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

Ganeti 2.2 design

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

This document describes the major changes in Ganeti 2.2 compared to

the 2.1 version.

The 2.2 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 2.1, in a timely fashion.

.. contents:: :depth: 4

Detailed design

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

As for 2.1 we divide the 2.2 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

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

Master Daemon Scaling improvements

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

Current state and shortcomings

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

Currently the Ganeti master daemon is based on four sets of threads:

- The main thread (1 thread) just accepts connections on the master

  socket

- The client worker pool (16 threads) handles those connections,

  one thread per connected socket, parses luxi requests, and sends data

  back to the clients

- The job queue worker pool (25 threads) executes the actual jobs

  submitted by the clients

- The rpc worker pool (10 threads) interacts with the nodes via

  http-based-rpc

This means that every masterd currently runs 52 threads to do its job.

Being able to reduce the number of thread sets would make the master's

architecture a lot simpler. Moreover having less threads can help

decrease lock contention, log pollution and memory usage.

Also, with the current architecture, masterd suffers from quite a few

scalability issues:

Core daemon connection handling

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

Since the 16 client worker threads handle one connection each, it's very

easy to exhaust them, by just connecting to masterd 16 times and not

sending any data. While we could perhaps make those pools resizable,

increasing the number of threads won't help with lock contention nor

with better handling long running operations making sure the client is

informed that everything is proceeding, and doesn't need to time out.

Wait for job change

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

The REQ_WAIT_FOR_JOB_CHANGE luxi operation makes the relevant client

thread block on its job for a relative long time. This is another easy

way to exhaust the 16 client threads, and a place where clients often

time out, moreover this operation is negative for the job queue lock

contention (see below).

Job Queue lock

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

The job queue lock is quite heavily contended, and certain easily

reproducible workloads show that's it's very easy to put masterd in

trouble: for example running ~15 background instance reinstall jobs,

results in a master daemon that, even without having finished the

client worker threads, can't answer simple job list requests, or

submit more jobs.

Currently the job queue lock is an exclusive non-fair lock insulating

the following job queue methods (called by the client workers).

  - AddNode

  - RemoveNode

  - SubmitJob

  - SubmitManyJobs

  - WaitForJobChanges

  - CancelJob

  - ArchiveJob

  - AutoArchiveJobs

  - QueryJobs

  - Shutdown

Moreover the job queue lock is acquired outside of the job queue in two

other classes:

  - jqueue._JobQueueWorker (in RunTask) before executing the opcode, after

    finishing its executing and when handling an exception.

  - jqueue._OpExecCallbacks (in NotifyStart and Feedback) when the

    processor (mcpu.Processor) is about to start working on the opcode

    (after acquiring the necessary locks) and when any data is sent back

    via the feedback function.

Of those the major critical points are:

  - Submit[Many]Job, QueryJobs, WaitForJobChanges, which can easily slow

    down and block client threads up to making the respective clients

    time out.

  - The code paths in NotifyStart, Feedback, and RunTask, which slow

    down job processing between clients and otherwise non-related jobs.

To increase the pain:

  - WaitForJobChanges is a bad offender because it's implemented with a

    notified condition which awakes waiting threads, who then try to

    acquire the global lock again

  - Many should-be-fast code paths are slowed down by replicating the

    change to remote nodes, and thus waiting, with the lock held, on

    remote rpcs to complete (starting, finishing, and submitting jobs)

Proposed changes

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

In order to be able to interact with the master daemon even when it's

under heavy load, and  to make it simpler to add core functionality

(such as an asynchronous rpc client) we propose three subsequent levels

of changes to the master core architecture.

After making this change we'll be able to re-evaluate the size of our

thread pool, if we see that we can make most threads in the client

worker pool always idle. In the future we should also investigate making

the rpc client asynchronous as well, so that we can make masterd a lot

smaller in number of threads, and memory size, and thus also easier to

understand, debug, and scale.

Connection handling

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

We'll move the main thread of ganeti-masterd to asyncore, so that it can

share the mainloop code with all other Ganeti daemons. Then all luxi

clients will be asyncore clients, and I/O to/from them will be handled

by the master thread asynchronously. Data will be read from the client

sockets as it becomes available, and kept in a buffer, then when a

complete message is found, it's passed to a client worker thread for

parsing and processing. The client worker thread is responsible for

serializing the reply, which can then be sent asynchronously by the main

thread on the socket.

