Architecting For Availability, Performance & Networking With ScaleIO
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- Caitlin Short
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1 Architecting For Availability, Performance & Networking With ScaleIO
2 Performance is a set of bottlenecks Performance related components:, Operating Systems Network Drives Performance features: Caching Reliability & Availability 2
3 What is Dell EMC ScaleIO? Software-Defined Storage that uses x86 servers to create an elastic/flexible, scalable, and resilient block storage infrastructure that reduces the complexity of traditional SANs Installs on industry-standard x86 servers Aggregates application servers local disks Add storage and/or compute on the fly ScaleIO agent (minimal footprint) 3
4 Multiple consumption choices Buy Buy & Build Build Lowest Risk, Highest Value, Lowest TCO Hyper-converged rack-scale engineered system ScaleIO software and optimized Dell PowerEdge servers Maximum Flexibility & Choice More Time & Resources ScaleIO software only Consume Maintain 4
5 ScaleIO software-defined stack ScaleIO Data Client (): A lightweight device driver that exposes ScaleIO volumes as block devices to the application. resides on the same server as the application. ScaleIO Data Server (): Manages the capacity of a server and acts as a backend for data access. resides on all servers contributing storage devices (drives). MDM Meta Data Manager (MDM): Configures and monitors the ScaleIO system. 6
6 ScaleIO configurations: 2-layer Server SAN Ethernet access app nodes dedicated to serving storage ETHERNET app app app Operationally separated Drop-in replacement for traditional storage Any x86 OS, any combination of operating systems and hypervisors is possible app 7
7 ScaleIO configurations: Converged CI or HCI vsphere Cluster app app Cluster app app Both and on the same node CPU and memory efficient app ETHERNET app app app app app 8
8 ScaleIO configurations: Hybrid app app app ETHERNET app app app One ScaleIO cluster -only, only, and + nodes all possible Scale storage and compute independently app app 1
9 Elasticity of architecture No fixed number of storage devices or nodes Grow and shrink at will, ScaleIO rebalances continuously 12
10 / Performance
11 performance top: 14
12 Max IOPs per node limited config (drives, Network etc. are not the limit) 25, Max 4KB IOPs 236,168 Default profile vs. performance profile IOPs Writes about half the Read IOPs IOPs 2, 15, 1, 5, 156,431 57,67 99,599 Default Profile Performance Profile Different CPUs will have different performance Read Write RHEL
13 CPU utilization CPU Core Util % CPU Core Util % % 892% 461% 458% Default Profile Performance Profile Read Cpu % Write Cpu % 4-5 Logical Cores used with default profile ~9 Logical Cores used with performance profile 2x2698V4 CPU has 2x2x2 =8 Logical cores 9/8 = 11% CPU utilization 16
14 CPU utilization linear with IOPs 4KB Read IOPs vs. CPU% 4KB Write IOPs vs. CPU% 12% 1% 11% 12% 1% 11% CPU % 8% 6% 7% CPU % 8% 6% 7% 4% 4% 4% 4% 2% % 1% 2% 5, 1, 15, 2, 25, 3, 2% % 2% 1% 2, 4, 6, 8, 1, 12, IOPs IOPs Utilization on a node with 2x2698V4 CPU (2 Cores each) Cores are only used when workload is generated 17
15 performance top: 18
16 Max IOPs per node limited config (, drives, Network etc are not the limit) Default profile vs. performance profile IOPs IOPs 6, 5, 4, 3, 2, Max IOPs 553, , ,996 26,976 Default Profile Performance Profile Writes are the same as the Read IOPs Different CPUs will have different performance 1, Read Write RHEL
