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

Ganeti 2.1 design

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

This document describes the major changes in Ganeti 2.1 compared to

the 2.0 version.

The 2.1 version will be a relatively small release. Its main aim is to

avoid changing too much of the core code, while addressing issues and

adding new features and improvements over 2.0, in a timely fashion.

.. contents:: :depth: 4

Objective

=========

Ganeti 2.1 will add features to help further automatization of cluster

operations, further improve scalability to even bigger clusters, and

make it easier to debug the Ganeti core.

Detailed design

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

As for 2.0 we divide the 2.1 design into three areas:

- core changes, which affect the master daemon/job queue/locking or

  all/most logical units

- logical unit/feature changes

- external interface changes (eg. command line, os api, hooks, ...)

Core changes

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

Storage units modelling

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

Currently, Ganeti has a good model of the block devices for instances

(e.g. LVM logical volumes, files, DRBD devices, etc.) but none of the

storage pools that are providing the space for these front-end

devices. For example, there are hardcoded inter-node RPC calls for

volume group listing, file storage creation/deletion, etc.

The storage units framework will implement a generic handling for all

kinds of storage backends:

- LVM physical volumes

- LVM volume groups

- File-based storage directories

- any other future storage method

There will be a generic list of methods that each storage unit type

will provide, like:

- list of storage units of this type

- check status of the storage unit

Additionally, there will be specific methods for each method, for

example:

- enable/disable allocations on a specific PV

- file storage directory creation/deletion

- VG consistency fixing

This will allow a much better modeling and unification of the various

RPC calls related to backend storage pool in the future. Ganeti 2.1 is

intended to add the basics of the framework, and not necessarilly move

all the curent VG/FileBased operations to it.

Note that while we model both LVM PVs and LVM VGs, the framework will

**not** model any relationship between the different types. In other

words, we don't model neither inheritances nor stacking, since this is

too complex for our needs. While a ``vgreduce`` operation on a LVM VG

could actually remove a PV from it, this will not be handled at the

framework level, but at individual operation level. The goal is that

this is a lightweight framework, for abstracting the different storage

operation, and not for modelling the storage hierarchy.

Locking improvements

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

Current State and shortcomings

++++++++++++++++++++++++++++++

The class ``LockSet`` (see ``lib/locking.py``) is a container for one or

many ``SharedLock`` instances. It provides an interface to add/remove

locks and to acquire and subsequently release any number of those locks

contained in it.

Locks in a ``LockSet`` are always acquired in alphabetic order. Due to

the way we're using locks for nodes and instances (the single cluster

lock isn't affected by this issue) this can lead to long delays when

acquiring locks if another operation tries to acquire multiple locks but

has to wait for yet another operation.

In the following demonstration we assume to have the instance locks

``inst1``, ``inst2``, ``inst3`` and ``inst4``.

#. Operation A grabs lock for instance ``inst4``.

#. Operation B wants to acquire all instance locks in alphabetic order,

   but it has to wait for ``inst4``.

#. Operation C tries to lock ``inst1``, but it has to wait until

   Operation B (which is trying to acquire all locks) releases the lock

   again.

#. Operation A finishes and releases lock on ``inst4``. Operation B can

   continue and eventually releases all locks.

#. Operation C can get ``inst1`` lock and finishes.

Technically there's no need for Operation C to wait for Operation A, and

subsequently Operation B, to finish. Operation B can't continue until

Operation A is done (it has to wait for ``inst4``), anyway.

Proposed changes

++++++++++++++++

Non-blocking lock acquiring

^^^^^^^^^^^^^^^^^^^^^^^^^^^

Acquiring locks for OpCode execution is always done in blocking mode.

They won't return until the lock has successfully been acquired (or an

error occurred, although we won't cover that case here).

``SharedLock`` and ``LockSet`` must be able to be acquired in a

non-blocking way. They must support a timeout and abort trying to

acquire the lock(s) after the specified amount of time.

Retry acquiring locks

^^^^^^^^^^^^^^^^^^^^^

To prevent other operations from waiting for a long time, such as

described in the demonstration before, ``LockSet`` must not keep locks

for a prolonged period of time when trying to acquire two or more locks.

Instead it should, with an increasing timeout for acquiring all locks,

release all locks again and sleep some time if it fails to acquire all

requested locks.

A good timeout value needs to be determined. In any case should

``LockSet`` proceed to acquire locks in blocking mode after a few

(unsuccessful) attempts to acquire all requested locks.

One proposal for the timeout is to use ``2**tries`` seconds, where

``tries`` is the number of unsuccessful tries.

In the demonstration before this would allow Operation C to continue

after Operation B unsuccessfully tried to acquire all locks and released

all acquired locks (``inst1``, ``inst2`` and ``inst3``) again.

Other solutions discussed

+++++++++++++++++++++++++

There was also some discussion on going one step further and extend the

job queue (see ``lib/jqueue.py``) to select the next task for a worker

depending on whether it can acquire the necessary locks. While this may

reduce the number of necessary worker threads and/or increase throughput

on large clusters with many jobs, it also brings many potential

problems, such as contention and increased memory usage, with it. As

this would be an extension of the changes proposed before it could be

implemented at a later point in time, but we decided to stay with the

simpler solution for now.

