Synnefo » snf-ganeti

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Partitioned Ganeti

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Current state and shortcomings

==============================

Currently Ganeti can be used to easily share a node between multiple

virtual instances. While it's easy to do a completely "best effort"

sharing it's quite harder to completely reserve resources for the use of

a particular instance. In particular this has to be done manually for

CPUs and disk, is implemented for RAM under Xen, but not under KVM, and

there's no provision for network level QoS.

Proposed changes

================

We want to make it easy to partition a node between machines with

exclusive use of hardware resources. While some sharing will anyway need

to happen (e.g. for operations that use the host domain, or use

resources, like buses, which are unique or very scarce on host systems)

we'll strive to maintain contention at a minimum, but won't try to avoid

all possible sources of it.

Exclusive use of disks

----------------------

``exclusive_storage`` is a new node parameter. When it's enabled, Ganeti

will allocate entire disks to instances. Though it's possible to think

of ways of doing something similar for other storage back-ends, this

design targets only ``plain`` and ``drbd``. The name is generic enough

in case the feature will be extended to other back-ends. The flag value

should be homogeneous within a node-group; ``cluster-verify`` will report

any violation of this condition.

Ganeti will consider each physical volume in the destination volume

group as a host disk (for proper isolation, an administrator should

make sure that there aren't multiple PVs on the same physical

disk). When ``exclusive_storage`` is enabled in a node group, all PVs

in the node group must have the same size (within a certain margin, say

1%, defined through a new parameter). Ganeti will check this condition

when the ``exclusive_storage`` flag is set, whenever a new node is added

and as part of ``cluster-verify``.

When creating a new disk for an instance, Ganeti will allocate the

minimum number of PVs to hold the disk, and those PVs will be excluded

from the pool of available PVs for further disk creations. The

underlying LV will be striped, when striping is allowed by the current

configuration. Ganeti will continue to track only the LVs, and query the

LVM layer to figure out which PVs are available and how much space is

free. Yet, creation, disk growing, and free-space reporting will ignore

any partially allocated PVs, so that PVs won't be shared between

instance disks.

For compatibility with the DRBD template and to take into account disk

variability, Ganeti will always subtract 2% (this will be a parameter)

from the PV space when calculating how many PVs are needed to allocate

an instance and when nodes report free space.

The obvious target for this option is plain disk template, which doesn't

provide redundancy. An administrator can still provide resilience

against disk failures by setting up RAID under PVs, but this is

transparent to Ganeti.

Spindles as a resource

~~~~~~~~~~~~~~~~~~~~~~

When resources are dedicated and there are more spindles than instances

on a node, it is natural to assign more spindles to instances than what

is strictly needed. For this reason, we introduce a new resource:

spindles. A spindle is a PV in LVM. The number of spindles required for

a disk of an instance is specified together with the size. Specifying

the number of spindles is possible only when ``exclusive_storage`` is

enabled. It is an error to specify a number of spindles insufficient to

contain the requested disk size.

When ``exclusive_storage`` is not enabled, spindles are not used in free

space calculation, in allocation algorithms, and policies. When it's

enabled, ``hspace``, ``hbal``, and allocators will use spindles instead

of disk size for their computation. For each node, the number of all the

spindles in every LVM group is recorded, and different LVM groups are

accounted separately in allocation and balancing.

There is already a concept of spindles in Ganeti. It's not related to

any actual spindle or volume count, but it's used in ``spindle_use`` to

measure the pressure of an instance on the storage system and in

``spindle_ratio`` to balance the I/O load on the nodes. When

``exclusive_storage`` is enabled, these parameters as currently defined

won't make any sense, so their meaning will be changed in this way:

- ``spindle_use`` refers to the resource, hence to the actual spindles

  (PVs in LVM), used by an instance. The values specified in the instance

  policy specifications are compared to the run-time numbers of spindle

  used by an instance. The ``spindle_use`` back-end parameter will be

  ignored.

- ``spindle_ratio`` in instance policies and ``spindle_count`` in node

  parameters are ignored, as the exclusive assignment of PVs already

  implies a value of 1.0 for the first, and the second is replaced by

  the actual number of spindles.

When ``exclusive_storage`` is disabled, the existing spindle parameters

behave as before.

Dedicated CPUs

--------------

``vpcu_ratio`` can be used to tie the number of VCPUs to the number of

CPUs provided by the hardware. We need to take into account the CPU

usage of the hypervisor. For Xen, this means counting the number of

VCPUs assigned to ``Domain-0``.

For KVM, it's more difficult to limit the number of CPUs used by the

node OS. ``cgroups`` could be a solution to restrict the node OS to use

some of the CPUs, leaving the other ones to instances and KVM processes.

For KVM, the number of CPUs for the host system should also be a

hypervisor parameter (set at the node group level).

Dedicated RAM

-------------

Instances should not compete for RAM. This is easily done on Xen, but it

is tricky on KVM.

Xen

~~~

Memory is already fully segregated under Xen, if sharing mechanisms

(transcendent memory, auto ballooning, etc) are not in use.

