Performance Management In The VMware World

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www.sysload.com 1 CMG – October 16, 2008 Performance Management In The VMware World Virtualized environments technology, benefits and reality VMware Host and guest based performance management “Don’t forget the guests !”. Why ?What? How ? Sysload positioning

Transcript of Performance Management In The VMware World

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CMG – October 16, 2008

Performance Management In The VMware World

Virtualized environments technology, benefits and reality

VMware Host and guest based performance management

“Don’t forget the guests !”. Why ?What? How ?

Sysload positioning

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Virtualized Environment

Two technologies : Containers & PartitioningReality behind virtualization benefits

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Two technologies : Containers & Partitioning

Containers technologiesSun Solaris 10 Parallels Virtuozzo

The Operating System is sliced…

HARDWARE

Operating System

Zone 1 Zone 2 …Zone 3

Solaris zones,

containers

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Micropartitioning technologiesIBM AIX LPAR/WPAR,I5/OSMS Hyper-VSolaris LDOMXen based (Citrix, Sun xVM, OracleVM)Virtual IronVMware

Hypervisor is added…

HARDWARE

Hypervisor

OS 1 OS 2 …OS 3VMs,

LPARs

Two technologies : Containers & Partitioning

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Reality behind virtualization benefitsPromises and benefits of virtualization

Administration

• Deployment / Maintenance

• Disaster recovery

• Asset management, provisioning

Technology

• Optimized for New technologies : Multi-core / thread

Economic

• A/C, Power Supply

• Room space

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Reality behind virtualization benefitsBack to reality… Forgotten constraints reemerge with

virtualization

Loss of traditional model: “1 server = 1 application”Physical machines sliced in Virtual Machine

-> add concurrent phenomenaIncrease of saturation risksEnvironment more dynamic, complex, sensitiveStrategic stake : resources utilization rate have to increaseOptimization constraints = Mainframe

… and Service level needs to stay high

Performance Management has never been so CRITICAL

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VMWare Performance Management ?

“… Host Based ?“

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Host Performance Analysis

Validate the theory VMware architecture… Resources expected, VMs and Services loads … Automatic resources mechanism : DRS ,…

Help for ESX administrationVMware Customization : sizing, …Management of VMware mechanism : shared pools, dynamic reallocation,…

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Host Performance AnalysisGlobal picture :

“Asset management”Number of VMs defined vs unused !Global Impact: CPU, MEM, …Load balancing: cross-guest Operating Systems

Performance of the host is the performance of VMware “Kernel”

ONLY.

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VMWare Performance Management ?

“Do not forget the guests.”

“ … Guest Based ?“

WHY ?

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Pool of resources

0% 20% 40% 60% 80% 100%

I/O

CPU

Memory

Dynamic re-allocation: Vmotion, (secs)

Move from a static to an unpredictable world

Hypervisor

CPU

Memory

I/O

CPU

Memory

I/O

CPU

Memory

I/O

Virtual machines

VM1 VM2 VM3 VM4 VM5

OR

VMware Distributed Resource Scheduler

(DRS)

Standalone Resource Pool

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Move from a static to an unpredictable world

Random saturation phenomena Random saturation phenomena

at the GUEST levelat the GUEST level

DRSHow is the decision made to switch ?

Are peaks taken into account in this decision?

-> Automatic resource re-allocation is based on average.

Host Resource PoolExpandable reservation

Shares : CPU pool, Balloon Driver, Swap I/O

-> Resources on one ESX are shared by the VMs. Available resources change dynamically.

Unsynchronized VMsEach Guest-Os has its own behavior running

Different applications and OSs.

-> Resource needs within or between VMs can occur at any time simultaneously.

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“Comfort loss” : less headroom

Optimization of each VM allocated resource

Less headroom

Peaks can happen at the same time

More random saturation peaks

Increase of saturation length

100%

Headroom

Average 40%

100% Headroo

m

100%

Headroom

Average 30%

Average 70%

200%

160%

180%

server 1

server 2

Server 1 + server 2

Average 90%

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Workload monitoring

Troubleshooting & AuditWhich applications or processes are impacted by a saturation on an individual guest, or host?What is the source of a saturation ?

Performance & CapacityBehavior of Workloads : Production cycle,…Make decision on VM optimization : resource usage,…

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“Don’t forget the guests !”. Why ?

