How Are My VM’s Doing? Managing for Performance

1. How Are My VM’s Doing?Managing for Performance Mike Matchett Dir. Product Management mmatchett@akorri.com

2. Akorri Customers & AwardsAny size enterprise across multiple industries Healthcare, Education, Legal Manufacturing, High Tech, Pharma Financial / Insurance Online Services

3. Virtualization Decouples Apps & Resources Physical Infrastructure Model Virtual Infrastructure Model NETWORK NETWORK Server Pool SAN SAN SAN LAYER Storage Pool Tier 1 Tier 2 Archive

4. Management of IT Virtualization • Good • Sharing resource “Pools” means less dedicated waste • Normalized resource units lowers administrative costs • Explicit "entitlements“ with “unused” available at peaks • Bad • Hard to see deep physical resource sharing by application • Hard to tell if the whole pool is shared efficiently • When contention happens it’s bad for everyone at once • Ugly • Who's 100% is really 100%? • ESX knobs and switches control capacity, not performance

5. AkorriCross-domain Management for Virtual Infrastructure • Agent-less Collection Across Databases, Servers, Storage, VMware & Storage Virtualization • Advanced Analytics & Modeling • Performance and Utilization • Troubleshooting & Root Cause • Optimization and Planning • Rapidly Delivers ROI: • Faster Problem Resolution • Avoid Performance Problems • Planning and Optimization V2.0

6. Akorri BalancePoint’s ModelIncludes Server and Storage Virtualization ServerVirtualization Storage Virtualization

7. Track Down Depend- encies Find “Root Cause” Recognize Problem Interrogate Components Isolate Faults Resolve Problem BalancePoint No Problem Resolve Problem • IRT™ • Performance Index™ • Utilization Analysis • Management Reporting Proactive Analysis X-Domain Analytics Troubleshooting Performance Issues is Difficult in Virtualized Data Centers BalancePoint • Map virtual topology • Identify faults • Identify bottlenecks • Identify contention • Make recommendations Recognize Problem

8. VMware ESX Netapp iSCSI CPU problem Example:Topology

9. Same Example – Storage View

10. KPIs and Metrics - Example Infrastructure Response Time Usage Index IOPS Capacity

11. Understand Resource Contention VMware ESX Server CPU Contention Application Contention for a RAID group

12. Dynamic Thresholds and Prediction • Thresholds can be dynamically set based on historical behavior • Predicts performance for the next 48 hours • Helps to manage seasonality and identify spikes in future activity Identify Problems Before They Happen

13. IT Service Management For Effectiveness (Performance Analysis) - • Load/Throughput - Number of Transactions • Response Time – Time it takes a Transaction to complete And for Efficiency (Capacity Management) - • Utilization – How Busy is the service? • How much of the available service capacity is being used? • How many transactions can it handle at good performance levels?

14. Response Time is Non-Linear • Max Capacity happens when system is 100% utilized • Service Level is set to a performance threshold • Optimal Capacity happens at less than 100% utilization

15. Queuing Theory to The Rescue… • Queuing Models create Response Time curves • Based on established mathematics • Useful analytically (historically) as well as predictively • A simple queuing model can represent a check-out line at the grocery store • Complex Queuing Network Models can represent nested IT domains • Advanced cross-domain solutions model IT virtualization

16. Infrastructure Efficiency - How long to service each transaction? Can be scored for how much of the time good service is provided… But requires a known Service Level Infrastructure Response Time Are we giving good performance? Response Time Performance Service Level

17. Is Infrastructure Over- or Under-Utilized? = 100 Optimal Utilization Optimal Point is based on modeling for performance > 100 OVER Performance is in jeopardy Infrastructure over-utilized < 100 UNDER Performance is stable Infrastructure has headroom Akorri Performance IndexA better 100%... PI > 100 Performance PI = 100 Optimal Point PI = 0

18. Practical Examples with BalancePoint • Operations Management and P2V Planning • Justifying Additional Physical Servers for Virtualized Server Clusters • Trigger/measure IT optimization projects • CIO Investment Planning

19. Scorecard Reporting Key Performance and Utilization Information for ESX and VMs, Physical Servers, Application Service, Storage Usage

20. E.g. VMware ESX Servers Model for PI factors in: Server capability Storage capability Other apps (contention) Easily rolls up to cluster, domain, and datacenter scores Do I Need More ESX Hosts?Can My Current Servers Support More Virtual Machines? No: Over Utilized Performance (Response Time pre Transaction) 100 Yes: More VMs Workload (Transactions per Sec)