Implementation details

++++++++++++++++++++++

``SharedLock`` redesign

^^^^^^^^^^^^^^^^^^^^^^^

The current design of ``SharedLock`` is not good for supporting timeouts

when acquiring a lock and there are also minor fairness issues in it. We

plan to address both with a redesign. A proof of concept implementation

was written and resulted in significantly simpler code.

Currently ``SharedLock`` uses two separate queues for shared and

exclusive acquires and waiters get to run in turns. This means if an

exclusive acquire is released, the lock will allow shared waiters to run

and vice versa.  Although it's still fair in the end there is a slight

bias towards shared waiters in the current implementation. The same

implementation with two shared queues can not support timeouts without

adding a lot of complexity.

Our proposed redesign changes ``SharedLock`` to have only one single

queue.  There will be one condition (see Condition_ for a note about

performance) in the queue per exclusive acquire and two for all shared

acquires (see below for an explanation). The maximum queue length will

always be ``2 + (number of exclusive acquires waiting)``. The number of

queue entries for shared acquires can vary from 0 to 2.

The two conditions for shared acquires are a bit special. They will be

used in turn. When the lock is instantiated, no conditions are in the

queue. As soon as the first shared acquire arrives (and there are

holder(s) or waiting acquires; see Acquire_), the active condition is

added to the queue. Until it becomes the topmost condition in the queue

and has been notified, any shared acquire is added to this active

condition. When the active condition is notified, the conditions are

swapped and further shared acquires are added to the previously inactive

condition (which has now become the active condition). After all waiters

on the previously active (now inactive) and now notified condition

received the notification, it is removed from the queue of pending

acquires.

This means shared acquires will skip any exclusive acquire in the queue.

We believe it's better to improve parallelization on operations only

asking for shared (or read-only) locks. Exclusive operations holding the

same lock can not be parallelized.

Acquire

*******

For exclusive acquires a new condition is created and appended to the

queue.  Shared acquires are added to the active condition for shared

acquires and if the condition is not yet on the queue, it's appended.

The next step is to wait for our condition to be on the top of the queue

(to guarantee fairness). If the timeout expired, we return to the caller

without acquiring the lock. On every notification we check whether the

lock has been deleted, in which case an error is returned to the caller.

The lock can be acquired if we're on top of the queue (there is no one

else ahead of us). For an exclusive acquire, there must not be other

exclusive or shared holders. For a shared acquire, there must not be an

exclusive holder.  If these conditions are all true, the lock is

acquired and we return to the caller. In any other case we wait again on

the condition.

If it was the last waiter on a condition, the condition is removed from

the queue.

Optimization: There's no need to touch the queue if there are no pending

acquires and no current holders. The caller can have the lock

immediately.

.. image:: design-2.1-lock-acquire.png

Release

*******

First the lock removes the caller from the internal owner list. If there

are pending acquires in the queue, the first (the oldest) condition is

notified.

If the first condition was the active condition for shared acquires, the

inactive condition will be made active. This ensures fairness with

exclusive locks by forcing consecutive shared acquires to wait in the

queue.

.. image:: design-2.1-lock-release.png

Delete

******

The caller must either hold the lock in exclusive mode already or the

lock must be acquired in exclusive mode. Trying to delete a lock while

it's held in shared mode must fail.

After ensuring the lock is held in exclusive mode, the lock will mark

itself as deleted and continue to notify all pending acquires. They will

wake up, notice the deleted lock and return an error to the caller.

Condition

^^^^^^^^^

Note: This is not necessary for the locking changes above, but it may be

a good optimization (pending performance tests).

The existing locking code in Ganeti 2.0 uses Python's built-in

``threading.Condition`` class. Unfortunately ``Condition`` implements

timeouts by sleeping 1ms to 20ms between tries to acquire the condition

lock in non-blocking mode. This requires unnecessary context switches

and contention on the CPython GIL (Global Interpreter Lock).

By using POSIX pipes (see ``pipe(2)``) we can use the operating system's

support for timeouts on file descriptors (see ``select(2)``). A custom

condition class will have to be written for this.

On instantiation the class creates a pipe. After each notification the

previous pipe is abandoned and re-created (technically the old pipe

needs to stay around until all notifications have been delivered).

All waiting clients of the condition use ``select(2)`` or ``poll(2)`` to

wait for notifications, optionally with a timeout. A notification will

be signalled to the waiting clients by closing the pipe. If the pipe

wasn't closed during the timeout, the waiting function returns to its

caller nonetheless.

Node daemon availability

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

Current State and shortcomings

++++++++++++++++++++++++++++++

Currently, when a Ganeti node suffers serious system disk damage, the

migration/failover of an instance may not correctly shutdown the virtual

machine on the broken node causing instances duplication. The ``gnt-node

powercycle`` command can be used to force a node reboot and thus to

avoid duplicated instances. This command relies on node daemon

availability, though, and thus can fail if the node daemon has some

pages swapped out of ram, for example.

