Documentation/HypervisorTuningGuide

About the Hypervisor Tuning Guide
The goal of the Hypervisor Tuning Guide (HTG) is to provide cloud operators with detailed instructions and settings to get the best performance out of their hypervisors.

This guide is broken into four major sections:


 * CPU
 * Memory
 * Network
 * Disk

Each section has tuning information for the following areas:


 * Symptoms of being (CPU, Memory, Network, Disk) bound
 * General hardware recommendations
 * Operating System configuration
 * Hypervisor configuration
 * OpenStack configuration
 * Instance and Image configuration
 * Validation, benchmarking, and reporting

How to Contribute
The HTG does not yet have a formal documentation repository since it's still very much in initial stages.

If you'd like to contribute, simply edit this wiki page! If you're not a fan of wikis, you can email Joe Topjian (joe@topjian.net) with any information that you feel is relevant. Maybe that's still too much typing, though, so if you're subscribed to the openstack-operators mailing list and your email client will auto-complete the address after a few characters, you can always send the information there.

If you'd much prefer sharing any information you have in person, please do so at the Ops mid-cycles and Summit events.

Please do not worry about grammar, spelling, or formatting. However, please try to add more than just short-hand notes.

What's Needed?
Right now, here are the most wanted areas:


 * Information about Hypervisors other than libvirt/KVM.
 * Information about operating systems other than Linux.
 * Real options, settings, and values that you have found to be successful in production.
 * Continue to expand and elaborate on existing areas.

Understanding Your Workload
I imagine this section to be the most theoretical / high level out of the entire guide.

CPU
Introduction about CPU.

Symptoms of Being CPU Bound
Compute Nodes that are CPU bound will generally see CPU usage at 80% or higher and idle usage less than 20%.

CPU Usage
On Linux-based systems, you can see CPU usage using the  tool. As an example:

procs ---memory-- ---swap-- -io -system-- --cpu- r b   swpd   free   buff  cache   si   so    bi    bo   in   cs us sy id wa st 1  0  35576 312096  95752 1104936    0    0     0     1    0    0  0  0 100  0  0
 * 1) vmstat

For CPU, there are five key areas to look at:


 * 1) r under procs: The number of running processes. If this number is consistently higher than the number of cores or CPUs on your compute node, then there are consistently more jobs being run than your node can handle.
 * 2) us under cpu: This is the amount of CPU spent running non-kernel code.
 * 3) sy under cpu: This is the amount of CPU spent running kernel code.
 * 4) id under cpu: This is the amount of idle CPU.
 * 5) st under cpu: This is the amount of stolen CPU. If an instance consistently sees a high st value, then the compute node hosting it might be under a lot of stress.

Load
Linux-based systems have an abstract concept of "Load". A high load means the system is running "hot" while a low load means it's relatively idle. But what number constitutes hot and cold? It varies from system to system. A general rule of thumb is that the system load will equal 1 when a core or CPU is consistently processing a job. Therefore, a normal load is equal to the number of cores / CPUs or less.

However, exaggeratedly high loads (100+) are usually an indication of IO problems and not CPU problems.

Load should not be used as the sole metric when diagnosing potential Compute Node problems. It's best to use Load as an indication to check further areas.

Simultaneous Multithreading
Simultaneous multithreading (SMT), commonly known as Hyper-threading in Intel CPUs, is a technology that enables the Operating System to see a single core / CPU as two cores / CPUs. This feature can usually be enabled or disabled in the Compute Node's BIOS.

It's important to understand that SMT will not make jobs run faster. Rather, it will allow two jobs to run simultaneously where only one job would have run before. Thus, SMT, in some cases, can increase the amount of completed jobs within the same time span than if it was turned off. CERN has seen a throughput increase of 20% with SMT enabled

The following guidelines are known for specific use cases:


 * Enable it for general purpose workloads
 * Disable it for virtual router applications

Notable CPU Flags
The following CPU flags have special relevance to virtualization. On Linux-based systems, you can see what flags are enabled and functional by doing:

$ cat /proc/cpuinfo


 * vmx (Intel) and smx (AMD): Hardware virtualization support
 * Add something here about nested virtualization support. I think there are requirements from both the CPU and hypervisor?
 * avx: Advanced Vector Extensions
 * sse4</tt>: Streaming SIMD Extensions 4
 * aes-ni</tt>: Advanced Encryption Standard New Instructions