Wait for job change

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

The REQ_WAIT_FOR_JOB_CHANGE luxi request is changed to be

subscription-based, so that the executing thread doesn't have to be

waiting for the changes to arrive. Threads producing messages (job queue

executors) will make sure that when there is a change another thread is

awaken and delivers it to the waiting clients. This can be either a

dedicated "wait for job changes" thread or pool, or one of the client

workers, depending on what's easier to implement. In either case the

main asyncore thread will only be involved in pushing of the actual

data, and not in fetching/serializing it.

Other features to look at, when implementing this code are:

  - Possibility not to need the job lock to know which updates to push:

    if the thread producing the data pushed a copy of the update for the

    waiting clients, the thread sending it won't need to acquire the

    lock again to fetch the actual data.

  - Possibility to signal clients about to time out, when no update has

    been received, not to despair and to keep waiting (luxi level

    keepalive).

  - Possibility to defer updates if they are too frequent, providing

    them at a maximum rate (lower priority).

Job Queue lock

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

In order to decrease the job queue lock contention, we will change the

code paths in the following ways, initially:

  - A per-job lock will be introduced. All operations affecting only one

    job (for example feedback, starting/finishing notifications,

    subscribing to or watching a job) will only require the job lock.

    This should be a leaf lock, but if a situation arises in which it

    must be acquired together with the global job queue lock the global

    one must always be acquired last (for the global section).

  - The locks will be converted to a sharedlock. Any read-only operation

    will be able to proceed in parallel.

  - During remote update (which happens already per-job) we'll drop the

    job lock level to shared mode, so that activities reading the lock

    (for example job change notifications or QueryJobs calls) will be

    able to proceed in parallel.

  - The wait for job changes improvements proposed above will be

    implemented.

In the future other improvements may include splitting off some of the

work (eg replication of a job to remote nodes) to a separate thread pool

or asynchronous thread, not tied with the code path for answering client

requests or the one executing the "real" work. This can be discussed

again after we used the more granular job queue in production and tested

its benefits.

Remote procedure call timeouts

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

Current state and shortcomings

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

The current RPC protocol used by Ganeti is based on HTTP. Every request

consists of an HTTP PUT request (e.g. ``PUT /hooks_runner HTTP/1.0``)

and doesn't return until the function called has returned. Parameters

and return values are encoded using JSON.

On the server side, ``ganeti-noded`` handles every incoming connection

in a separate process by forking just after accepting the connection.

This process exits after sending the response.

There is one major problem with this design: Timeouts can not be used on

a per-request basis. Neither client or server know how long it will

take. Even if we might be able to group requests into different

categories (e.g. fast and slow), this is not reliable.

If a node has an issue or the network connection fails while a request

is being handled, the master daemon can wait for a long time for the

connection to time out (e.g. due to the operating system's underlying

TCP keep-alive packets or timeouts). While the settings for keep-alive

packets can be changed using Linux-specific socket options, we prefer to

use application-level timeouts because these cover both machine down and

unresponsive node daemon cases.

Proposed changes

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

RPC glossary

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

Function call ID

  Unique identifier returned by ``ganeti-noded`` after invoking a

  function.

Function process

  Process started by ``ganeti-noded`` to call actual (backend) function.

Protocol

^^^^^^^^

Initially we chose HTTP as our RPC protocol because there were existing

libraries, which, unfortunately, turned out to miss important features

(such as SSL certificate authentication) and we had to write our own.

This proposal can easily be implemented using HTTP, though it would

likely be more efficient and less complicated to use the LUXI protocol

already used to communicate between client tools and the Ganeti master

daemon. Switching to another protocol can occur at a later point. This

proposal should be implemented using HTTP as its underlying protocol.

The LUXI protocol currently contains two functions, ``WaitForJobChange``

and ``AutoArchiveJobs``, which can take a longer time. They both support

a parameter to specify the timeout. This timeout is usually chosen as

roughly half of the socket timeout, guaranteeing a response before the

socket times out. After the specified amount of time,

``AutoArchiveJobs`` returns and reports the number of archived jobs.

``WaitForJobChange`` returns and reports a timeout. In both cases, the

functions can be called again.

A similar model can be used for the inter-node RPC protocol. In some

sense, the node daemon will implement a light variant of *"node daemon

jobs"*. When the function call is sent, it specifies an initial timeout.

If the function didn't finish within this timeout, a response is sent

with a unique identifier, the function call ID. The client can then

choose to wait for the function to finish again with a timeout.