Proposed changes

++++++++++++++++

The proposed solution forces node daemon to run exclusively in RAM. It

uses python ctypes to to call ``mlockall(MCL_CURRENT | MCL_FUTURE)`` on

the node daemon process and all its children. In addition another log

handler has been implemented for node daemon to redirect to

``/dev/console`` messages that cannot be written on the logfile.

With these changes node daemon can successfully run basic tasks such as

a powercycle request even when the system disk is heavily damaged and

reading/writing to disk fails constantly.

New Features

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

Automated Ganeti Cluster Merger

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

Current situation

+++++++++++++++++

Currently there's no easy way to merge two or more clusters together.

But in order to optimize resources this is a needed missing piece. The

goal of this design doc is to come up with a easy to use solution which

allows you to merge two or more cluster together.

Initial contact

+++++++++++++++

As the design of Ganeti is based on an autonomous system, Ganeti by

itself has no way to reach nodes outside of its cluster. To overcome

this situation we're required to prepare the cluster before we can go

ahead with the actual merge: We've to replace at least the ssh keys on

the affected nodes before we can do any operation within ``gnt-``

commands.

To make this a automated process we'll ask the user to provide us with

the root password of every cluster we've to merge. We use the password

to grab the current ``id_dsa`` key and then rely on that ssh key for any

further communication to be made until the cluster is fully merged.

Cluster merge

+++++++++++++

After initial contact we do the cluster merge:

1. Grab the list of nodes

2. On all nodes add our own ``id_dsa.pub`` key to ``authorized_keys``

3. Stop all instances running on the merging cluster

4. Disable ``ganeti-watcher`` as it tries to restart Ganeti daemons

5. Stop all Ganeti daemons on all merging nodes

6. Grab the ``config.data`` from the master of the merging cluster

7. Stop local ``ganeti-masterd``

8. Merge the config:

   1. Open our own cluster ``config.data``

   2. Open cluster ``config.data`` of the merging cluster

   3. Grab all nodes of the merging cluster

   4. Set ``master_candidate`` to false on all merging nodes

   5. Add the nodes to our own cluster ``config.data``

   6. Grab all the instances on the merging cluster

   7. Adjust the port if the instance has drbd layout:

      1. In ``logical_id`` (index 2)

      2. In ``physical_id`` (index 1 and 3)

   8. Add the instances to our own cluster ``config.data``

9. Start ``ganeti-masterd`` with ``--no-voting`` ``--yes-do-it``

10. ``gnt-node add --readd`` on all merging nodes

11. ``gnt-cluster redist-conf``

12. Restart ``ganeti-masterd`` normally

13. Enable ``ganeti-watcher`` again

14. Start all merging instances again

Rollback

++++++++

Until we actually (re)add any nodes we can abort and rollback the merge

at any point. After merging the config, though, we've to get the backup

copy of ``config.data`` (from another master candidate node). And for

security reasons it's a good idea to undo ``id_dsa.pub`` distribution by

going on every affected node and remove the ``id_dsa.pub`` key again.

Also we've to keep in mind, that we've to start the Ganeti daemons and

starting up the instances again.

Verification

++++++++++++

Last but not least we should verify that the merge was successful.

Therefore we run ``gnt-cluster verify``, which ensures that the cluster

overall is in a healthy state. Additional it's also possible to compare

the list of instances/nodes with a list made prior to the upgrade to

make sure we didn't lose any data/instance/node.

Appendix

++++++++

cluster-merge.py

^^^^^^^^^^^^^^^^

Used to merge the cluster config. This is a POC and might differ from

actual production code.

::

  #!/usr/bin/python

  import sys

  from ganeti import config

  from ganeti import constants

  c_mine = config.ConfigWriter(offline=True)

  c_other = config.ConfigWriter(sys.argv[1])

  fake_id = 0

  for node in c_other.GetNodeList():

    node_info = c_other.GetNodeInfo(node)

    node_info.master_candidate = False

    c_mine.AddNode(node_info, str(fake_id))

    fake_id += 1

  for instance in c_other.GetInstanceList():

    instance_info = c_other.GetInstanceInfo(instance)

    for dsk in instance_info.disks:

      if dsk.dev_type in constants.LDS_DRBD:

         port = c_mine.AllocatePort()

         logical_id = list(dsk.logical_id)

         logical_id[2] = port

         dsk.logical_id = tuple(logical_id)

         physical_id = list(dsk.physical_id)

         physical_id[1] = physical_id[3] = port

         dsk.physical_id = tuple(physical_id)

    c_mine.AddInstance(instance_info, str(fake_id))

    fake_id += 1

Feature changes

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

Ganeti Confd

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

Current State and shortcomings

++++++++++++++++++++++++++++++

In Ganeti 2.0 all nodes are equal, but some are more equal than others.

In particular they are divided between "master", "master candidates" and

"normal".  (Moreover they can be offline or drained, but this is not

important for the current discussion). In general the whole

configuration is only replicated to master candidates, and some partial

information is spread to all nodes via ssconf.