21. Example: VMware Status Report Key Performance and Utilization Information for ESX and VMs

22. The Business of IT Trigger and Measure IT Optimization Projects For Example - • If PI is always low (<20%) • Server Consolidation • Storage Tiering • If PI is often high (>120%) • Infrastructure Upgrades • Application Tuning • If PI varies high and low • Load Re-balancing • Server and Storage Virtualization PI over Time

23. CIO Reviews IT KPI’s For Every Application/VM each Quarter… The PI Scale 100+: INDICATES RISK 1000 900 690 570 480 405 325 240 • PI is “non-linear” over 100 • Escalates rapidly with poor performance • High penalty for poor service levels 190 150 125 100 80 0-100: SHOWS HEADROOM 60 • PI is “linear” up to 100 • A score of 100 = “Optimal” • Example: an ESX server with 5 VMs and a PI score of “50” could handle 5 more similar VMs 40 20

24. For Akorri VMware CustomersWhat We Do: • Provide single view of VMware infrastructure • Alert on current and future performance problems, and identifies the source of the problem • Help troubleshoot performance problems through advanced analytics and predictive modeling • Optimize server/storage utilization • Drive IT alignment across virtual infrastructure BalancePoint helps ensure the success of virtualization projects in production environments.

25. Thanks! Mike Matchett Director Product Management Akorri mmatchett@akorri.com http://www.akorri.com Live BalancePoint webex demos every Wed – check website for details…

26. Additional Slides

27. Availability v. Performance • Availability • Relatively easy to monitor and measure inside and out • ROI is limited to minimizing amount of downtime • 100% uptime is the best you can do • Performance • Hard to measure internally, calibrate externally • ROI is theoretically unbounded • Can always try to improve performance another 10%... Improving Availability from 99.99 to 99.999% buys 5 minutes of uptime/yr - (100% * 5 min). Improving Performance by 10% can buy continuing productivity - (+10% * 7*24*365*60 min)

28. Manage Availability or Performance? • Availability • Under-performing systems don’t meet service levels, and are therefore not considered available… • Performance • Un-available systems are just performing very very badly… At a service level the all-or-nothing Availability definition works. However IT must use performance to manage, optimize, and plan.

29. Infrastructure AgilityProve Virtualization Works… • An analysis of variance of infrastructure efficiency over time • Lower variance means higher agility • Resources dedicated to single applications will usually show low agility • Shared resource pools are dynamically assigned to applications demonstrating high agility PI over Time High Variability = Low Agility Agile Datacenters automatically handle large changes in application usage while also optimizing IT investment!

30. How? • BalancePoint discovers and collects performance and utilization data directly from VirtualCenter and also from: • VM OS • ESX Server OS • Database • Server components • Storage systems • Collection is done without any software agents • BalancePoint uses advanced analytical techniques to correlate across the I/O stack: • Queue depth analysis • Infrastructure response time and throughput • Historical / time series analysis • Storage and server capacity utilization analysis and trending

31. BalancePoint VMware Advantages • Multiple points of deep data collection and analysis across domains – DB, VM, CPU, memory, HBA, array • Not simply collecting and presenting VirtualCenter stats • Heterogeneous storage array support and drill down • Other VMware management tools have little/no storage insight • Akorri performance analytics & metrics (IRT, UI, PI) • Not simply reporting raw stats • Rapid installation due to agent-less design • No heavy agent infrastructure BalancePoint shows exactly what is happening across the server and storage infrastructure.

32. What Else? • Akorri is a VMware Technology Alliance partner • BalancePoint is VMotion/DRS “aware” • Identifies when a VM has moved & tracks performance changes • BalancePoint supports all major storage array vendors • EMC, IBM, HP, HDS, Netapp, Dell, Engenio, Dot Hill, etc. • BalancePoint supports all major server OS’s • VMware, Linux, Windows, Solaris, HPUX, AIX, etc. Managing Virtual Infrastructure

33. BalancePoint Produces Results • An internet business avoided purchasing unnecessary storage hardware worth $350K. • A financial firm found a bottleneck in HBA settings that was slowing down millions of dollars worth of storage. • An insurance company realized $271K in year-one ROI • A healthcare company cut troubleshooting time for application performance events in half. • A financial company avoided buying more software that could only manage vendor-specific platforms. • A service provider used BalancePoint to ensure the success of a business-critical VMware project.

34. Automatically maps database to storage infrastructure Oracle instances Oracle schema elements Creates ViewPoint Topology Provides visibility into complex Oracle configurations Improves troubleshooting of Oracle issues, performance and capacity problems Deep Storage Insight for Database Applications Oracle and SQL