Inter-node RPC calls would no longer be blocking indefinitely and there

would be an implicit ping-mechanism.

Request handling

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

To support the protocol changes described above, the way the node daemon

handles request will have to change. Instead of forking and handling

every connection in a separate process, there should be one child

process per function call and the master process will handle the

communication with clients and the function processes using asynchronous

I/O.

Function processes communicate with the parent process via stdio and

possibly their exit status. Every function process has a unique

identifier, though it shouldn't be the process ID only (PIDs can be

recycled and are prone to race conditions for this use case). The

proposed format is ``${ppid}:${cpid}:${time}:${random}``, where ``ppid``

is the ``ganeti-noded`` PID, ``cpid`` the child's PID, ``time`` the

current Unix timestamp with decimal places and ``random`` at least 16

random bits.

The following operations will be supported:

``StartFunction(fn_name, fn_args, timeout)``

  Starts a function specified by ``fn_name`` with arguments in

  ``fn_args`` and waits up to ``timeout`` seconds for the function

  to finish. Fire-and-forget calls can be made by specifying a timeout

  of 0 seconds (e.g. for powercycling the node). Returns three values:

  function call ID (if not finished), whether function finished (or

  timeout) and the function's return value.

``WaitForFunction(fnc_id, timeout)``

  Waits up to ``timeout`` seconds for function call to finish. Return

  value same as ``StartFunction``.

In the future, ``StartFunction`` could support an additional parameter

to specify after how long the function process should be aborted.

Simplified timing diagram::

  Master daemon        Node daemon                      Function process

   |

  Call function

  (timeout 10s) -----> Parse request and fork for ----> Start function

                       calling actual function, then     |

                       wait up to 10s for function to    |

                       finish                            |

                        |                                |

                       ...                              ...

                        |                                |

  Examine return <----  |                                |

  value and wait                                         |

  again -------------> Wait another 10s for function     |

                        |                                |

                       ...                              ...

                        |                                |

  Examine return <----  |                                |

  value and wait                                         |

  again -------------> Wait another 10s for function     |

                        |                                |

                       ...                              ...

                        |                                |

                        |                               Function ends,

                       Get return value and forward <-- process exits

  Process return <---- it to caller

  value and continue

   |

.. TODO: Convert diagram above to graphviz/dot graphic

On process termination (e.g. after having been sent a ``SIGTERM`` or

``SIGINT`` signal), ``ganeti-noded`` should send ``SIGTERM`` to all

function processes and wait for all of them to terminate.

Inter-cluster instance moves

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

Current state and shortcomings

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

With the current design of Ganeti, moving whole instances between

different clusters involves a lot of manual work. There are several ways

to move instances, one of them being to export the instance, manually

copying all data to the new cluster before importing it again. Manual

changes to the instances configuration, such as the IP address, may be

necessary in the new environment. The goal is to improve and automate

this process in Ganeti 2.2.

Proposed changes

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

Authorization, Authentication and Security

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

Until now, each Ganeti cluster was a self-contained entity and wouldn't

talk to other Ganeti clusters. Nodes within clusters only had to trust

the other nodes in the same cluster and the network used for replication

was trusted, too (hence the ability the use a separate, local network

for replication).

For inter-cluster instance transfers this model must be weakened. Nodes

in one cluster will have to talk to nodes in other clusters, sometimes

in other locations and, very important, via untrusted network

connections.

Various option have been considered for securing and authenticating the

data transfer from one machine to another. To reduce the risk of

accidentally overwriting data due to software bugs, authenticating the

arriving data was considered critical. Eventually we decided to use

socat's OpenSSL options (``OPENSSL:``, ``OPENSSL-LISTEN:`` et al), which

provide us with encryption, authentication and authorization when used

with separate keys and certificates.

Combinations of OpenSSH, GnuPG and Netcat were deemed too complex to set

up from within Ganeti. Any solution involving OpenSSH would require a

dedicated user with a home directory and likely automated modifications

to the user's ``$HOME/.ssh/authorized_keys`` file. When using Netcat,

GnuPG or another encryption method would be necessary to transfer the

data over an untrusted network. socat combines both in one program and

is already a dependency.

Each of the two clusters will have to generate an RSA key. The public

parts are exchanged between the clusters by a third party, such as an

administrator or a system interacting with Ganeti via the remote API

("third party" from here on). After receiving each other's public key,

the clusters can start talking to each other.