This change was done so that the most frequent Ganeti operations didn't

need to contact all nodes, and so clusters could become bigger. If we

want more information to be available on all nodes, we need to add more

ssconf values, which is counter-balancing the change, or to talk with

the master node, which is not designed to happen now, and requires its

availability.

Information such as the instance->primary_node mapping will be needed on

all nodes, and we also want to make sure services external to the

cluster can query this information as well. This information must be

available at all times, so we can't query it through RAPI, which would

be a single point of failure, as it's only available on the master.

Proposed changes

++++++++++++++++

In order to allow fast and highly available access read-only to some

configuration values, we'll create a new ganeti-confd daemon, which will

run on master candidates. This daemon will talk via UDP, and

authenticate messages using HMAC with a cluster-wide shared key. This

key will be generated at cluster init time, and stored on the clusters

alongside the ganeti SSL keys, and readable only by root.

An interested client can query a value by making a request to a subset

of the cluster master candidates. It will then wait to get a few

responses, and use the one with the highest configuration serial number.

Since the configuration serial number is increased each time the ganeti

config is updated, and the serial number is included in all answers,

this can be used to make sure to use the most recent answer, in case

some master candidates are stale or in the middle of a configuration

update.

In order to prevent replay attacks queries will contain the current unix

timestamp according to the client, and the server will verify that its

timestamp is in the same 5 minutes range (this requires synchronized

clocks, which is a good idea anyway). Queries will also contain a "salt"

which they expect the answers to be sent with, and clients are supposed

to accept only answers which contain salt generated by them.

The configuration daemon will be able to answer simple queries such as:

- master candidates list

- master node

- offline nodes

- instance list

- instance primary nodes

Wire protocol

^^^^^^^^^^^^^

A confd query will look like this, on the wire::

  plj0{

    "msg": "{\"type\": 1,

             \"rsalt\": \"9aa6ce92-8336-11de-af38-001d093e835f\",

             \"protocol\": 1,

             \"query\": \"node1.example.com\"}\n",

    "salt": "1249637704",

    "hmac": "4a4139b2c3c5921f7e439469a0a45ad200aead0f"

  }

"plj0" is a fourcc that details the message content. It stands for plain

json 0, and can be changed as we move on to different type of protocols

(for example protocol buffers, or encrypted json). What follows is a

json encoded string, with the following fields:

- 'msg' contains a JSON-encoded query, its fields are:

  - 'protocol', integer, is the confd protocol version (initially just

    constants.CONFD_PROTOCOL_VERSION, with a value of 1)

  - 'type', integer, is the query type. For example "node role by name"

    or "node primary ip by instance ip". Constants will be provided for

    the actual available query types.

  - 'query', string, is the search key. For example an ip, or a node

    name.

  - 'rsalt', string, is the required response salt. The client must use

    it to recognize which answer it's getting.

- 'salt' must be the current unix timestamp, according to the client.

  Servers can refuse messages which have a wrong timing, according to

  their configuration and clock.

- 'hmac' is an hmac signature of salt+msg, with the cluster hmac key

If an answer comes back (which is optional, since confd works over UDP)

it will be in this format::

  plj0{

    "msg": "{\"status\": 0,

             \"answer\": 0,

             \"serial\": 42,

             \"protocol\": 1}\n",

    "salt": "9aa6ce92-8336-11de-af38-001d093e835f",

    "hmac": "aaeccc0dff9328fdf7967cb600b6a80a6a9332af"

  }

Where:

- 'plj0' the message type magic fourcc, as discussed above

- 'msg' contains a JSON-encoded answer, its fields are:

  - 'protocol', integer, is the confd protocol version (initially just

    constants.CONFD_PROTOCOL_VERSION, with a value of 1)

  - 'status', integer, is the error code. Initially just 0 for 'ok' or

    '1' for 'error' (in which case answer contains an error detail,

    rather than an answer), but in the future it may be expanded to have

    more meanings (eg: 2, the answer is compressed)

  - 'answer', is the actual answer. Its type and meaning is query

    specific. For example for "node primary ip by instance ip" queries

    it will be a string containing an IP address, for "node role by

    name" queries it will be an integer which encodes the role (master,

    candidate, drained, offline) according to constants.

- 'salt' is the requested salt from the query. A client can use it to

  recognize what query the answer is answering.

- 'hmac' is an hmac signature of salt+msg, with the cluster hmac key

Redistribute Config

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

Current State and shortcomings

++++++++++++++++++++++++++++++

Currently LURedistributeConfig triggers a copy of the updated

configuration file to all master candidates and of the ssconf files to

all nodes. There are other files which are maintained manually but which

are important to keep in sync. These are:

- rapi SSL key certificate file (rapi.pem) (on master candidates)

- rapi user/password file rapi_users (on master candidates)

Furthermore there are some files which are hypervisor specific but we

may want to keep in sync:

- the xen-hvm hypervisor uses one shared file for all vnc passwords, and

  copies the file once, during node add. This design is subject to

  revision to be able to have different passwords for different groups

  of instances via the use of hypervisor parameters, and to allow

  xen-hvm and kvm to use an equal system to provide password-protected

  vnc sessions. In general, though, it would be useful if the vnc

  password files were copied as well, to avoid unwanted vnc password

  changes on instance failover/migrate.