Environment is less deterministic, micro phenomena add up and saturation can occur at anytime.

Headroom is minimized, impact on users is longer.

Applications are living in VMs.

“Guest view is the End-user View”

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VMWare Performance Management ?

“Do not forget the guests.”

WHAT to manage ?

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At the Guests !

All Operating Systems that run under VMsSpecificity of each OS : Linux, Solaris, Windows, NetwareHomogeneous level of information

Correlation between VMs and ESX

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Workload : Processes and Group of processes

Behavior of workloads

Impact of workloadOn the VMOn one Physical MachineCross Physical Machines

Physical Machines

VMs

Workloads

Users

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Performance, Capacity, Utilization

Server saturation/utilizationProcessor subsystemMemory subsystemDisk subsystemNetwork subsystem

Real-time & historical dataMonitoringTroubleshooting Capacity Management, trending

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VMware Performance Management ?

“Do not forget the guests.”

How to manage ?

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Granularity & metricsGranularity down to 5 seconds

Mixing metrics for alerts, diagnostics, trending

1 min. time frame

CPU (counter)

1 min. time frame

CPU 1min. = average Nb thread1min. = “picture”

# waiting thread in queue (state)

Example : %CPU & # Waiting Threads = Saturation

Granularity 5 seconds

Sat =Yes

During 30s !

Granularity 1 Minute

Sat =No !!

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Lost in translation - Resources seen from the Guest

From Guests perspective

From ESX perspective

VM1

Hypervisor

0 6

0 6

No Adjustment : VM1-Cpu = ∑ VM1-CPU /6

Time keeping aware : VM1-Cpu = ∑ VM1-CPU /3

VM 2 VM 3 VM 2VM 1 CPU 1CPU 1CPU 1VM 1VM 1

VM 1 VM 1 VM 1

VM1-Cpu = ∑ VM1-CPU /3

CPU sequence

Right !

Right !

Wrong!

CPU given by the OS is WRONG!

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Lost in translation - Time keeping focused analysis

GuestOs have no idea it is virtualized ! -> Time is not managed accurately due to virtualization*All time-related metrics are impacted

-> Measurements have to be adjusted (corrected) by the monitoring tool

* sources : VMware white paper (08-12-2008)

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Maximum flexibility for fast diagnosticsData collection

Several sources of information covering the entire Server

• ESX

• VMs

• Workloads

• Processes

Real time dataHistorical data

Data analysisCentral consoleCorrelation between data sources (interactive console)Statistics capabilityFlexible graphic representation

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Agent based data collection

Agent to monitor each Guest-OSGranularityProcessesTimeKeeping

Agent to monitor each ESX

Because of proliferation of VMs, keeping a very light footprint on the Guest-OSs is KEY !

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Sysload Positioning

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Real-time Sever Performance and Capacity Management

Software Provider since 1998Headquarters: Paris and BostonSubsidiary in UKOver 400 Customers and 70,000 Licensed Servers

• Major Enterprises (100+ servers)

• Managed Services Providers

• Key Customers since 2000

Profitable Company since 2004Investor: AXA Private Equity

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Unique Technology / ArchitectureDesigned to address large enterprise requirements

Scalability-Parallel data collection

Distributed / Client –Server

Low bandwidth between the distributed servers and the console

Integration with third-party products to leverage existing investments

No additional hardware and software required

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Sysload for VMware VITwo analysis levels

ESX Agents: ESX Server 2.X and 3.xGuest OS agents : Windows, Linux, Solaris, Netware

Agent characteristics250 metrics / advanced metricsTime Keeping awareDown to 1 sec. real-time granularityBoolean conditions between metrics (real-time)Historical Analysis (5 minutes granularity)Local history databaseWorkload / Application Tracking Low overhead on Guest-OS and ESX server (< 1% CPU)

ConsoleUnified view cross guests and ESX agentsReal Time and Historical ReportingEasy to use, trouble shooting features

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When implementing performance management technologies designed to support virtualization platforms such as those from VMware, etc.,  IT

organizations should look for solutions that provide the requisite granularity of detail while also

minimizing the resource impact - especially as virtual machine densities increase.

Cameron Haight, Gartner, Inc.

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