All encrypted connections must be verified on both sides. Neither side

may accept unverified certificates. The generated certificate should

only be valid for the time necessary to move the instance.

For additional protection of the instance data, the two clusters can

verify the certificates and destination information exchanged via the

third party by checking an HMAC signature using a key shared among the

involved clusters. By default this secret key will be a random string

unique to the cluster, generated by running SHA1 over 20 bytes read from

``/dev/urandom`` and the administrator must synchronize the secrets

between clusters before instances can be moved. If the third party does

not know the secret, it can't forge the certificates or redirect the

data. Unless disabled by a new cluster parameter, verifying the HMAC

signatures must be mandatory. The HMAC signature for X509 certificates

will be prepended to the certificate similar to an :rfc:`822` header and

only covers the certificate (from ``-----BEGIN CERTIFICATE-----`` to

``-----END CERTIFICATE-----``). The header name will be

``X-Ganeti-Signature`` and its value will have the format

``$salt/$hash`` (salt and hash separated by slash). The salt may only

contain characters in the range ``[a-zA-Z0-9]``.

On the web, the destination cluster would be equivalent to an HTTPS

server requiring verifiable client certificates. The browser would be

equivalent to the source cluster and must verify the server's

certificate while providing a client certificate to the server.

Copying data

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

To simplify the implementation, we decided to operate at a block-device

level only, allowing us to easily support non-DRBD instance moves.

Intra-cluster instance moves will re-use the existing export and import

scripts supplied by instance OS definitions. Unlike simply copying the

raw data, this allows to use filesystem-specific utilities to dump only

used parts of the disk and to exclude certain disks from the move.

Compression should be used to further reduce the amount of data

transferred.

The export scripts writes all data to stdout and the import script reads

it from stdin again. To avoid copying data and reduce disk space

consumption, everything is read from the disk and sent over the network

directly, where it'll be written to the new block device directly again.

Workflow

^^^^^^^^

#. Third party tells source cluster to shut down instance, asks for the

   instance specification and for the public part of an encryption key

   - Instance information can already be retrieved using an existing API

     (``OpQueryInstanceData``).

   - An RSA encryption key and a corresponding self-signed X509

     certificate is generated using the "openssl" command. This key will

     be used to encrypt the data sent to the destination cluster.

     - Private keys never leave the cluster.

     - The public part (the X509 certificate) is signed using HMAC with

       salting and a secret shared between Ganeti clusters.

#. Third party tells destination cluster to create an instance with the

   same specifications as on source cluster and to prepare for an

   instance move with the key received from the source cluster and

   receives the public part of the destination's encryption key

   - The current API to create instances (``OpCreateInstance``) will be

     extended to support an import from a remote cluster.

   - A valid, unexpired X509 certificate signed with the destination

     cluster's secret will be required. By verifying the signature, we

     know the third party didn't modify the certificate.

     - The private keys never leave their cluster, hence the third party

       can not decrypt or intercept the instance's data by modifying the

       IP address or port sent by the destination cluster.

   - The destination cluster generates another key and certificate,

     signs and sends it to the third party, who will have to pass it to

     the API for exporting an instance (``OpExportInstance``). This

     certificate is used to ensure we're sending the disk data to the

     correct destination cluster.

   - Once a disk can be imported, the API sends the destination

     information (IP address and TCP port) together with an HMAC

     signature to the third party.

#. Third party hands public part of the destination's encryption key

   together with all necessary information to source cluster and tells

   it to start the move

   - The existing API for exporting instances (``OpExportInstance``)

     will be extended to export instances to remote clusters.

#. Source cluster connects to destination cluster for each disk and

   transfers its data using the instance OS definition's export and

   import scripts

   - Before starting, the source cluster must verify the HMAC signature

     of the certificate and destination information (IP address and TCP

     port).

   - When connecting to the remote machine, strong certificate checks

     must be employed.

#. Due to the asynchronous nature of the whole process, the destination

   cluster checks whether all disks have been transferred every time

   after transferring a single disk; if so, it destroys the encryption

   key

#. After sending all disks, the source cluster destroys its key

#. Destination cluster runs OS definition's rename script to adjust

   instance settings if needed (e.g. IP address)

#. Destination cluster starts the instance if requested at the beginning

   by the third party

#. Source cluster removes the instance if requested

Instance move in pseudo code

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

.. highlight:: python

The following pseudo code describes a script moving instances between

clusters and what happens on both clusters.