Optionally the admin may want to also ship files such as the global

xend.conf file, and the network scripts to all nodes.

Proposed changes

++++++++++++++++

RedistributeConfig will be changed to copy also the rapi files, and to

call every enabled hypervisor asking for a list of additional files to

copy. Users will have the possibility to populate a file containing a

list of files to be distributed; this file will be propagated as well.

Such solution is really simple to implement and it's easily usable by

scripts.

This code will be also shared (via tasklets or by other means, if

tasklets are not ready for 2.1) with the AddNode and SetNodeParams LUs

(so that the relevant files will be automatically shipped to new master

candidates as they are set).

VNC Console Password

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

Current State and shortcomings

++++++++++++++++++++++++++++++

Currently just the xen-hvm hypervisor supports setting a password to

connect the the instances' VNC console, and has one common password

stored in a file.

This doesn't allow different passwords for different instances/groups of

instances, and makes it necessary to remember to copy the file around

the cluster when the password changes.

Proposed changes

++++++++++++++++

We'll change the VNC password file to a vnc_password_file hypervisor

parameter.  This way it can have a cluster default, but also a different

value for each instance. The VNC enabled hypervisors (xen and kvm) will

publish all the password files in use through the cluster so that a

redistribute-config will ship them to all nodes (see the Redistribute

Config proposed changes above).

The current VNC_PASSWORD_FILE constant will be removed, but its value

will be used as the default HV_VNC_PASSWORD_FILE value, thus retaining

backwards compatibility with 2.0.

The code to export the list of VNC password files from the hypervisors

to RedistributeConfig will be shared between the KVM and xen-hvm

hypervisors.

Disk/Net parameters

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

Current State and shortcomings

++++++++++++++++++++++++++++++

Currently disks and network interfaces have a few tweakable options and

all the rest is left to a default we chose. We're finding that we need

more and more to tweak some of these parameters, for example to disable

barriers for DRBD devices, or allow striping for the LVM volumes.

Moreover for many of these parameters it will be nice to have

cluster-wide defaults, and then be able to change them per

disk/interface.

Proposed changes

++++++++++++++++

We will add new cluster level diskparams and netparams, which will

contain all the tweakable parameters. All values which have a sensible

cluster-wide default will go into this new structure while parameters

which have unique values will not.

Example of network parameters:

  - mode: bridge/route

  - link: for mode "bridge" the bridge to connect to, for mode route it

    can contain the routing table, or the destination interface

Example of disk parameters:

  - stripe: lvm stripes

  - stripe_size: lvm stripe size

  - meta_flushes: drbd, enable/disable metadata "barriers"

  - data_flushes: drbd, enable/disable data "barriers"

Some parameters are bound to be disk-type specific (drbd, vs lvm, vs

files) or hypervisor specific (nic models for example), but for now they

will all live in the same structure. Each component is supposed to

validate only the parameters it knows about, and ganeti itself will make

sure that no "globally unknown" parameters are added, and that no

parameters have overridden meanings for different components.

The parameters will be kept, as for the BEPARAMS into a "default"

category, which will allow us to expand on by creating instance

"classes" in the future.  Instance classes is not a feature we plan

implementing in 2.1, though.

Global hypervisor parameters

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

Current State and shortcomings

++++++++++++++++++++++++++++++

Currently all hypervisor parameters are modifiable both globally

(cluster level) and at instance level. However, there is no other

framework to held hypervisor-specific parameters, so if we want to add

a new class of hypervisor parameters that only makes sense on a global

level, we have to change the hvparams framework.

Proposed changes

++++++++++++++++

We add a new (global, not per-hypervisor) list of parameters which are

not changeable on a per-instance level. The create, modify and query

instance operations are changed to not allow/show these parameters.

Furthermore, to allow transition of parameters to the global list, and

to allow cleanup of inadverdently-customised parameters, the

``UpgradeConfig()`` method of instances will drop any such parameters

from their list of hvparams, such that a restart of the master daemon

is all that is needed for cleaning these up.

Also, the framework is simple enough that if we need to replicate it

at beparams level we can do so easily.

Non bridged instances support

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

Current State and shortcomings

++++++++++++++++++++++++++++++

Currently each instance NIC must be connected to a bridge, and if the

bridge is not specified the default cluster one is used. This makes it

impossible to use the vif-route xen network scripts, or other

alternative mechanisms that don't need a bridge to work.

Proposed changes

++++++++++++++++

The new "mode" network parameter will distinguish between bridged

interfaces and routed ones.

When mode is "bridge" the "link" parameter will contain the bridge the

instance should be connected to, effectively making things as today. The

value has been migrated from a nic field to a parameter to allow for an

easier manipulation of the cluster default.