TBD

 * thread policies can also be important (prefer/avoid) - hopefully a mitaka enhancement
 * NUMA?
 * http://docs.openstack.org/developer/nova/testing/libvirt-numa.html
 * CPU pinning

Linux

 * exclude cores, dedicate cores / cpus specifically for certain OS tasks
 * iso cpu
 * see rh blog post below
 * reasonable increase in performance by compiling own kernels
 * turn off cpu scaling - run at full frequency
 * TSC
 * x86 Specific - different architectures have different timekeeping mechanisms
 * can be virtualised or not
 * can run one core slower than another
 * clock source
 * avoiding jitter - eg asterisk, telephony
 * time stamp counter, is it a tec vs hpet thing?

Windows

 * virtio drivers

Hyper-V

 * has numa spanning enabled by default, should be disabled for performance, caveat with restarting instance

CPU Mode and Model
The two most notable CPU-related configuration options in Nova are:


 * 1) cpu_mode
 * 2) cpu_model

Both of these items can be read about in detail in the config reference. Additionally, CERN's experience with benchmarking  can be found here.

Overcommitting
You can configure Nova to report that the Compute Node has more CPUs than it really does by altering the  setting on each Compute Node. This setting can either take a whole or fraction of a number. For example:


 * : Configures Nova to report it has 16 times the number of CPUs than what the Compute Node really has. This is the default.
 * : Configures Nova to report it has 1.5 times the number of CPUs.
 * : Effectively disables CPU overcommitting.

Generally, it's safe to overcommit CPUs. It has been reported that the main reason not to overcommit CPU is because of not overcommitting memory (which will be explained in the Memory section of this guide).

Note: You must also make sure  contains   in order to use.


 * RAM overcommit, particularly with KSM, has a CPU hit as well

Instance and Image Configuration

 * Describe scenarios where the instance sees a CPU flag but cannot use it.
 * CPU quotas and shares
 * Reported use-case: default of 80% on all flavors, if workloads are very cpu heavy, don't do.
 * guest kernel scheduler set to "none" (elevator=noop on kernel command line)
 * what are the benefits of this? host and guest schedulers don't fight
 * Hyper-v enlightenment features
 * Hyper-v gen 2 vms are seen to be faster than gen 1, reason?

General Tools

 * top
 * vmstat
 * htop

Benchmarking Tools

 * phoronix
 * Benchmark suite like HEP-Spec2006 used in High energy physics for HTC workers node give mark in HS06 (http://w3.hepix.org/benchmarks/doku.php/)
 * Depends on your workload. Test using the dominant workload that is going to be run on your cloud.
 * For Java-related workloads, DaCapo is a pretty good benchmark - http://www.dacapobench.org
 * What about full system simulations? ie: Deploy an entire Hadoop cluster and have it create large simulated loads?
 * Did for hadoop with 10+ nodes
 * This is a good idea, TeraSort type benchmarks are really useful.
 * https://github.com/ibmcb/cbtool
 * http://www.phoronix-test-suite.com/
 * https://github.com/GoogleCloudPlatform/PerfKitBenchmarker

System

 * CPU: user, system, iowait, irq, soft irq

Instance

 * nova diagnostics
 * Do not record per-process stats - explain why
 * overlaying cputime vs allocated cpu

Symptoms of Being Memory Bound
In general, the  command can be used to determine the amount of memory used and available. Linux usually reports much more memory being used than in reality. This site offers good information about reading how much memory is available.

Another symptom of being memory bound is running out of swap space. The  command also reports swap usage.

OOM Killer
The Out of Memory Killer is a kernel feature that will reap processes when the system is truly out of memory. You can determine if processes are being reaped by looking for the following in your logs:

Out of memory: Kill process

More information about the OOM Killer can be found here.

NUMA Balancing
It's recommended to ensure that each NUMA node has the same amount of memory. If you plan to upgrade the amount of memory in a compute node, ensure the amount is balanced on each node. For example, do not upgrade one node by 16GB and another by 8GB.

Memory Speeds
Memory speeds are known to vary by chip. If possible, ensure all memory in a system is the same brand and type.

More on this?

