Database acceleration: 5x transactions per minute and 1/2 the cost of storage. Toby Coleridge, CTO

Transcription

1 Database acceleration: 5x transactions per minute and 1/2 the cost of storage Toby Coleridge, CTO

2 Agenda: Database and USX in the real world Building database applications ontop of Atlantis USX. SQL Performance testing and reference archtiecture 2

3 Case Study: Financial Services Database Performance Benefits 5x performance improvement transactions per minute & batch processing Performance improvements can be achieved without buying additional storage hardware Cost Benefits 5 yr. savings of $1.5M (53%) for each 60TB storage optimized Savings increase to $2.05M (73%) with hyper-converged architecture Projected 5 yr. Savings over $10M for 1.25 petabytes vs. business-asusual architecture Atlantis Computing Confidential & Proprietary 3

4 Previous Architecture EqualLogic Production SAN/LAN - 10GbE iscsi & Fiber channel VMware vsphere Clusters Virtualized Workloads VMware vsphere Clusters Hitachi Data Systems (HDS) Atlantis Computing Confidential & Proprietary VMware vsphere Clusters 4

5 Atlantis USX Architecture USX EqualLogic VMware vsphere Clusters USX Volumes (Datastores) Virtualized Workloads Production SAN/LAN - 10GbE iscsi & Fiber channel USX VMware vsphere Clusters USX Volumes (Datastores) Hitachi Data Systems (HDS) USX Atlantis Computing Confidential & Proprietary VMware vsphere Clusters USX Volumes (Datastores) 5

6 USX ROI Analysis 250TB USX ROI analysis using 250TB shared storage: 5 Year Cost Savings Costs Existing Storage Atlantis USX Consolidating Existing Storage Atlantis USX Hyper-Converged Storage Hardware (SAN, NAS, Flash,SAS/SATA) $ 11,236,943 $ 2,247,389 $15,166 Atlantis USX Software License + Server Cost $ - $ 2,996,883 $ 2,982,604 Total Storage Cost $ 11,236,943 $ 5,244,272 $ 2,997,770 Average Cost per Effective GB/Year $ 4.31 $ 2.17 $ 1.30 Savings Percentage Compared to Existing Storage 0% 53% 73% Atlantis Computing Confidential & Proprietary 7

7 USX ROI Analysis 250TB USX ROI analysis using 250TB shared storage: Atlantis Computing Confidential & Proprietary 8

8 Customer Results Greater than 80% storage footprint reduction (5:1-8:1) for database Reduces storage costs by 53% over 5 years using existing SAN Reduce storage costs by ~ 70% over 5 years by switching to hyper-converged Significant increase in application performance DB Events/Minute increase by 5X Peak test duration (batch job) reduced from 36 to 7 hours Atlantis Computing Confidential & Proprietary 9

9 Building database applications ontop of Atlantis USX. 10

10 Reference Architecture Overview 4 x IBM x3650 M5 2 x 400GB SSD ; 2 * 1.2TB HDD Atlantis USX 2.1; Hybrid Volumes 11

11 SQL Logical Architecture DataBases DataBases DataBases DataBases Windows and SQL Failover Cluster Scale out File Server over iscsi Volume Layer to Aggregate and Present resources Stand Alone NFS/iSCSI Resilience Storage protocol USX Volume VMs Service Layer to make local resource available over the network USX Service VMs vsphere vsphere vsphere vsphere Hypervisor Disk/Memory Disk/Memory Disk/Memory Disk/Memory Local Resources 12

12 SQL Architecture for standalone SQL Server Logs Drive Data Drive USX Volume VM for SQL Logs USX Volume VM for SQL Data USX HA VM USX Service VM USX Service VM USX Service VM USX Service VM 13

13 MS SQL always on Availability Groups Failover Cluster Instances 14

14 SQL Always on USX architecture SQL Server in a WSFC with SOFS USX Volume VM for SQL Logs SQL Server in a WSFC with SOFS USX Volume VM for SQL Data SQL Server in a WSFC with SOFS USX HA VM SQL Server in a WSFC with SOFS USX Service VM USX Service VM USX Service VM USX Service VM Windows Server Failover Clustering (WSFC) has a prerequisite for iscsi. Microsoft best practice is to create a Scale out File Server (SOFS) Cluster Shared Volume on top of the USX iscsi volume. This configuration usually applies to SQL Enterprise licensing. All SQL servers have logs and data drives on different volumes. 15

15 SQL Server 2014 In-memory OLTP OLTP Logging New feature for SQL Server 2014 Holds tables in memory for fast access Operations on In Memory tables are always fully logged for recovery reasons. Due to all operations being logged the benefits of in Memory OLTP increased throughput cannot be achieved without fast write storage for the log file. If In Memory OLTP is being considered it mandates an infrastructure design with very quick underlying storage. As without this, the log file storage quickly becomes the bottleneck and means that any benefits will be negated. 16

16 SQL Testing Results 17

17 IOMeter with SQL IO Profile 18

18 Iometer Latency 19

19 SQLIO Results 20

20 IOPS MB/s IOPS and throughput by block size SQLIO - Single VM Aggregate I/O by Block Size 4 KB 32 KB 64 KB IOPS Throughput 21

21 IOPS MB/s IOPS and throughput by block size SQLIO - Single VM Aggregate I/O by Block Size KB 64 KB 512 KB 0 IOPS USX Throughput USX 22

22 ms Latency by block size 0.6 SQLIO - Single VM Latency by Block Size KB 32 KB 64 KB Read Write 23

23 ms Latency by block size 12.0 SQLIO - Single VM Latency by block size KB 64 KB 512 KB Latency Read USX Latency Write USX 24

24 ms Latency vs Outstanding IO SQLIO - Single VM Latency by Outstanding Ops vs Nutanix USX Read USX Write Nutanix Read Nutanix Write 25

25 IOPS Random IOPS by block size SQLIO - Single VM Random IOPS by Block Size USX (64, 32,4) KB 32 KB 4 KB USX Read USX Write 26

26 60W/40R, 90% random 27

27 TPM vs Users TPM TPM 28