When mode is "route" the ip field of the interface will become

mandatory, to allow for a route to be set. In the future we may want

also to accept multiple IPs or IP/mask values for this purpose. We will

evaluate possible meanings of the link parameter to signify a routing

table to be used, which would allow for insulation between instance

groups (as today happens for different bridges).

For now we won't add a parameter to specify which network script gets

called for which instance, so in a mixed cluster the network script must

be able to handle both cases. The default kvm vif script will be changed

to do so. (Xen doesn't have a ganeti provided script, so nothing will be

done for that hypervisor)

Introducing persistent UUIDs

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

Current state and shortcomings

++++++++++++++++++++++++++++++

Some objects in the Ganeti configurations are tracked by their name

while also supporting renames. This creates an extra difficulty,

because neither Ganeti nor external management tools can then track

the actual entity, and due to the name change it behaves like a new

one.

Proposed changes part 1

+++++++++++++++++++++++

We will change Ganeti to use UUIDs for entity tracking, but in a

staggered way. In 2.1, we will simply add an “uuid” attribute to each

of the instances, nodes and cluster itself. This will be reported on

instance creation for nodes, and on node adds for the nodes. It will

be of course avaiblable for querying via the OpQueryNodes/Instance and

cluster information, and via RAPI as well.

Note that Ganeti will not provide any way to change this attribute.

Upgrading from Ganeti 2.0 will automatically add an ‘uuid’ attribute

to all entities missing it.

Proposed changes part 2

+++++++++++++++++++++++

In the next release (e.g. 2.2), the tracking of objects will change

from the name to the UUID internally, and externally Ganeti will

accept both forms of identification; e.g. an RAPI call would be made

either against ``/2/instances/foo.bar`` or against

``/2/instances/bb3b2e42…``. Since an FQDN must have at least a dot,

and dots are not valid characters in UUIDs, we will not have namespace

issues.

Another change here is that node identification (during cluster

operations/queries like master startup, “am I the master?” and

similar) could be done via UUIDs which is more stable than the current

hostname-based scheme.

Internal tracking refers to the way the configuration is stored; a

DRBD disk of an instance refers to the node name (so that IPs can be

changed easily), but this is still a problem for name changes; thus

these will be changed to point to the node UUID to ease renames.

The advantages of this change (after the second round of changes), is

that node rename becomes trivial, whereas today node rename would

require a complete lock of all instances.

Automated disk repairs infrastructure

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

Replacing defective disks in an automated fashion is quite difficult

with the current version of Ganeti. These changes will introduce

additional functionality and interfaces to simplify automating disk

replacements on a Ganeti node.

Fix node volume group

+++++++++++++++++++++

This is the most difficult addition, as it can lead to dataloss if it's

not properly safeguarded.

The operation must be done only when all the other nodes that have

instances in common with the target node are fine, i.e. this is the only

node with problems, and also we have to double-check that all instances

on this node have at least a good copy of the data.

This might mean that we have to enhance the GetMirrorStatus calls, and

introduce and a smarter version that can tell us more about the status

of an instance.

Stop allocation on a given PV

+++++++++++++++++++++++++++++

This is somewhat simple. First we need a "list PVs" opcode (and its

associated logical unit) and then a set PV status opcode/LU. These in

combination should allow both checking and changing the disk/PV status.

Instance disk status

++++++++++++++++++++

This new opcode or opcode change must list the instance-disk-index and

node combinations of the instance together with their status. This will

allow determining what part of the instance is broken (if any).

Repair instance

+++++++++++++++

This new opcode/LU/RAPI call will run ``replace-disks -p`` as needed, in

order to fix the instance status. It only affects primary instances;

secondaries can just be moved away.

Migrate node

++++++++++++

This new opcode/LU/RAPI call will take over the current ``gnt-node

migrate`` code and run migrate for all instances on the node.

Evacuate node

++++++++++++++

This new opcode/LU/RAPI call will take over the current ``gnt-node

evacuate`` code and run replace-secondary with an iallocator script for

all instances on the node.

User-id pool

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

In order to allow running different processes under unique user-ids

on a node, we introduce the user-id pool concept.

The user-id pool is a cluster-wide configuration parameter.

It is a list of user-ids and/or user-id ranges that are reserved

for running Ganeti processes (including KVM instances).

The code guarantees that on a given node a given user-id is only

handed out if there is no other process running with that user-id.

Please note, that this can only be guaranteed if all processes in

the system - that run under a user-id belonging to the pool - are

started by reserving a user-id first. That can be accomplished

either by using the RequestUnusedUid() function to get an unused

user-id or by implementing the same locking mechanism.

Implementation

++++++++++++++

The functions that are specific to the user-id pool feature are located

in a separate module: ``lib/uidpool.py``.

Storage

^^^^^^^

The user-id pool is a single cluster parameter. It is stored in the

*Cluster* object under the ``uid_pool`` name as a list of integer

tuples. These tuples represent the boundaries of user-id ranges.

For single user-ids, the boundaries are equal.

The internal user-id pool representation is converted into a

string: a newline separated list of user-ids or user-id ranges.

