© 2009 vmware inc. all rights reserved vsphere performance best practices rob moran premier...
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© 2009 VMware Inc. All rights reserved
vSphere Performance Best Practices
Rob Moran
Premier Services Engineer – VMware Global Support Services – Cork, Ireland
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Global Support Services and Customer Advocacy
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Customer Support Day Events
Coming to a location near you: sharing of VMware best practices!
• Support Days are a collaboration between VMware Support, Sales and customers – you learn directly from the experts
• Topics are driven by customer input, and typically include:
• Best practices
• Tips/tricks
• Top issues
• Product roadmaps/demos
• Certification offerings
http://www.vmware.com/go/supportdays
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Overview
What a performance problem sounds like:
• “My VM is running slow and I don’t know what to do!”
• “I tried adding more memory and CPUs but the problem got worse!”`
• “My VM is slow on one host but fast on another!”
What to look for? Where to start?
We will explore some of the most common performance-related issues that our support centers receive cases for
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A word about performance….
Troubleshooting methodology must define:
• How to find root cause
• How to fix the problem
Must answer these questions:
1. How do we know when we are done?
2. Where do we start looking for problems?
3. How do we know what to look for to identify a problem?
4. How do we find the root-cause of a problem we have identified?
5. What do we change to fix the root-cause?
6. Where do we look next if no problem is found?
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Agenda
Benchmarking & Tools
Best Practices and Troubleshooting
The 4 “food groups”
• Memory
• CPU
• Storage
• Network
© 2009 VMware Inc. All rights reserved
BENCHMARKING & TOOLS
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Benchmarking
Consistent and reproducible results
Important to have base level of acceptable performance
• Expectation vs. Acceptable
Determine baseline of performance prior to deployment
• Benchmark on a physical system if applicable
Avoid subjective metrics, stay quantitative
• “The system seems slower”
• “This worked better last year”
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Benchmarking
Benchmarking should be done at the application layer
• Use application-specific benchmarking tools and load generators
• Check with the application vendor
Isolate variables, benchmark optimum situation before introducing load
Understand dependencies
• Human interaction
• Other “food groups”
• Compare apples-to-apples
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Aggregates thousands of metrics into Workload, Capacity, Health scores
Self-learns “normal” conditions using patented analytics
Smart alerts of impending performance and capacity degradation
Identifies potential performance problems before they start
Slide 10
Tools – vCenter Operations
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Tools – vCenter OperationsSlide 11
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Tools – esxtop
Valuable tool built in to vSphere hosts
View or capture real-time data
• View or playback data later
• Import data in 3rd party tools
vSphere Client performance graphs get their data from the kernel and VSI
• Presentation/unit may be different (e.g. %RDY)
© 2009 VMware Inc. All rights reserved
MEMORY
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Memory – Overhead
A VM’s RAM is not necessarily machine RAM
• vRAM + overhead = maximum machine RAM
Source: vSphere 5.1 Resource Management Guide• Note: These are estimated values
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Memory – Transparent Page Sharing
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Memory – Host Memory Management
Occurs when memory is under contention
Ballooning
Compression
Swapping
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Memory – Ballooning
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Memory – Compression
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Memory – Swapping
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Memory – Swapping
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Memory – VM Resource Allocation
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Memory – Resource Pool Allocation
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Memory – Ballooning vs. Swapping
Ballooning is better than swapping
Guest can surrender unused/free pages
Guest chooses what to swap, can avoid swapping “hot” pages
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Memory – Rightsizing
Generally it is better to OVER-commit than UNDER-commit
If the running VMs are consuming too much host/pool memory…
• Some VMs may not get physical memory
• Ballooning or host swapping
• Higher disk IO
• All VMs slow down
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Memory – Rightsizing