17 CPU utilization CPU Core Util % % 616% CPU Core Util % % 198% Default Profile Performance Profile 1 ~2 Logical Cores used with default profile ~6 Logical Cores used with performance profile 2x2698V4 CPU has 2x2x2 =8 Logical cores 6/8 = 7-8 % CPU utilization 2 Read Cpu % Write Cpu %
18 CPU utilization linear with IOPs 4KB Read IOPs vs. CPU% 4KB Write IOPs vs. CPU% 8% 7% 8% 8% 7% 7% CPU % 6% 5% 4% 3% 2% 1% % 6% 3% 1% % 1, 2, 3, 4, 5, 6, CPU % 6% 5% 4% 3% 2% 1% % 6% 3% 1% % 1, 2, 3, 4, 5, 6, IOPs IOPs Utilization on a node with 2x2698V4 CPU (2 Cores each) Cores are only used when workload is generated 21
19 Bottom line CPU usage Reasonable limits are 1-2K Reads/sec Reasonable limits are 2-5K IOs/sec ScaleIO consumes minimal CPU resources: CPU utilization is proportional to the IOPs At max IOPs ~11% for and ~8% for with Real life workloads usually ~5% 22
20 Other I/O Sizes & Network Limits
21 IOPs per node vs. IO size, 2x1Gb IOPs 3, 236,168 25, 2, 15, 1, 5, Reads IO size Max IOPs change with IO size Dell Ready Node R63 with 2698V4 CPU RHEL
22 IOPs per node vs. IO size, 2x1Gb IOPs 3, 25, Reads 236,168 2,343 MB/sec 3, 2,5 IOPs 12, 1, 99,599 Writes 1,162 MB/sec 1,4 1,2 2, 15, 1, 5, 2, 1,5 1, 5 Linux IOPs Linux MB/s 8, 6, 4, 2, 1, Linux IOPs Linux MB/s IO size IO size Max IOPs and MB/sec per IO size Network bandwidth with 2x1Gb is limited to: ~2GB/sec for Reads ~1GB/sec for Writes 25
23 IOPs per node vs. IO size, 2 vs. 4x1Gb IOPs 25, 2, 15, 1, 5, 512B Reads 2 vs. 4x1Gb Ethernet ports 212,546 2,337 4K 8K 16K 32K 64K 128K 256K 512K 1M IO size MB/sec 5, 4,5 4, 3,5 3, 2,5 2, 1,5 1, 5 Dell 73 with 2 x 1GB NIC IOPS Dell 73 with 2 x 1Gb NIC MB/s IOPs 1, 9, 8, 7, 6, 5, 4, 3, 2, 1, 512B Writes 2 vs. 4x1Gb Ethernet ports 91,55 1,162 4K 8K 16K 32K 64K 128K 256K 512K 1M IO size MB/sec 2,5 2, 1,5 1, 5 Dell 73 with 2 x 1Gb NIC IOPs Dell 73 with 2 X 1Gb NIC MB/s Max IOPs and MB/sec per IO size for an R73xd Storage Only 1x265V4 CPU config with 2-4x1Gb network, RHEL
24 IOPs per node vs. IO size, 2 vs. 4x1Gb IOPs 25, 2, 15, 1, 5, 512B Reads 2 vs. 4x1Gb Ethernet ports 212,546 4,494 2,337 4K 8K 16K 32K 64K 128K 256K 512K 1M IO size MB/sec 5, 4,5 4, 3,5 3, 2,5 2, 1,5 1, 5 Dell 73 with 2 x 1GB NIC IOPS Dell 73 with 4 X 1Gb NIC MB/s Dell 73 with 2 x 1Gb NIC MB/s IOPs 1, 9, 8, 7, 6, 5, 4, 3, 2, 1, 512B Writes 2 vs. 4x1Gb Ethernet ports 91,55 2,332 1,162 4K 8K 16K 32K 64K 128K 256K 512K 1M IO size MB/sec 2,5 2, 1,5 1, 5 Dell 73 with 2 x 1Gb NIC IOPs Dell 73 with 4 X 1Gb NIC MB/s Dell 73 with 2 X 1Gb NIC MB/s Max IOPs and MB/sec per IO size for an R73xd Storage Only 1x265V4 CPU config with 2-4x1Gb network, RHEL
25 Bottom line - network limits Max IOPs depend on the IO size The large IOs are limited by the network ScaleIO can consume network bandwidth: 2x1Gb ports per node: ~2GB/sec of Reads and ~1 GB/sec of Writes 4x1Gb ports per node: ~4GB/sec of Reads and ~2 GB/sec of Writes 4x25Gb ports per node: ~1GB/sec 1x1Gb ports per node: ~1GB/sec not a good idea because of redundancy Different configs will have a slightly different performance 3
26 Performance of Different Operating Systems
27 IOPs per node per operating system Max IOPs for different OSs ESX performance lower than Linux and Windows 25, 2, 236,168 23,754 4K IOPs ESX direct Path 15-2% faster than non-direct path 15, 1, 143, ,663 99,599 94,886 5, 56,73 48,15 4K Read 4K Write Linux Windows ESX Direct Path ESX Non-Direct Path 32
28 Scalability
29 ScaleIO scales linearly The latest high-end HDS storage can do ~5M IOPs HP system, 3PAR 285 AFA 2.5-3M IOPs 35
30 GUI Read workload 36
31 Scalability with 249 nodes 38
