Storage and IO in a Virtual World

Transcription

1 Storage and IO in a Virtual World S. Kartik, Ph.D EMC Distinguished Engineer CTO, Central Division, EMC CMG Minneapolis-St. Paul Winter Conference

2 Virtualization: Further Optimizing ILM Information Lifecycle Management Align IT infrastructure with the business based on the changing value of information Data Classification Server virtualization Network virtualization Storage virtualization Servers Network Storage Physical infrastructure Virtualization: Optimizing server, network, and storage resources 2

3 Defining Virtualization Virtual Memory Each application sees its own logical memory, independent of the physical memory Any abstraction that optimizes resources and improves flexibility Virtual Networks Each application sees its own logical network, independent of the physical network Virtual Servers Each application sees its own logical server, independent of the physical servers Virtual Storage Each application sees its own logical storage, independent of the physical disks 3

4 What is Storage Virtualization? Enabling technology that separates storage presented to an application from the underlying hardware Presents a logical view of physical storage media Block storage from multiple systems appears in a common, logical pool 4

5 What Makes Virtualization Interesting? Potential Benefits: Higher rates of usage Simplified management Platform independence More flexibility Lower total cost of ownership Better availability Server Application functions Network Data-access functions Storage Datapreservation functions 5

6 Usage Scenarios for Block-level Storage Virtualization Next-Generation Data Center Operations Heterogeneous Storage Consolidation Storage Utilization Extending Volumes Online Application Growth Business Continuity Nondisruptive Data Mobility Scalability 6

7 The path to virtualization Appliance and Controller Virtualization In-band Network Virtualization Split-path V-engine State dependent cache Increased I/O latency Limited fabric ports Limited performance No state/no cache ensure data integrity I/O at wire speed Full-fabric bandwidth Scalable performance 7

8 SAN Storage Virtualization Architectures In-band Split-Path (Out-of-Band) Concerns with: Data integrity Performance Management SAN No Concerns with: Data integrity Performance Management Intelligent SAN Control Two Step Process 1 10 msec TagmaStore One Step Process < 0.1 msec 1 10 msec 1 10 msec EMC IBM HDS/HP EMC IBM HDS/HP 8

9 Stateful vs. Stateless Virtualization Architectures State is a unique configuration of information in a program or machine. Source: Wikipedia.org, June 2007 Stateful virtualization architectures Contain data within cache Written by the application Stateless architectures Do not employ cache Maintain a consistent image between the application and attached storage arrays Inconsistent image Stateful Architecture Cache Virtual Volume Physical Volume Physical storage Consistent image Stateless Architecture Virtual Volume Cache-less Physical Volume Physical storage 9

10 Cache based in-band architecture All I/O must go through the virtualization engine All writes terminate in the cache Large arrays have large caches EMC, HDS, IBM 256GB In-band engines typically have same or less Appliance-based - 8 GB/2-nodes Array based 256 GB total 70% write On the bright side Poorly performing arrays will get a boost! Low functionality arrays become smarter On the not-so-bright side Limited cache becomes a bottleneck for more powerful arrays Latency and throughput implications Response time for high-end arrays is affected IOPS and MB/s usually throttled Scalability limitations 10

11 Stateless out-of-band architecture V- engine Most I/Os do not go through the virtualization engine Control frames and error handling is done by the virtualization engine All writes terminate in the virtualized array Intelligent SAN technology Port count is not limited by V-engine On the bright side High end arrays behave as unvirtualized High-end array functionality is preserved No perceptible latency and throughput implications Allows much greater scalability for virtualized arrays Will impart functionality to array s that have none On the not-so-bright side Will not make slow storage fast 11

12 SPC-1 Results High-end arrays Public Results: on SPC-1 Website Will Benchmarks save us and tell us what we need to know? SPC-1 is a backend intensive workload it counts the # of drives in the configuration [See: where I blog about this. 12

13 Recent SPC-1 Results Mid-range and high-end Most results later than SPC-1 v1.9 Lines to guide eyes 13

14 What are the performance metrics that matter? Latency 5 kinds of IO RRM Needs a backend IO RRH Expects to find the IO in cache RW Should be a cache hit, unless SR Expects pre-fetch to kick in SW Ability to destage before write ceilings are hit Cached architectures help poorly performing storage and hurt highperformance storage Base latency just going through in-band cache for RRM RRH can get flushed out too soon due to limited cache SR pre-fetch algorithms need to lick in quickly and be sensed by backend arrays SW de-stage is slower than native Uncached architectures do not affect latency noticeably They don t boost performance And don t hurt it either Overall, cached architectures limit scalability and be ready for latency issues Generally not seen in performance sensitive environments 14

15 Layout & Tuning in Virtualized Storage If you choose to virtualize Proceed with caution It is easy to treat all volumes as equal as they appear to be One cannot ignore backend layout considerations! Indexes and tables on the same spindles? Not a good idea Resist the temptation To mix volumes of differing performance characteristics Stripe across arrays Concatenate volumes across arrays Virtualization does let one fix issues somewhat easily Can move troubled volumes to a different location Can move volumes or applications between arrays Tuning can be done on the fly without outages but There will be a performance hit while the movement is going on 15

16 Local and Remote Replication Cache based architectures IO terminates from host perspective in the cache Which means The storage has a fuzzy picture of reality Only the virtualization engine knows truth All advanced functionality MUST happen at the virtualization engine level All array functionality is unavailable (unless un-cached!) Virtualization engine has to manage copy, mobility and remote replication functions in addition to normal IO Have to account for performance impact, cache use, etc Un-cached architectures Array terminates the IO from host Array functionality can be used for local and remote replication Mobility jobs will likely use virtualization engine But PPRC, SRDF, FlashCopy, TrueCopy, ShadowImage, Timefinder can be used when appropriate 16

17 Performance Management: Operational issues Performance The Good Management: Operational Considerations One single pane of glass Full data mobility live The Bad Abstraction comes with obfuscation Need to track the IO through many virtual layers SRM tools are growing up to provide an end-to-end view but not there yet Good instrumentation and process is needed Still need some expertise in element managers and native performance tools for virtualized arrays The Ugly Finger-pointing between vendors Support issues Change management 17

18 Summary & Conclusions Virtualization holds much promise for simplification of storage management and increasing uptime Two core architectures In-band or cache-based Out-of-band or split-path/stateless Cache helps low performance arrays But limits high-end arrays and scalability Adds latency to IO Path Out-of-band is more scalable Preserves functionality and performance of arrays Will not boost poor performance Careful with data layout Many operational implications to be considered to be successful 18

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