#. Script is started, gets the instance name and destination cluster::

    (instance_name, dest_cluster_name) = sys.argv[1:]

    # Get destination cluster object

    dest_cluster = db.FindCluster(dest_cluster_name)

    # Use database to find source cluster

    src_cluster = db.FindClusterByInstance(instance_name)

#. Script tells source cluster to stop instance::

    # Stop instance

    src_cluster.StopInstance(instance_name)

    # Get instance specification (memory, disk, etc.)

    inst_spec = src_cluster.GetInstanceInfo(instance_name)

    (src_key_name, src_cert) = src_cluster.CreateX509Certificate()

#. ``CreateX509Certificate`` on source cluster::

    key_file = mkstemp()

    cert_file = "%s.cert" % key_file

    RunCmd(["/usr/bin/openssl", "req", "-new",

             "-newkey", "rsa:1024", "-days", "1",

             "-nodes", "-x509", "-batch",

             "-keyout", key_file, "-out", cert_file])

    plain_cert = utils.ReadFile(cert_file)

    # HMAC sign using secret key, this adds a "X-Ganeti-Signature"

    # header to the beginning of the certificate

    signed_cert = utils.SignX509Certificate(plain_cert,

      utils.ReadFile(constants.X509_SIGNKEY_FILE))

    # The certificate now looks like the following:

    #

    #   X-Ganeti-Signature: $1234$28676f0516c6ab68062b[…]

    #   -----BEGIN CERTIFICATE-----

    #   MIICsDCCAhmgAwIBAgI[…]

    #   -----END CERTIFICATE-----

    # Return name of key file and signed certificate in PEM format

    return (os.path.basename(key_file), signed_cert)

#. Script creates instance on destination cluster and waits for move to

   finish::

    dest_cluster.CreateInstance(mode=constants.REMOTE_IMPORT,

                                spec=inst_spec,

                                source_cert=src_cert)

    # Wait until destination cluster gives us its certificate

    dest_cert = None

    disk_info = []

    while not (dest_cert and len(disk_info) < len(inst_spec.disks)):

      tmp = dest_cluster.WaitOutput()

      if tmp is Certificate:

        dest_cert = tmp

      elif tmp is DiskInfo:

        # DiskInfo contains destination address and port

        disk_info[tmp.index] = tmp

    # Tell source cluster to export disks

    for disk in disk_info:

      src_cluster.ExportDisk(instance_name, disk=disk,

                             key_name=src_key_name,

                             dest_cert=dest_cert)

    print ("Instance %s sucessfully moved to %s" %

           (instance_name, dest_cluster.name))

#. ``CreateInstance`` on destination cluster::

    # …

    if mode == constants.REMOTE_IMPORT:

      # Make sure certificate was not modified since it was generated by

      # source cluster (which must use the same secret)

      if (not utils.VerifySignedX509Cert(source_cert,

            utils.ReadFile(constants.X509_SIGNKEY_FILE))):

        raise Error("Certificate not signed with this cluster's secret")

      if utils.CheckExpiredX509Cert(source_cert):

        raise Error("X509 certificate is expired")

      source_cert_file = utils.WriteTempFile(source_cert)

      # See above for X509 certificate generation and signing

      (key_name, signed_cert) = CreateSignedX509Certificate()

      SendToClient("x509-cert", signed_cert)

      for disk in instance.disks:

        # Start socat

        RunCmd(("socat"

                " OPENSSL-LISTEN:%s,…,key=%s,cert=%s,cafile=%s,verify=1"

                " stdout > /dev/disk…") %

               port, GetRsaKeyPath(key_name, private=True),

               GetRsaKeyPath(key_name, private=False), src_cert_file)

        SendToClient("send-disk-to", disk, ip_address, port)

      DestroyX509Cert(key_name)

      RunRenameScript(instance_name)

#. ``ExportDisk`` on source cluster::

    # Make sure certificate was not modified since it was generated by

    # destination cluster (which must use the same secret)

    if (not utils.VerifySignedX509Cert(cert_pem,

          utils.ReadFile(constants.X509_SIGNKEY_FILE))):

      raise Error("Certificate not signed with this cluster's secret")

    if utils.CheckExpiredX509Cert(cert_pem):

      raise Error("X509 certificate is expired")

    dest_cert_file = utils.WriteTempFile(cert_pem)

    # Start socat

    RunCmd(("socat stdin"

            " OPENSSL:%s:%s,…,key=%s,cert=%s,cafile=%s,verify=1"

            " < /dev/disk…") %

           disk.host, disk.port,

           GetRsaKeyPath(key_name, private=True),

           GetRsaKeyPath(key_name, private=False), dest_cert_file)

    if instance.all_disks_done:

      DestroyX509Cert(key_name)

.. highlight:: text

Miscellaneous notes

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

- A very similar system could also be used for instance exports within

  the same cluster. Currently OpenSSH is being used, but could be

  replaced by socat and SSL/TLS.