This string representation is distributed to all the nodes via the

*ssconf* mechanism. This means that the user-id pool can be

accessed in a read-only way on any node without consulting the master

node or master candidate nodes.

Initial value

^^^^^^^^^^^^^

The value of the user-id pool cluster parameter can be initialized

at cluster initialization time using the

``gnt-cluster init --uid-pool <uid-pool definition> ...``

command.

As there is no sensible default value for the user-id pool parameter,

it is initialized to an empty list if no ``--uid-pool`` option is

supplied at cluster init time.

If the user-id pool is empty, the user-id pool feature is considered

to be disabled.

Manipulation

^^^^^^^^^^^^

The user-id pool cluster parameter can be modified from the

command-line with the following commands:

- ``gnt-cluster modify --uid-pool <uid-pool definition>``

- ``gnt-cluster modify --add-uids <uid-pool definition>``

- ``gnt-cluster modify --remove-uids <uid-pool definition>``

The ``--uid-pool`` option overwrites the current setting with the

supplied ``<uid-pool definition>``, while

``--add-uids``/``--remove-uids`` adds/removes the listed uids

or uid-ranges from the pool.

The ``<uid-pool definition>`` should be a comma-separated list of

user-ids or user-id ranges. A range should be defined by a lower and

a higher boundary. The boundaries should be separated with a dash.

The boundaries are inclusive.

The ``<uid-pool definition>`` is parsed into the internal

representation, sanity-checked and stored in the ``uid_pool``

attribute of the *Cluster* object.

It is also immediately converted into a string (formatted in the

input format) and distributed to all nodes via the *ssconf* mechanism.

Inspection

^^^^^^^^^^

The current value of the user-id pool cluster parameter is printed

by the ``gnt-cluster info`` command.

The output format is accepted by the ``gnt-cluster modify --uid-pool``

command.

Locking

^^^^^^^

The ``uidpool.py`` module provides a function (``RequestUnusedUid``)

for requesting an unused user-id from the pool.

This will try to find a random user-id that is not currently in use.

The algorithm is the following:

1) Randomize the list of user-ids in the user-id pool

2) Iterate over this randomized UID list

3) Create a lock file (it doesn't matter if it already exists)

4) Acquire an exclusive POSIX lock on the file, to provide mutual

   exclusion for the following non-atomic operations

5) Check if there is a process in the system with the given UID

6) If there isn't, return the UID, otherwise unlock the file and

   continue the iteration over the user-ids

The user can than start a new process with this user-id.

Once a process is successfully started, the exclusive POSIX lock can

be released, but the lock file will remain in the filesystem.

The presence of such a lock file means that the given user-id is most

probably in use. The lack of a uid lock file does not guarantee that

there are no processes with that user-id.

After acquiring the exclusive POSIX lock, ``RequestUnusedUid``

always performs a check to see if there is a process running with the

given uid.

A user-id can be returned to the pool, by calling the

``ReleaseUid`` function. This will remove the corresponding lock file.

Note, that it doesn't check if there is any process still running

with that user-id. The removal of the lock file only means that there

are most probably no processes with the given user-id. This helps

in speeding up the process of finding a user-id that is guaranteed to

be unused.

There is a convenience function, called ``ExecWithUnusedUid`` that

wraps the execution of a function (or any callable) that requires a

unique user-id. ``ExecWithUnusedUid`` takes care of requesting an

unused user-id and unlocking the lock file. It also automatically

returns the user-id to the pool if the callable raises an exception.

Code examples

+++++++++++++

Requesting a user-id from the pool:

::

  from ganeti import ssconf

  from ganeti import uidpool

  # Get list of all user-ids in the uid-pool from ssconf

  ss = ssconf.SimpleStore()

  uid_pool = uidpool.ParseUidPool(ss.GetUidPool(), separator="\n")

  all_uids = set(uidpool.ExpandUidPool(uid_pool))

  uid = uidpool.RequestUnusedUid(all_uids)

  try:

    <start a process with the UID>

    # Once the process is started, we can release the file lock

    uid.Unlock()

  except ..., err:

    # Return the UID to the pool

    uidpool.ReleaseUid(uid)

Releasing a user-id:

::

  from ganeti import uidpool

  uid = <get the UID the process is running under>

  <stop the process>

  uidpool.ReleaseUid(uid)