If a VM has too little vRAM…
• Applications suffer from lack of RAM
• The guest OS swaps
• Increased disk traffic, thrashing
• SAN slow down as a result of increased disk traffic
If a VM has too much vRAM…
• Higher overhead memory
• Possible decreased failover capacity
• Longer vMotion time
• Larger VSWP file
• Wasted resources
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Memory – Troubleshooting
Wrong resource allocation May not notice a limit, e.g. VM or template with a limit gets cloned
Custom share values
Ballooning or swapping at the host level
• Ballooning is a warning sign, not a problem
• Swapping is a performance issue if seen over an extended period
Swapping/paging at the guest level
• Under-provisioned guest memory
Missing balloon driver (Tools)
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Memory – Best Practices
Avoid high active host memory over-commitment
• No host swapping occurs when total memory demand is less than the physical memory (Assuming no limits)
Right-size guest memory
• Avoid guest OS swapping
Ensure there is enough vRAM to cover demand peaks
Use a fully automated DRS cluster
• Use Resource Pools with High/Normal/Low shares
• Avoid using custom shares
© 2009 VMware Inc. All rights reserved
CPU
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CPU – Overview
Raw processing power of a given host or VM
• Hosts provide CPU resources
• VMs and Resource Pools consume CPU resources
CPU cores/threads need to be shared between VMs
Fair scheduling vCPU time
• Hardware interrupts for a VM
• Parallel processing for SMP VMs
• I/O
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CPU – esxtop
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CPU – esxtop
Interpret the esxtop columns correctly
%RDY - The percentage of time a VM is ready to run, but no physical processor is ready to run it which may result in decreased performance
%USED – Physical CPU usage
%SYS – Percentage of time in the VMkernel
%RUN – Percentage of total scheduled time to run
%WAIT – Percentage of time in blocked or busy wait states
%IDLE – %WAIT- %IDLE can be used to estimate I/O wait time
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CPU – Performance Overhead & Utilization
Different workloads have different overhead costs (%SYS) even for the same utilization (%USED)
CPU virtualization adds varying amounts of system overhead
• Direct execution vs. privileged execution
• Non-paravirtual adapters vs. emulated adaptors
• Virtual hardware (Interrupts!)
• Network and storage I/O
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CPU – vSMP
Relaxed Co-Scheduling: vCPUs can run out-of-sync
Idle vCPUs incur a scheduling penalty
• configure only as many vCPUs as needed
• Imposes unnecessary scheduling constraints
Use Uniprocessor VMs for single-threaded applications
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CPU– Scheduling
Over committing physical CPUs
VMkernel CPU Scheduler
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CPU– Scheduling
Over committing physical CPUs
VMkernel CPU Scheduler
X X
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CPU– Scheduling
Over committing physical CPUs
VMkernel CPU Scheduler
X XX X
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CPU – Ready Time
The percentage of time that a vCPU is ready to execute, but waiting for physical CPU time
Does not necessarily indicate a problem
• Indicates possible CPU contention or limits
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CPU – NUMA nodes
Non-Uniform Memory Access system architecture
Each node consists of CPU cores and memory
A CPU core in one NUMA node can access memory in another node, but at a small performance cost
NUMA node 1 NUMA node 2
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CPU – Troubleshooting
vCPU to pCPU over allocation
• HyperThreading does not double CPU capacity!
Limits or too many reservations
• can create artificial limits.
Expecting the same consolidation ratios with different workloads
• Virtualizing “easy” systems first, then expanding to heavier systems
• Compare Apples to Apples
• Frequency, turbo, cache sizes, cache sharing, core count, instruction set…
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CPU – Best Practices
Right-size vSMP VMs
Keep heavy-hitters separated
• Fully automated DRS should do this for you
• Use anti-affinity rules if necessary
Use a fully automated DRS cluster
• Test that vMotion works
• Use Resource Pools with High/Normal/Low shares
• Avoid using custom shares
© 2009 VMware Inc. All rights reserved
STORAGE
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Storage – esxtop Counters
Different esxtop storage views
• Adapter (d)
• VM (v)
• Disk Device (u)
Key Fields:
• DAVG + KAVG = GAVG
• QUED/USD – Command Queue Depth
• CMDS/s – Commands Per Second
• MBREADS/s
• MBWRTN/s
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Storage – Troubleshooting with esxtop
High DAVG: issue beyond the adapter
• bad/overloaded zoning, over utilized storage processors, too few platters in the RAID set, etc.
