/capacity/cost STOM_P2 (Performance Capacity) 2 Server Nodes in 2U (1U Server effectively) Flash PCIe Card 2EA / Each Node Storage Capacity: - 10TB (w/ 2x 5TB PCIe Card) Network Interface: - 4 x 1Gbe Copper ports - 2 x 10Gbe Fiber ports Max. Bandwidth: - HTTP: >18Gbps NVMe PCIe Flash Card 1EA/2EA, 2.5 SATA SSD 16EA STOM_S16 (Capacity Cost) 2 Server Nodes in 2U (1U Server effectively) 2.5 SATA SSD 16EA / Each Node Storage Capacity: - 8TB (w/ 16x 0.5TB SSD) - 16TB (w/ 16x 1TB SSD) Network Interface: - 4 x 1Gbe Copper ports - 2 x 10Gbe Fiber ports Max. Bandwidth: - HTTP: >18Gbps 10 10

2 All-flash VoD Streaming System Competitiveness of all-flash SKT STOM servers can cut power consumption by 90% and cost by 40% compared to a HDD-based CDN server HDD CDN Server (`15) SKT STOM: All-flash CDN Server (`15) 2U 2 servers in 2U Footprint (Size) 1U 2U SKT PCIe Card CDN Server CDN Server SKH SATA SSD STOM-A_P2 STOM-A_S16 Computing Intel E5 Power & BOM reduction Intel Atom Rangeley Power & BOM reduction Intel Atom Rangeley Max Service BW 10Gbps(RTSP) ~ 10Gbps(RTSP) ~20Gbps(HTTP) ~ 10Gbps(RTSP) ~20Gbps(HTTP) Storage Module 300GB HDD 70EA (15TB*) Performance focused SKT PCIe Card 5TB 2EA (10TB) Capacity & Cost focused SKH SATA SSD 1TB 16EA (14TB*) Streaming Contents Full HD Full HD Ultra HD Full HD Power Consumption 200 W/Gbps (Estimated) 90% 17 W/Gbps 95% 11 W/Gbps * Total Usable Capacity by RAID Configuration 11 11

2 All-flash VoD Streaming System STOM Performance 12 12

2 All-flash VoD Streaming System Next R&D Next generation of STOM exploits state-of-art Intel CPUs and provides higher density storage STOM-A Family STOM-D Family (`15.4Q) Intel Atom Rangeley SoC STOM-A P1 (`15.2) STOM-A P2 (`15.3) STOM-A S16 (`15.4) Max. BW: Storage: - RTSP: >9Gbps - 1x PCIe Card - HTTP: >16Gbps Max. BW: Storage: - RTSP: >9Gbps - 2x PCIe Card - HTTP: >16Gbps Max. BW: Storage: - RTSP: >9Gbps - 16x 2.5 SATA - HTTP: >16Gbps Intel High Performance Enterprise CPU (`15.3 Release) High Performance XEON Architecture 14nm Tech, DDR4 Memory Cost/Density Competitive Edge (Identical Design) Intel Xeon D SoC STOM-D P2 STOM-D S16 Max. BW: - RTSP: ~20Gbps - HTTP: ~40Gbps Max. BW: - RTSP: ~20Gbps - HTTP: ~40Gbps Storage: - 2x PCIe Card Storage: - 16x 2.5 SATA Max. BW: Expected x2 Application Performance Ultra High Performance/Massive Capacity CDN Server : STOM-E (`16.1H) Max. CPU Performance (Encryption, etc.), Wide N/W (80Gbps), Massive Storage, Space Efficiency (1U) Computing (Xeon-D or Xeon-E5) & Storage (SATA SSD or NVMe SSD) Modular Architecture 13 13

3 Big Data Analytics Accelerator Enhancing T-DW (SK Telecom s Hadoop-based Data Warehouse solution) by employing SSDs with customized caching SW T-Data Warehouse Ex) Big Data from N/W Equipments are analyzed to operate and mgmt. infrastructure more effectively and make N/W stable to the limit. TPC-H Comparison to conventional flash caching SW in Hadoop DW Environment (Feasibility Test) SSDs are applied with customized caching SW to workloads SSD to each server for cache Applied to SK Telecom infrastructure in `15 Hadoop/Spark based cost-effective solution We observe that storage I/O can be much reduced by customizing caching SW to Hadoop workload. (Deployment of SSD caching in SKT s infrastructure in progress) 14 14

Thank you Please visit us at Booth #107 15 15