Linux
Go into depth about NUMA, huge pages, and other Linux/memory areas. Pull from the following articles:


 * NFVI Deployment Guide - Huge Pages
 * Examining Huge Pages or Transparent Huge Pages performance
 * RHEL Performance Guide - CPU
 * RHEL Performance Guide - Memboy
 * Mysteries of NUMA Memory Management Revealed
 * Optimizing Linux Memory Management for Low-latency / High-throughput Databases

Kernel Tunables

 * Transparent Hugepage Support: can go either way depending on workload
 * Memory overcommit
 * KSM enables identical memory pages to be combined. This is a form of memory deduplication.

KVM / libvirt
libvirt/KVM has memory ballooning support, though Nova does not take advantage of it.

libvirt/KVM also has support for Extended Page Table. Consider enabling or disabling it depending on your workload. For example, having EPT enabled has been seen to impact performance on High Energy Physics applications.

OpenStack Configuration
You can configure the amount of memory reserved for the compute node (meaning, instances will not have access to it) by setting the  setting in   The default is 512mb which has been reported to be too low for real-world use.

Overcommitting
You can configure Nova to overcommit the available amount of memory with the  setting in. By default, this is set to 1.5:1, meaning Nova will think you have 1.5x more memory than you really do.

Flavor Extra Specs

 * hw:mem_pages_size: Specify the page size to the guest.

nova flavor-key m1.small set hw:mem_page_size=2048

Guest Notes
At this time, guests cannot see the speed of the memory.

General Tools

 * free
 * sar

Benchmarking

 * stream

System
can provide the following metrics:


 * page in
 * page out
 * page scans
 * page faults

can provide the amount of available memory over time.

can also provide general memory information.

Instance
The  command can be used to display memory usage of individual instances. Keep in mind, though, that since OpenStack cannot "deflate" the virtio memory balloon in libvirt/KVM environments, memory will always be seen to increase until max capacity is reached.

can also be used to view memory usage in libvirt/KVM environments.

Symptoms of Being Network Bound
Network-bound compute nodes will see symptoms like the following:
 * On the guest, the  metric will be high.   can be seen in the 7th column of the   output.
 * If your instances' ephemeral disks are stored on a network storage device, you will see a high amount of "IO Wait" time.
 * You might see discards on your network switches
 * You might see many dropped packets on the hypervisor

General Hardware Recommendations
10gb NICs are recommended over 1gb NICs.

It's generally recommended to use some type of NIC bonding on your compute nodes. LACP is the most common form of bonding, though be aware that it requires configuration on both the Linux side and the upstream network side.

(todo: balance-tlb and balance-alb?)

Modern NICs have features such as VXLAN offloading which should decrease the amount of work required on the compute node iteself.

Linux
CloudFlare has an article on network tuning within Linux. (todo: vet the article, add more references).

Disabling GRO might help increase performance. See the following articles for reference:
 * 
 * 

Check the NUMA locality of SR-IOV (and passthrough) devices (pretty much get this for free if you are using NUMATopologyFilter and have a chipset that has locality)

Jumbo frames (9000 MTU) might also provide a performance benefit. It might also be required depending on your network topology and configuration.

Kernel Tunables

 * : time of connection inactivity after which the first keep alive request is sent
 * : Limits the  listen backlog. A higher value can support a higher amount of simultaneous requests.
 * : Increase the connection tracking limit. Hitting this limit will cause packet loss and other odd behavior (such as random ping loss). Common values are anywhere between 64k and 512k.
 * You should definitely increase this value if you use . See here.
 * : In addition to to, also increase the size of the hash-table where the connection tracking is stored. Common values are anywhere between 16k and 128k
 * : For UDP request response type traffic which doesn't reuse the UDP port (DNS traffic, for example), lower this value to something like "5".
 * (todo) Different queue algos: FQ_CODEL,
 * should be increased on the interface if you are seeing dropped packets

KVM / libvirt
vhost-net usually provides better performance than just the virtio driver (vhost-net can be thought of as a complementary enhancement to virtio). To enable vhost-net, do:

$ sudo modprobe vhost_net

If you aren't able to use vhost-net, make sure to at least use the virtio driver regardless.

virtio-multiqueue can also increase performance (todo: elaborate).

If you're using an Open vSwitch-based environment, look into OVS acceleration such as  (todo: elaborate. relevant? more info?)

Instance and Image Configuration

 * PCI passthrough can be used to give an instance direct access to a NIC.
 * SR-IOV might also provide benefits.