High KAVG: issue in the kernel storage stack
• Driver issue
• Full queue
Aborts: GAVG exceeding 5000 ms
• Command will be repeated, storage delay for the VM
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Storage – Benchmarking with iometer
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Storage – Storage I/O Control
Allows the use of Shares per VMDK
Throttling occurs when datastore reaches latency threshold
• Higher share VMDKs perform IO first
vCenter monitors latency across all hosts
• Not effective if datastore shared with other vCenters
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Storage – Storage DRS
Datastore clusters
• Maintenance mode
• Anti-affinity rules
vCenter monitors for latency and disk space
• Migrate VMDKs for better performance or utilization
Not effective with automated tiering SANs
• Check HCL to confirm these features are compatible
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Storage – Troubleshooting
Snapshots
Excessive traffic down one HBA / Switch / SP can cause latency
• Consider using Round Robin in conjunction with ALUA
• Always be paranoid when it comes to monitoring storage I/O
Consider your I/O patterns
• Peak time for storage IO?
• Virus scans, database maintenance, user logins
Always consult with array vendor
• They know the best practices for their array!
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Storage – Best Practices
Use different tiers of storage for different VM workloads
• Slower storage for OS VMDKs
• Faster storage for databases or other high-IO applications
Use the Paravirtual SCSI adapter
• Reduced overhead, higher throughput
Use path balancing where possible, either through 3rd party plugins / Round Robin and ALUA, if supported.
Use Storage DRS with SIOC
• Balance for both free space and latency
• Simplified datastore management
© 2009 VMware Inc. All rights reserved
NETWORK
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Network – Load Balancing
Load balancing defines which uplink is used
• Route based on Port ID
• Route based on IP hash
• Route based on MAC hash
• Route based on NIC load (Load Based Teaming)
Probability of high-bandwidth VMs being on the same physical NIC
Traffic will stay on elected uplink until an event occurs
• NIC link state change, adding/removing NIC from a team, beacon probe timeout…
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Network – Troubleshooting
Check counters for NICs and VMs
• Network load imbalance
• 10 Gbps NICs can incur a significant CPU load when running at 100%
Ensure hardware supports TSO
• Use latest drivers and firmware for your NIC on the host
For multi-tier VM applications, use DRS affinity rules to keep VMs on same host
• Same vSwitch / VLAN, rules out physical network
If using Jumbo Frames, ensure it is enabled end-to-end
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Network – Best Practices
Use the vmxnet3 virtual adapter
• Less CPU overhead
• 10 Gbps connection to vSwitch
Use the latest driver/firmware for the NICs on the host
Use network shares
• Requires Virtual Distributed Switch 4.1
Isolate vMotion and iSCSI traffic from regular VM traffic
• Separate vSwitches with dedicated NIC(s)
• Most applicable with Gigabit NICs
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How to measure the network?
scp from/to ESXi host is not valid check!
With scp we will involve underlying storage on source and destination VM/host
CPU can affect the test, scp will encrypt/decrypt the network flow
Copy to ESXi host can give false result as the management interface has very limited resources
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How to check network performance?
VM – VM on same ESXi host. This will exclude physical network problems
VM –VM on different ESXi host. This will involve physical NICs and switch as well
Physical – VM. Will also test physical devices but we can focus on one VM
Physical – Physical: this will give us some number about what to expect
Use iperf/jperf/netperf. Free tool for network test
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Iperf
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Iperf
Windows and Linux version
Will not use storage
We can use different option for test (UDP/TCP)
Automatically calculates bandwith
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In conclusion…
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Key Takeaways – Performance Best Practices
Understand your environment
• Hardware, storage, networking
• VMs & applications
Advanced configuration values do not need to be tweaked or modified
• In almost all situations
Use fully automated DRS
Use Paravirtual hardware
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Important Links
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Important Links