Deploying ssd in the data center 2014
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This document discusses various options for deploying solid state drives (SSDs) in the data center to address storage performance issues. It describes all-flash arrays that use only SSDs, hybrid arrays that combine SSDs and hard disk drives, and server-side flash caching. Key points covered include the performance benefits of SSDs over HDDs, different types of SSDs, form factors, deployment architectures like all-flash arrays from vendors, hybrid arrays, server-side caching software, virtual storage appliances, and hyperconverged infrastructure systems. Choosing the best solution depends on factors like performance needs, capacity, data services required, and budget.
Deploying ssd in the data center 2014
- 1. Deploying SSD in the data center Or How this Flash Makes Storage Like This Flash
- 2. Today’s Agenda • The storage performance problem • Flash to the rescue – A brief flash memory primer – Flash/SSD types and form factors • The All Flash Arrays (AFA) • Hybrid arrays • Server side flash • Converged architectures • Choosing a solution
- 3. The IO Gap • Processor speed doubles every 2-3 years • Disks have been stuck at 15K RPM since 2000
- 4. “The I/O Blender” Strains Storage • Virtualization throws I/O into a blender… all I/O is now random I/O! • 10 VMs doing sequential I/O to the same datastore=random I/O • Disk drives are good at sequential, less good at random
- 5. Data Access Performance • L1 processor cache ~1ns • L2 processor cache ~4ns • Main memory ~100ns • PCIe SSD read 16-60μs (16,000-60,00ns) • SAS/SATA SSD read 50-200μs (50,000- 200,000ns) • Disk read 4-50ms (4-50,000,000ns) Moral of the story: keep IOPS away from the disk
- 6. Traditional Performance Solutions • Head per track disk drives, DRAM SSDs – Huge price premium limits use to the very few • Wide Striping – A 15K RPM disk delivers 200 IOPS – For 10,000 IOPS spread load across 50 drives • Of course that’s 15PB of capacity – Short stroking • Use just outside tracks to cut latency • Wasting capacity wastes $ and OpEx (power, maint)
- 7. What Is Flash Memory? • Solid State, Non-volatile memory – Stored charge device – Not as fast as DRAM but retains • Read/Write blocks but must erase 256KB-1MB pages – Erase takes 2ms or more – Erase wears out cells • Writes always slower than reads
- 8. The Three, and a half, Types of Flash • Single Level Cell (SLC) (1bit/cell) – Fastest – 100,000 program/erase cycle lifetime • Multi Level Cell (MLC) (2 bits/cell) – Slower – 10,000 program/erase cycle lifetime • eMLC or HET MLC (2 bits/cell) – Slightly slower writes – 30,000 cycles • Triple Level Cell (TLC) (3 bits/cell) – Not ready for data center use – Phones, tablets, maybe laptops
- 9. Flash’s Future • Today’s state of the art flash 1x nm cells (17- 19nm) • Most shipping SSDs still 24nm • Smaller cells are denser, cheaper, crappier • Samsung now shipping 3d – Because they couldn’t get Hi-k to work • Other foundries have 1-2 more shrinks • Other technologies post 2020 – PCM, Memristors, Spin Torque, Etc.
- 10. Anatomy of an SSD • Flash Controller – Provides external interface • SATA • SAS • PCIe – Wear leveling – Error correction • DRAM – Write buffer – Metadata • Ultra or other capacitor – Power failure DRAM dump – Enterprise SSDs only
- 11. Flash/SSD Form Factors • SATA 2.5” – The standard for laptops, good for servers • SAS 2.5” – Dual ports for dual controller arrays • PCIe – Lower latency, higher bandwidth – Blades require special form factors • SATA Express – 2.5” PCIe frequently with NVMe
- 12. SSDs use Flash but Flash≠SSD • Fusion-IO cards – Atomic Writes • Send multiple writes (eg: parts of a database transaction) – Key-Value Store • NVMe – PCIe but with more, deeper queues • Memory Channel Flash (SanDisk UltraDIMM) – Block storage or direct memory – Write latency as low as 3µsec – Requires BIOS support – Pricey
- 13. Selecting SSDs • Trust your OEM’s qualification – They really do test • Most applications won’t need 100K IOPS • Endurance ≠ reliability – SSDs more reliable than HDDs • 2 million hr MTBF • 10^17 BER vs 10^15 for near line HDD – Wear out is predictable – Consider treating SSDs as consumables – However don’t use read optimized drive in write heavy environment