- During the design of intra-cluster instance moves we also discussed

  encrypting instance exports using GnuPG.

- While most instances should have exactly the same configuration as

  on the source cluster, setting them up with a different disk layout

  might be helpful in some use-cases.

- A cleanup operation, similar to the one available for failed instance

  migrations, should be provided.

- ``ganeti-watcher`` should remove instances pending a move from another

  cluster after a certain amount of time. This takes care of failures

  somewhere in the process.

- RSA keys can be generated using the existing

  ``bootstrap.GenerateSelfSignedSslCert`` function, though it might be

  useful to not write both parts into a single file, requiring small

  changes to the function. The public part always starts with

  ``-----BEGIN CERTIFICATE-----`` and ends with ``-----END

  CERTIFICATE-----``.

- The source and destination cluster might be different when it comes

  to available hypervisors, kernels, etc. The destination cluster should

  refuse to accept an instance move if it can't fulfill an instance's

  requirements.

Privilege separation

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

Current state and shortcomings

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

All Ganeti daemons are run under the user root. This is not ideal from a

security perspective as for possible exploitation of any daemon the user

has full access to the system.

In order to overcome this situation we'll allow Ganeti to run its daemon

under different users and a dedicated group. This also will allow some

side effects, like letting the user run some ``gnt-*`` commands if one

is in the same group.

Implementation

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

For Ganeti 2.2 the implementation will be focused on a the RAPI daemon

only. This involves changes to ``daemons.py`` so it's possible to drop

privileges on daemonize the process. Though, this will be a short term

solution which will be replaced by a privilege drop already on daemon

startup in Ganeti 2.3.

It also needs changes in the master daemon to create the socket with new

permissions/owners to allow RAPI access. There will be no other

permission/owner changes in the file structure as the RAPI daemon is

started with root permission. In that time it will read all needed files

and then drop privileges before contacting the master daemon.

Feature changes

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

KVM Security

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

Current state and shortcomings

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

Currently all kvm processes run as root. Taking ownership of the

hypervisor process, from inside a virtual machine, would mean a full

compromise of the whole Ganeti cluster, knowledge of all Ganeti

authentication secrets, full access to all running instances, and the

option of subverting other basic services on the cluster (eg: ssh).

Proposed changes

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

We would like to decrease the surface of attack available if an

hypervisor is compromised. We can do so adding different features to

Ganeti, which will allow restricting the broken hypervisor

possibilities, in the absence of a local privilege escalation attack, to

subvert the node.

Dropping privileges in kvm to a single user (easy)

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

By passing the ``-runas`` option to kvm, we can make it drop privileges.

The user can be chosen by an hypervisor parameter, so that each instance

can have its own user, but by default they will all run under the same

one. It should be very easy to implement, and can easily be backported

to 2.1.X.

This mode protects the Ganeti cluster from a subverted hypervisor, but

doesn't protect the instances between each other, unless care is taken

to specify a different user for each. This would prevent the worst

attacks, including:

- logging in to other nodes

- administering the Ganeti cluster

- subverting other services

But the following would remain an option:

- terminate other VMs (but not start them again, as that requires root

  privileges to set up networking) (unless different users are used)

- trace other VMs, and probably subvert them and access their data

  (unless different users are used)

- send network traffic from the node

- read unprotected data on the node filesystem

Running kvm in a chroot (slightly harder)

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

By passing the ``-chroot`` option to kvm, we can restrict the kvm

process in its own (possibly empty) root directory. We need to set this

area up so that the instance disks and control sockets are accessible,

so it would require slightly more work at the Ganeti level.

