Squeezing Top Performance From Your Virtualized SQL Server

Transcription

1 queezing op Performance From Your Virtualized QL erver Omaha QL erver Users Group bout Heraflux echnologies Consulting services focused around mission-critical data reas of Focus: Health and tability Performance Optimization Virtualization and Cloud Enablement Infrastructure rchitecture Risk ssessments High vailability Disaster Recovery Capacity Management raining and Education 2 1

2 bout David davidklee.net gplus.to/kleegeek linked.com/a/davidaklee pecialties / Focus reas / Passions: Performance uning & roubleshooting Virtualization Cloud Enablement Infrastructure rchitecture High vailability Disaster Recovery Health Monitoring Capacity Management virtualization.sqlpass.org hadrvc.sqlpass.org 3 genda What does Virtualization Mean for DBs? Environmental Design & Performance Impact QL erver Virtual Machine Construction Real World uned versus Non-uned Performance 4 2

3 Virtualization What Is It? Why hould DBs Care? 5 What is Virtualization? Most DB s virtualization experience dded layer removes hardware dependency from the O and above Hardware treated as physical resource queues Not just P2Ving a single server ransparent to performance Expect at least equivalent raw performance (when done right) 6 3

4 Hypervisor Options (Q1 2014) ware vphere 5.5 Microsoft Hyper-V 2012 R2 7 Environment Underneath Your Data 8 4

5 Physical Environment Model Local Disks (O, Instance Home) QL erver QL erver B QL erver C 9 Virtualization (Private Cloud) Model VIRULIZION 10 5

6 Logical Environment Model 16 vcpu 128 GB vrm 8 vcpu 64 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 150 GHz CPU 4 B Memory V I R U L I Z I O N 4x10GbE Network 20 B ier 1 torage 40 B ier 2 torage 11 Performance Benchmarks and Baselines he demonstration of performance is largely subjective Until youmake it objectivethrough benchmark metrics Must benchmark (and then create baseline): Each component underneath O QL erver Instance itself Long running tasks / jobs / queries ools for benchmark statistics collection 12 6

7 Configuration op to Bottom Performance 13 Host - Physical erver Fastest CPU cores vs. higher core count Maximize host memory capacity But ensure maximum memory performance (i.e. Management ips Plan for no memory overcommitment Plan for no more than 80% memory resource consumption Hot-fail hosts available or reserve failover cluster resources 14 7

8 (hared) torage Configuration ypes of storage Local torage (not recommended) Fibre Channel IP-Based (MB, ici, NF) iered / hybrid ingle points of failure RID ypes & Controller cache ware: PVCI Performance Can go 1 LUN -> 1 datastore -> 1 virtual disk if needed Benchmark all your storage Microsoft QLIO ( IOMeter( QLIO Batch ( Metrics to collect: hroughput (MB/s) I/OsPer econd (IOps) Latency (ms) ggregate Performance 10 QL 5,000 IOPs steady state Each can burst to 10,000 IOPs Now virtualize them all Can one host perform up to 100,000 IOPs? Performance problem = Negative business impact 16 8

9 One Lane Highways vs. Interstate torage performance bottleneck potential Get fastest possible! Get most possible! Multi-pathing configuration & software Vendor-recommended HB queue depth settings Verify and test end-to-end performance 17 Network Performance est Verify network end-to-end performance Use iperf to test network throughput bit.ly/1edcybi How-o Guide: tinyurl.com/ost9gll 18 9

10 Networking Performance ip Colocatetwo s on the same host to increase virtual network performance 19 Construction Performance-Oriented From Day One 20 10

11 Virtual Machine Configuration Correct vcpu vnum configuration ware - Full memory reservation Hyper-V - Dynamic Memory CPU & RM O-level hot-add disables vnum Use virtual disks whenever possible Right-ized virtual machine resources 21 Right-izing the Virtual Machine Right amount of vcpu and vrm resources Physical world = ize for end of life Virtual world = ize for rightnow Idle vcpus will slow application s performance nalyze performance baselines and determine the resources you need Repeat right-sizing analysis routinely More depth: tinyurl.com/n42avu4 How to right-size? Understand CPU scheduling

12 CPU cheduling 16 vcpu 128 GB vrm 8 vcpu 64 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm 2 vcpu 16 GB vrm V I R U L I Z I O N (wo sockets, eight cores, no H) CPU Ready to Run cheduling Queue 23 ware vcpu Ready ime vcpu Ready ime = Delay between vcpu task queue entry and execution of the task on a pcpu Performance impact of high vcpu Ready ime at: tinyurl.com/ kleecpuovercommit 24 12

13 Hyper-V CPU Wait ime Equivalent to ware vcpu Ready ime Hyper-V 2012 and above Perfmon counter: Hyper-V Hypervisor\Virtual Processor\CPU Wait ime Per Dispatch Jonathan ehayias writeup: tinyurl.com/cpureadyhyperv 25 Configuration - Disks Disk Layout (Worst Case) C: -Operating ystem D: -QL erver Instance Home E: -ystem Databases (master, model, msdb) * F: -User Database Data (1 of X) G: -User Database Log (1 of Y) H: -empdb Y: -Windows Page file ** Z: -Backups 26 13

14 Windows erver O et power settings to High Performance (CPU-Z) et antivirus exclusions for QL erver (tinyurl.com/sqlav) Ongoing O-level performance metric collection No greater than five minute interval 24 x 7, not just as-needed Windows Perfmon, Microsoft COM, or any other third-party utility tinyurl.com/kleeperfmon 27 Instance-Level Configuration et Max and Min erver Memory Enable Lock Pages in Memory Enable Instant File Initialization Parallelizable workloads et MaxDOP= vnumnode core count Cost threshold for parallelism = Not default Large Pages (understand pros and cons) 28 14

15 Benchmarks Demonstrate Raw Performance 29 Instance Benchmark Utility - DVDtore Open source database server benchmarking tool ingle number output for relative instance-level performance comparisons Orders placed per test vailable from linux.dell.com/dvdstore How-to at tinyurl.com/kleedvdstore 30 15

16 Performance Putting it ll ogether: uned vs. Non-uned s 31 DVDtore Performance Comparisons 2 vocketx 3 vcpu Core (plus vnum extended) 32GB vrm uned Multiple virtual disks with PVCI 50GB DVDtore database ll best practices applied 128 worker threads (2 tests x 64 t) pproximately 52% CPU utilized 774,925 combined orders placed in 60 min Not uned 6 vocketx 1 vcore(default) 32 GB vrm One large virtual disk Click-through QL erver install pproximately 41% CPU utilized 538,164 combined orders placed in 60 minutes 31% slower than tuned 32 16

17 Conclusions Understand your QL erver workloads Individual ggregate Validate target virtualization environment performance Right-size your s Use benchmarks to demonstrate equivalent & ongoing performance Routinely check ongoing performance 33 davidklee.net gplus.to/kleegeek linked.com/a/davidaklee 34 17

18 ny Questions? 18