- 14. SanDisk’s Enterprise SATA SSDs Name Sizes IOPS r/w Endurance Application Eco 240, 480, 960 80K/15K 1 DWPD, 3yr Read intensive Ascend 240, 480, 960 75K/14K 1 DWPD, 3yr Read intensive Ultra 200, 400, 800 75K/25K 3 DWPD, 5yr General purpose Extreme 100, 200, 400, 800 75K/25K 10 DWPD, 5yr Write intensive DWPD = Drive Writes Per Day
- 15. Flash for Acceleration • There are 31 flavors of flash usage • What’s best for you depends on your: – Application mix – IOPS demand – Tolerance of variable performance – Pocketbook – Organizational politics
- 16. Basic Deployment Models • SSDs in server as disk • All solid state array • Hybrid arrays – Sub LUN tiering – Caching • Server side caching • Others
- 17. • Minimizes latency and maximizes bandwidth – No SAN latency/congestion – Dedicated controller • But servers are unreliable – Data on server SSD is captive – Good where applications are resilient – Web 2.0 – SQL Server Always On – Software cross-server mirroring Flash in the Server
- 18. All Flash Array Vendors Want You to Think of This
- 19. But Some Are This
- 20. Or Worse This
- 21. What You Really Want
- 22. Rackmount SSDs • Our drag racers – They go fast but that’s all they do • The first generation of solid state • Not arrays because: – Single Controller – Limited to no data services – IBM’s Texas Memory – Astute Networks – Historically Violin Memory though that’s changing
- 23. The Hot Rods • Legacy architectures with SSD replacing HDD – NetApp EF550 – EMC VNX – Equallogic PS6110s – Many 2nd and 3rd tier vendor’s AFAs • Limited performance • 50-300,000 IOPS • Full set of data management features • Wrong architecture/data layout for flash
- 24. All Solid State Arrays • Minimum dual controllers w/failover • Even better scale-out • Higher performance (1 megaIOP or better) • Better scalability (100s of TB) • Most have partial data management features – Snapshots, replication, thin provisioning, REST, Etc. • May include data deduplication, compression – Lower cost w/minimal impact on performance
- 25. Legacy Vendors All Flash Array • 3Par and Compellent’s data layout better for flash – Easier tiering, less write amplification • Dell - Compellent – Mixed flash • SLC write cache/buffer, MLC main storage – Traditional dual controller • HP 3Par Storeserv 7450 – 220TB (Raw) – 2-4 controllers
- 26. Pure Storage • Dual Controllers w/SAS shelves • SLC write cache in shelf • 2.75-35TB raw capacity • Always on compress and dedupe • FC, iSCSI or FCoE • Snapshots now, replication soon • Good support, upgrade policies • Graduated from startup to upstart • Promising scale-out
- 27. SolidFire • Scale out architecture – 5 node starter 174TB (raw) 375K IOPS – Scale to 100 nodes • Always on dedupe, compression • Content addressed SSDs • Leading storage QoS • Moving from cloud providers to enterprise • iSCSI, FC via bridge nodes
- 28. Cisco/Whiptail • Cisco bought AFA startup Whiptail, put with UCS • Storage router based scale out • Up to 24TB raw node, 10 nodes • FC, iSCSI • Dedupe, compression Storage Appliance Storage Router Storage Router Storage Appliance HP ProLiant DL380 G6 FANS PROC 1 PROC 2 POWER SUPPLY 2 POWER SUPPLY 1 OVER TEMP POWER CAP 1 2 3 4 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 ONLINE SPARE MIRROR UID 2 1 4 3 6 5 8 7 6 5 4 3 2 1 HP ProLiant DL380 G6 FANS PROC 1 PROC 2 POWER SUPPLY 2 POWER SUPPLY 1 OVER TEMP POWER CAP 1 2 3 4 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 ONLINE SPARE MIRROR UID 2 1 4 3 6 5 8 7 6 5 4 3 2 1 HP ProLiant DL380 G6 FANS PROC 1 PROC 2 POWER SUPPLY 2 POWER SUPPLY 1 OVER TEMP POWER CAP 1 2 3 4 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 ONLINE SPARE MIRROR UID 2 1 4 3 6 5 8 7 6 5 4 3 2 1 Storage Appliance Storage Appliance Workloads
- 29. EMC XtremIO • Scale-out Fibre Channel • X-Brick is 2 x86 servers w/SSDs • Scales to 8 X-Bricks • Infiniband RDMA interconnect • Shared memory requires UPS • Full time dedupe, CAS • 10-80TB raw
- 31. Hybrid Arrays • Combine flash and spinning disk in one system – Usually 7200RPM • Legacy designs with SSDs added • Next-Gen Hybrids – Tegile – Nimble – Fusion-IO/IO control – Tintri • High performance – 20,000 IOPS or more from 3-4u – 10% flash usually provides 2-4x performance boost • May include deduplication, compression, virtualization features
- 32. Sub-LUN Tiering • Moves “hot” data from slow to fast storage • Only 1 copy of data • Must collect access frequency metadata • Usually on legacy arrays • Ask about granularity, frequency – Up to 1GB, once a day • Can give unpredictable performance