External interface changes

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

OS API

~~~~~~

The OS API of Ganeti 2.0 has been built with extensibility in mind.

Since we pass everything as environment variables it's a lot easier to

send new information to the OSes without breaking retrocompatibility.

This section of the design outlines the proposed extensions to the API

and their implementation.

API Version Compatibility Handling

++++++++++++++++++++++++++++++++++

In 2.1 there will be a new OS API version (eg. 15), which should be

mostly compatible with api 10, except for some new added variables.

Since it's easy not to pass some variables we'll be able to handle

Ganeti 2.0 OSes by just filtering out the newly added piece of

information. We will still encourage OSes to declare support for the new

API after checking that the new variables don't provide any conflict for

them, and we will drop api 10 support after ganeti 2.1 has released.

New Environment variables

+++++++++++++++++++++++++

Some variables have never been added to the OS api but would definitely

be useful for the OSes. We plan to add an INSTANCE_HYPERVISOR variable

to allow the OS to make changes relevant to the virtualization the

instance is going to use. Since this field is immutable for each

instance, the os can tight the install without caring of making sure the

instance can run under any virtualization technology.

We also want the OS to know the particular hypervisor parameters, to be

able to customize the install even more.  Since the parameters can

change, though, we will pass them only as an "FYI": if an OS ties some

instance functionality to the value of a particular hypervisor parameter

manual changes or a reinstall may be needed to adapt the instance to the

new environment. This is not a regression as of today, because even if

the OSes are left blind about this information, sometimes they still

need to make compromises and cannot satisfy all possible parameter

values.

OS Variants

+++++++++++

Currently we are assisting to some degree of "os proliferation" just to

change a simple installation behavior. This means that the same OS gets

installed on the cluster multiple times, with different names, to

customize just one installation behavior. Usually such OSes try to share

as much as possible through symlinks, but this still causes

complications on the user side, especially when multiple parameters must

be cross-matched.

For example today if you want to install debian etch, lenny or squeeze

you probably need to install the debootstrap OS multiple times, changing

its configuration file, and calling it debootstrap-etch,

debootstrap-lenny or debootstrap-squeeze. Furthermore if you have for

example a "server" and a "development" environment which installs

different packages/configuration files and must be available for all

installs you'll probably end  up with deboostrap-etch-server,

debootstrap-etch-dev, debootrap-lenny-server, debootstrap-lenny-dev,

etc. Crossing more than two parameters quickly becomes not manageable.

In order to avoid this we plan to make OSes more customizable, by

allowing each OS to declare a list of variants which can be used to

customize it. The variants list is mandatory and must be written, one

variant per line, in the new "variants.list" file inside the main os

dir. At least one supported variant must be supported. When choosing the

OS exactly one variant will have to be specified, and will be encoded in

the os name as <OS-name>+<variant>. As for today it will be possible to

change an instance's OS at creation or install time.

The 2.1 OS list will be the combination of each OS, plus its supported

variants. This will cause the name name proliferation to remain, but at

least the internal OS code will be simplified to just parsing the passed

variant, without the need for symlinks or code duplication.

Also we expect the OSes to declare only "interesting" variants, but to

accept some non-declared ones which a user will be able to pass in by

overriding the checks ganeti does. This will be useful for allowing some

variations to be used without polluting the OS list (per-OS

documentation should list all supported variants). If a variant which is

not internally supported is forced through, the OS scripts should abort.

In the future (post 2.1) we may want to move to full fledged parameters

all orthogonal to each other (for example "architecture" (i386, amd64),

"suite" (lenny, squeeze, ...), etc). (As opposed to the variant, which

is a single parameter, and you need a different variant for all the set

of combinations you want to support).  In this case we envision the

variants to be moved inside of Ganeti and be associated with lists

parameter->values associations, which will then be passed to the OS.

IAllocator changes

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

Current State and shortcomings

++++++++++++++++++++++++++++++

The iallocator interface allows creation of instances without manually

specifying nodes, but instead by specifying plugins which will do the

required computations and produce a valid node list.

However, the interface is quite akward to use:

- one cannot set a 'default' iallocator script

- one cannot use it to easily test if allocation would succeed

- some new functionality, such as rebalancing clusters and calculating

  capacity estimates is needed

Proposed changes

++++++++++++++++

There are two area of improvements proposed:

- improving the use of the current interface

- extending the IAllocator API to cover more automation

Default iallocator names

^^^^^^^^^^^^^^^^^^^^^^^^

The cluster will hold, for each type of iallocator, a (possibly empty)

list of modules that will be used automatically.

If the list is empty, the behaviour will remain the same.

If the list has one entry, then ganeti will behave as if

'--iallocator' was specifyed on the command line. I.e. use this

allocator by default. If the user however passed nodes, those will be

used in preference.

If the list has multiple entries, they will be tried in order until

one gives a successful answer.

Dry-run allocation

^^^^^^^^^^^^^^^^^^

The create instance LU will get a new 'dry-run' option that will just

simulate the placement, and return the chosen node-lists after running

all the usual checks.

Cluster balancing

^^^^^^^^^^^^^^^^^

Instance add/removals/moves can create a situation where load on the

nodes is not spread equally. For this, a new iallocator mode will be

implemented called ``balance`` in which the plugin, given the current

cluster state, and a maximum number of operations, will need to

compute the instance relocations needed in order to achieve a "better"

(for whatever the script believes it's better) cluster.

Cluster capacity calculation

^^^^^^^^^^^^^^^^^^^^^^^^^^^^

In this mode, called ``capacity``, given an instance specification and

the current cluster state (similar to the ``allocate`` mode), the

plugin needs to return:

- how many instances can be allocated on the cluster with that

  specification

- on which nodes these will be allocated (in order)

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