 * Network IO quotas and shares
 * not advanced enough
 * instead, using libvirt hooks
 * todo: elaborate on this

General Tools
iftop is a top-like tool for network traffic.

Benchmarking
iperf can be considered the standard for network benchmarking

System
The collection of  files can provide a wealth of network-based metrics. Additionally,  can provide further information and metrics.

Instance
can provide network statistics of the instance.

and  can also be used to obtain network statistics on KVM/libvirt-based hypervisors.

Symptoms of Being Disk Bound
Compute nodes that are disk bound might see extremely high load values in the range of 50+. They will also see a large  value (which can be seen using the   utility).

Spindle vs SSD
Some find using SSD-based disks for logging useful. CERN has tested SSD with  and have found it successful.

Be aware that some have run into too many faulty SSD disks for them to consider them worthwhile. This should not scare you from using SSD disks, just something to keep in mind.
 * SSD: TRIM, trim requests from guest aren't passed to hypervisor

Hardware RAID, Software RAID, no RAID?
Some people either don't use a hardware RAID card or will create individual RAID0 drives and pass them through to the compute node. They will then use  to provide the drive resiliency.

Hardware RAID5 has been mentioned to provide the best durability. Others use RAID1 for the operating system and JBOD for ephemeral. This configuration does not provide resiliency for ephemeral disks, though.

For best performance, ensure the filesystem write size matches the RAID stripe size.

If you use a hardware RAID card with a battery backup, be aware that if the battery dies and writes switch from "write back" to write through", you will incur a performance hit.

Linux
XFS and EXT4 are the most common filesystems to use.

For XFS, turn on [http://xfs.org/index.php/XFS_FAQ#Write_barrier_support. barrier] for performance, but not for database-related activity.

The decision to use either the CFQ or deadline kernel schedules is highly workload specific. (todo: elaborate)

Caching, of course, can offer great performance benefits, but be aware of the data loss that will incur if the cache is ever lost during an event such as a power failure.

If your workload can incur data loss, having  and mounting the guest root with   can increase performance. See here for information.

KVM / libvirt
This article contains useful information about KVM/libvirt and caching.

VirtIO SCSI is a para-virtualized SCSI controller and is a successor to. It enables SCSI-passthrough and, in certain cases, enables the guest to better detect volume disconnects. As well, it sets the instance's devices names to the more standard. To enable  in the guest, see Instance and Image Configuration.

OpenStack Configuration
This article is a great reference for the many ways that backing disks can be configured in OpenStack. The many configuration combinations all have advantages and disadvantages depending on your overall storage environment (todo: elaborate).

Image Formats
qcow files are smaller than raw files due to thin-provisioning. qcow also has the advantage of being able to do "copy-on-write" with a backing file.

See the following blueprint for ways in which qcow can be configured for performance.

If you are using Redhat, pre-linking turned on by default. So after the VM boots, prelinker re-writes all the libraries and the qcow grows like crazy even with no disk activity. It's recommended to disable the prelinker to avoid this.

Images Type
Some positive experience on performance for I/O has been reported using images_type=lvm. This involves setting up a volume group and then allocating the VMs from dedicated block devices to the VM using LVM on the hypervisor.

Overcommit
Disk overcommitting is generally a safe thing to do. Thin-provisioning can increase the amount of available storage by not allocating empty storage.

Image Metadata
To take advantage of, add the following key/value pairs to an image:

hw_disk_bus_model=virtio-scsi hw_scsi_model=virtio-scsi hw_disk_bus=scsi

Guest Notes
tuned is a utility that can adaptively configure a system. The "virtual-guest" profile has been known to work well for guests.

A performance increase was not seen when switching between IDE and SCSI block drivers. SCSI has support for TRIM, but guest-originated TRIM requests are currently ignored (verify?).

Disk IO limits can be enforced on both ephemeral disks and volumes. We need to determine how to effectively apply these limits, though (help!)

On guest images, it's recommended to use the noop scheduler as well as to turn off  and prelinking.

Benchmarking

 * fio is a great tool for extensive benchmarks.
 * bonnie++ is great for quick benchmarks.

System

 * iowait
 * iops
 * iostats
 * vmstat
 * sysstat (sar metrics)

Instance
can pull the IO activity from an instance's disks.

and  can also be used on KVM/libvirt-based hypervisors to pull disk statistics.