KVM

~~~

Under KVM or LXC memory is fully shared between the host system and all

the guests, and instances can even be swapped out by the host OS.

It's not clear if the problem can be solved by limiting the size of the

instances, so that there is plenty of room for the host OS.

We could implement segregation using cgroups to limit the memory used by

the host OS. This requires finishing the implementation of the memory

hypervisor status (set at the node group level) that changes how free

memory is computed under KVM systems. Then we have to add a way to

enforce this limit on the host system itself, rather than leaving it as

a calculation tool only.

Another problem for KVM is that we need to decide about the size of the

cgroup versus the size of the VM: some overhead will in particular

exist, due to the fact that an instance and its encapsulating KVM

process share the same space. For KVM systems the physical memory

allocatable to instances should be computed by subtracting an overhead

for the KVM processes, whose value can be either statically configured

or set in a hypervisor status parameter.

NUMA

~~~~

If instances are pinned to CPUs, and the amount of memory used for every

instance is proportionate to the number of VCPUs, NUMA shouldn't be a

problem, as the hypervisors allocate memory in the appropriate NUMA

node. Work is in progress in Xen and the Linux kernel to always allocate

memory correctly even without pinning. Therefore, we don't need to

address this problem specifically; it will be solved by future versions

of the hypervisors or by implementing CPU pinning.

Constrained instance sizes

--------------------------

In order to simplify allocation and resource provisioning we want to

limit the possible sizes of instances to a finite set of specifications,

defined at node-group level.

Currently it's possible to define an instance policy that limits the

minimum and maximum value for CPU, memory, and disk usage (and spindles

and any other resource, when implemented), independently from each other. We

extend the policy by allowing it to contain more occurrences of the

specifications for both the limits for the instance resources. Each

specification pair (minimum and maximum) has a unique priority

associated to it (or in other words, specifications are ordered), which

is used by ``hspace`` (see below). The standard specification doesn't

change: there is one for the whole cluster.

For example, a policy could be set up to allow instances with this

constraints:

- between 1 and 2 CPUs, 2 GB of RAM, and between 10 GB and 400 GB of

  disk space;

- 4 CPUs, 4 GB of RAM, and between 10 GB and 800 GB of disk space.

Then, an instance using 1 CPU, 2 GB of RAM and 50 GB of disk would be

legal, as an instance using 4 CPUs, 4 GB of RAM, and 20 GB of disk,

while an instance using 2 CPUs, 4 GB of RAM and 40 GB of disk would be

illegal.

Ganeti will refuse to create (or modify) instances that violate instance

policy constraints, unless the flag ``--ignore-ipolicy`` is passed.

While the changes needed to check constraint violations are

straightforward, ``hspace`` behavior needs some adjustments for tiered

allocation. ``hspace`` will start to allocate instances using the

maximum specification with the highest priority, then it will try to

lower the most constrained resources (without breaking the policy)

before moving to the second highest priority, and so on.

For consistent results in capacity calculation, the specifications

inside a policy should be ordered so that the biggest specifications

have the highest priorities. Also, specifications should not overlap.

Ganeti won't check nor enforce such constraints, though.

Implementation order

====================

We will implement this design in the following order:

- Exclusive use of disks (without spindles as a resource)

- Constrained instance sizes

- Spindles as a resource

- Dedicated CPU and memory

In this way have always new features that are immediately useful.

Spindles as a resource are not needed for correct capacity calculation,

as long as allowed disk sizes are multiples of spindle size, so it's

been moved after constrained instance sizes. If it turns out that it's

easier to implement dedicated disks with spindles as a resource, then we

will do that.

Possible future enhancements

============================

This section briefly describes some enhancements to the current design.

They may require their own design document, and must be re-evaluated

when considered for implementation, as Ganeti and the hypervisors may

change substantially in the meantime.

Network bandwidth

-----------------

A new resource is introduced: network bandwidth. An administrator must

be able to assign some network bandwidth to the virtual interfaces of an

instance, and set limits in instance policies. Also, a list of the

physical network interfaces available for Ganeti use and their maximum

bandwidth must be kept at node-group or node level. This information

will be taken into account for allocation, balancing, and free-space

calculation.

An additional enhancement is Ganeti enforcing the values set in the

bandwidth resource. This can be done by configuring limits for example

via openvswitch or normal QoS for bridging or routing. The bandwidth

resource represents the average bandwidth usage, so a few new back-end

parameters are needed to configure how to deal with bursts (they depend

on the actual way used to enforce the limit).

CPU pinning

-----------

In order to avoid unwarranted migrations between CPUs and to deal with

NUMA effectively we may need CPU pinning. CPU scheduling is a complex

topic and still under active development in Xen and the Linux kernel, so

we wont' try to outsmart their developers. If we need pinning it's more

to have predictable performance than to get the maximum performance

(which is best done by the hypervisor), so we'll implement a very simple

algorithm that allocates CPUs when an instance is assigned to a node

(either when it's created or when it's moved) and takes into account

NUMA and maybe CPU multithreading. A more refined version might run also

when an instance is deleted, but that would involve reassigning CPUs,

which could be bad with NUMA.

Overcommit for RAM and disks

----------------------------

Right now it is possible to assign more VCPUs to the instances running

on a node than there are CPU available. This works as normally CPU usage

on average is way below 100%. There are ways to share memory pages

(e.g. KSM, transcendent memory) and disk blocks, so we could add new

parameters to overcommit memory and disks, similar to ``vcpu_ratio``.

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