- 33. Flash Caching • Data copied to flash on read and/or write • Real time • Write around – Reads cached • Write-through cache – All writes to disk and flash synchronously – Acknowledgment from disk • Write back cache – Write to flash, spool to disk asynchronously
- 34. Server Flash Caching Advantages • Take advantage of lower latency – Especially w/PCIe flash card/SSD • Data written to back end array – So not captive in failure scenario • Works with any array – Or DAS for that matter • Allows focused use of flash – Put your dollars just where needed – Match SSD performance to application – Politics: Server team not storage team solution
- 35. Caching Boosts Performance! 0 500 1000 1500 2000 2500 3000 3500 Baseline PCIe SSD Cache Low end SSD Cache Published TPC-C results
- 36. Write Through and Write Back 0 10000 20000 30000 40000 50000 60000 Baseline Write Through Write Back TPC-C IOPS • 100 GB cache • Dataset 330GB grows to 450GB over 3 hour test
- 37. Server Side Caching Software • Over 20 products on the market • Some best for physical servers – Windows or Linux • Others for hypervisors – Live migration/vMotion a problem • Most provide write through cache – No unique data in server – Only accelerates • Duplicated, distributed cache provides write back
- 38. Live Migration Issues • Does cache allow migration – Through standard workflow • To allow automation like DRS? • Is cache cold after migration? • Cache coherency issues • Guest cache – Cache LUN locks VM to server • Can automate but breaks workflow • Hypervisor cache – Must prepare, warm cache at destination
- 39. Distributed Cache • Duplicate cached writes across n servers • Eliminates imprisoned data • Allows cache for servers w/o SSD • RDMA based solutions – PernixData – Dell Fluid Cache • Qlogic caching HBA acts as target & initiator
- 40. Virtual Storage Appliances • Storage array software in a VM • iSCSI or NFS back to host(s) • Caching in software or RAID controller • Players: VMware StoreMagic HP/Lefthand Nexenta
- 41. Hyperconvirged Infrastructure • Use server CPU and drive slots for storage • Software pools SSD & HDD across multiple servers • Data protection via n-way replication • Can be sold as hardware or software – Software defined/driven
- 42. Hyper-convirged Systems • Nutanix – Derived from Google File System – 4 nodes/block – Multi-hypervisor – Storage for cluster only • Simplivity – Dedupe and backup to the cloud – Storage available to other servers – 2u Servers • Both have compute and storage heavy models
- 43. Software Defined Storage • VMware’s VSAN – Scales from 4-32 nodes – 1 SSD, 1 HDD required per node • Maxta Storage Platform – Data optimization (compress, dedupe) – Metadata based snapshots • EMC ScaleIO – Scales to 100s of nodes – Hypervisor agnostic
- 44. All Flash Array? • If you need: – More than 75,000 IOPS – For one or more high ROI applications • Expect to pay $4-7 GB • Even with dedupe • Think about data services – Snapshots, replication, Etc.
- 45. Hybrids • Hybrids fit most users – High performance to flash – Low performance from disk – All automatic • Look for flash-first architectures – Usually but not always from newer vendors • Ask about granularity and frequency for tiering • Again data services – Snaps on HDD – Per-VM services
- 46. I’ll give up Fibre Channel, When you pry it from my cold dead hands
- 47. Server Side Caching • Decouples performance from capacity • Strategic use – Pernix data write back cache w/low cost array • Tactical solition – Offload existing array – Boost performance with minimal Opex
- 48. Questions and Contact • Contact info: – [email protected] – @DeepStoragenet on Twitter
Editor's Notes
- #19: Lamborghini Gallardo 0-60 3.8 Top Speed 202
- #22: M5 0-60 3.7 Top Speed 205
- #33: Like driving by looking in rear view mirrorEMC FAST VP algorithm: Each IO to slice adds to counter. Ios age out so after 24 hrs it’s worth .5 and after 7 days almost 0. Once an hour data is analyzed and slices sorted by “heat”. Data moved during allowed movement times (no more frequewntly than once/hr leaving 10% of fastest pool free for future promotions and new allocations to high proirity LUNS in pool. Schedule set for start time (IE 22:00 all 7 days), duration, UI shows estimated migration time. Uiser can select rate from high, med, low.
- #36: SQL Server/FlashSoft http://www.sandisk.com/assets/docs/SQL_Server_Performance_Enhancement.pdf
- #37: Note: Flashsoft data w/Virident SSD Baseline 15 15K RPM SAS disks RAID 0