32 Bottom line - scalability ScaleIO scales almost linearly ScaleIO outperforms HDS and HP many times over Using a fraction of the existing application servers minimizes the cost of the storage 4
33 Caching
34 Caching boost HDD performance Better Response Time and increased max IOPs DRAM as cache: RMCache ScaleIO Read RAM Cache SSD/Flash as Cache RFCache DAS Cache 44
35 Some notes about Cache Use Cache for HDD configs Flash/SSD only configs do not need cache! Cache improves the performance up to the HHD limits In Converged Infrastructure configs, using DRAM for Read Cache may take away from the application cache Cache works when there is a skew in the workload 8% of all IO accesses 2% of the capacity 45
36 SSD Read+Write Cache IOPS 4K Reads, 312GB TAS, 124t - DAS Cache (5 HDD/1 SSD) 12, 1, 8, 6, 4, 2, HDD performance ,117 1,33 1,489 1,675 1,861 2,47 2,233 2,419 2,65 2,791 2,977 3,163 3,349 3,535 3,721 3,97 4,93 4,279 4,465 4,651 4,837 (sec) IOPs grow and Response time shrinks with time because more of the IOPs are serviced from cache Cache takes time to warm up SSD performance IOPS 7, 6, 5, 4, 3, 2, 1, DAS cache, 4KB Writes, 9GB SIO volume per node, 5 HDDs/1 SSD SSD performance ,65 1,217 1,369 1,521 1,673 1,825 1,977 2,129 2,281 2,433 2,585 2,737 2,889 3,41 3,193 3,345 3,497 3,649 3,81 3,953 4,15 4,257 4,49 4,561 4,713 4,865 (sec) HDD performance DAS-Cache buffers the writes as they arrive, then destaged to the HDDs At no point is the performance worse than HDD only 46
37 ScaleIO Response Times
38 Response times in ScaleIO - SSD RT (msec) IO RT SSD KB 8KB 16KB 32KB 64KB Read RT Write RT RT (msec) IO RT SSD Read RT Write RT Response Time (RT) is a critical aspect of performance RT is shown for a single threaded workload Write RT is about 3% higher than Read RT 48
39 Response times in ScaleIO - HDD The Raid controller makes the HDD write RT better than Reads At high IO Write rates the writes will be serviced from the HDD and the Write RT will be similar to Read RT Note that real life workloads have bursts causing the IOs to be queued which will affect the RT RT (msec) IO RT HDD Read RT Write RT 5
40 Bottom line response time Great Read and Write Response Times 51
41 Drive Limits
42 SSD drive IOPs limits 8KB Reads 8 KB Writes IOPS 12, 1, 8, 6, 4, 2, 16 99, , , ,861 Toshiba_PM4_8GB_ 1WPD Toshiba_PM4_16GB _1WPD Toshiba_PM4_192GB _3WPD Toshiba_PM4_192GB _1WPD IOPS 7, 6, 5, 4, 3, 2, 1, 65,539 59,41 38,353 18,416 Toshiba_PM4_8GB_ 1WPD Toshiba_PM4_16GB _1WPD Toshiba_PM4_192GB _3WPD Toshiba_PM4_192GB _1WPD 5 1, 1, total queue depth total queue depth Different SSD drives will have VERY different Write IOPs limits! Read IOPs are very close 54
43 SSD drive MB/sec limits 256 KB Reads 256 KB Writes 1,2 6 1, 1, MB/Sec Toshiba_PM4_8GB_ 1WPD Toshiba_PM4_16GB _1WPD Toshiba_PM4_192GB _3WPD Toshiba_PM4_192GB _1WPD MB/Sec Toshiba_PM4_8GB_ 1WPD Toshiba_PM4_16GB _1WPD Toshiba_PM4_192GB _3WPD Toshiba_PM4_192GB _1WPD total queue depth total queue depth Different SSD drives will have VERY different Write MB/sec Flash drive concern is wear! 55
44 Bottom line drive performance HDD max drive IOPs depends on the queue and Response Time Reasonable values are: 7.2K: 5 1K: 11 15K: 13 Flash: varies significantly especially on Writes! Be weary of wear! Vendor performance focuses on Seq operation, can be misleading 56
45 Dell EMC PowerEdge 14G R64, R74xd
46 New Dell EMC PowerEdge14G servers Skylake CPUs Boot Optimized Storage Solution (BOSS ) NVDIMM-N More drive slots NVMe drives GPUs R74xd R64 63
47 Availability & Reliability
48 Reliability and availability definition Reliability: is the probability of not having a failure event during some period of time Availability: is the percentage of time the data will be available In other words reliability is the absence of failure. Availability relates to duration of time that the system is operating normally. 65
49 Reliability life time = MTBF: Mean Time Between Failures Enterprise level drives have ~8, hours of MTBF, which is about 9 years 9 drives will have a drive failure every year 9 drives will have a failure every 5 weeks Since drives are protected, one drive failing isn t an issue. The risk of a DU/DL starts after a drive fails. If another drive from the same protection group will fail we have a risk of losing data. This is why rebuild time is so important 66
50 (Un)Availability Availability = MTBF MTBF+RTO % up time, or 6 9 s What is the difference between 6 9's and 3 9's? 6 9's are equivalent to being down half a minute in a year 876 * ( ) *36 = 31 seconds 5 9's are equivalent to being down ~5 minutes in a year 4 9's is equivalent of being down ~1 hour in a year 3 9's is equivalent of being down ~9 hours in a year 67
51 Tools: ScaleIO sizer 71
52 Bottom line resiliency ScaleIO can achieve reliability and availability that is equal to and better than enterprise level storage systems Trust the tools 72
53 Common Issues
54 Testing for performance The effect of the number of concurrent threads on the IOPs 8KB Read 8KB Write 25, 2, , 8, IOPS 15, 1, IOPS 6, 4, , Total Queue Depth 2, Total Queue Depth 74
55 Summary ScaleIO consumes minimal CPU resources The large IOs are limited by the network ScaleIO scales almost linearly Use Flash/SSD/DRAM to boost HDD Pool RT and IOPs. Do not use caching for SSD Pools 75
56 Summary continued Great Read and Write Response Times Flash drive performance varies, Be weary of wear! ScaleIO can achieve reliability and availability that is equal to and better than enterprise level storage systems. Use the tools. Avoid single threaded performance testing Have fun at the conference! 76
57 NEXT STEPS Join the ECN ScaleIO Product Community Follow Us on VISIT AND where you ll have access to whitepapers, videos, demos etc. DOWNLOAD Free & Frictionless version of ScaleIO Reach out to your local sales team! 77
58 Want More ScaleIO? EMC ScaleIO In The Enterprise: The Citi Experience (storage.28) 3: PM; 8:3 AM ScaleIO: Architecture Deep Dive (storage.29) 4:3 PM; 1: PM ScaleIO: Architecting For Availability, Performance & Networking With ScaleIO (storage.3) 1:3 PM; 1: AM ScaleIO: Simplying OpenStack With ScaleIO Software Defined Storage (storage.32) 8:3 AM ScaleIO & vsan: Software-Defined Storage - The Revolution is Here! (storage.33) 12: PM; 12: PM ScaleIO: Customer Panel: How Is Software Defined Storage Helping My Data Center? (storage.34) 4:3 PM; 3: PM ScaleIO: Software-Defined Storage Lifecycle Management Viewed Through Demos (storage.36) 8:3 AM; 8:3 AM Birds of a Feather ScaleIO: Redefining Software-Defined Storage & Hyper-Convergence 1:3 PM Try our Hands-on-Labs Build A 1-Node ScaleIO Cluster In Minutes! Operations & Lifecycle Management Of Dell EMC ScaleIO Software Defined Storage Use REX-Ray & ScaleIO With Docker, Mesos & Kubernetes (Hands-on Lab) Visit us in Booth! #757 78
59 Want to win a Levitating Death Star Speaker? while at Dell EMC World 2 Winners will be chosen daily from Monday May 8 through Thursday May 11 All winners will be notified through Twitter Direct Message NO PURCHASE NECESSARY. Ends 5/11/217. To enter and for Official Rules, visit 79
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