Breaking out in a chroot would mean:

- a lot less options to find a local privilege escalation vector

- the impossibility to write local data, if the chroot is set up

  correctly

- the impossibility to read filesystem data on the host

It would still be possible though to:

- terminate other VMs

- trace other VMs, and possibly subvert them (if a tracer can be

  installed in the chroot)

- send network traffic from the node

Running kvm with a pool of users (slightly harder)

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

If rather than passing a single user as an hypervisor parameter, we have

a pool of useable ones, we can dynamically choose a free one to use and

thus guarantee that each machine will be separate from the others,

without putting the burden of this on the cluster administrator.

This would mean interfering between machines would be impossible, and

can still be combined with the chroot benefits.

Running iptables rules to limit network interaction (easy)

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

These don't need to be handled by Ganeti, but we can ship examples. If

the users used to run VMs would be blocked from sending some or all

network traffic, it would become impossible for a broken into hypervisor

to send arbitrary data on the node network, which is especially useful

when the instance and the node network are separated (using ganeti-nbma

or a separate set of network interfaces), or when a separate replication

network is maintained. We need to experiment to see how much restriction

we can properly apply, without limiting the instance legitimate traffic.

Running kvm inside a container (even harder)

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

Recent linux kernels support different process namespaces through

control groups. PIDs, users, filesystems and even network interfaces can

be separated. If we can set up ganeti to run kvm in a separate container

we could insulate all the host process from being even visible if the

hypervisor gets broken into. Most probably separating the network

namespace would require one extra hop in the host, through a veth

interface, thus reducing performance, so we may want to avoid that, and

just rely on iptables.

Implementation plan

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

We will first implement dropping privileges for kvm processes as a

single user, and most probably backport it to 2.1. Then we'll ship

example iptables rules to show how the user can be limited in its

network activities.  After that we'll implement chroot restriction for

kvm processes, and extend the user limitation to use a user pool.

Finally we'll look into namespaces and containers, although that might

slip after the 2.2 release.

External interface changes

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

OS API

~~~~~~

The OS variants implementation in Ganeti 2.1 didn't prove to be useful

enough to alleviate the need to hack around the Ganeti API in order to

provide flexible OS parameters.

As such, for Ganeti 2.2 we will provide support for arbitrary OS

parameters. However, since OSes are not registered in Ganeti, but

instead discovered at runtime, the interface is not entirely

straightforward.

Furthermore, to support the system administrator in keeping OSes

properly in sync across the nodes of a cluster, Ganeti will also verify

(if existing) the consistence of a new ``os_version`` file.

These changes to the OS API will bump the API version to 20.

OS version

++++++++++

A new ``os_version`` file will be supported by Ganeti. This file is not

required, but if existing, its contents will be checked for consistency

across nodes. The file should hold only one line of text (any extra data

will be discarded), and its contents will be shown in the OS information

and diagnose commands.

It is recommended that OS authors increase the contents of this file for

any changes; at a minimum, modifications that change the behaviour of

import/export scripts must increase the version, since they break

intra-cluster migration.

Parameters

++++++++++

The interface between Ganeti and the OS scripts will be based on

environment variables, and as such the parameters and their values will

need to be valid in this context.

Names

^^^^^

The parameter names will be declared in a new file, ``parameters.list``,

together with a one-line documentation (whitespace-separated). Example::

  $ cat parameters.list

  ns1    Specifies the first name server to add to /etc/resolv.conf

  extra_packages  Specifies additional packages to install

  rootfs_size     Specifies the root filesystem size (the rest will be left unallocated)

  track  Specifies the distribution track, one of 'stable', 'testing' or 'unstable'

As seen above, the documentation can be separate via multiple

spaces/tabs from the names.

The parameter names as read from the file will be used for the command

line interface in lowercased form; as such, there shouldn't be any two

parameters which differ in case only.

Values

^^^^^^

The values of the parameters are, from Ganeti's point of view,

completely freeform. If a given parameter has, from the OS' point of

view, a fixed set of valid values, these should be documented as such

and verified by the OS, but Ganeti will not handle such parameters

specially.

An empty value must be handled identically as a missing parameter. In

other words, the validation script should only test for non-empty

values, and not for declared versus undeclared parameters.

Furthermore, each parameter should have an (internal to the OS) default

value, that will be used if not passed from Ganeti. More precisely, it

should be possible for any parameter to specify a value that will have

the same effect as not passing the parameter, and no in no case should

the absence of a parameter be treated as an exceptional case (outside

the value space).

Environment variables

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

The parameters will be exposed in the environment upper-case and

prefixed with the string ``OSP_``. For example, a parameter declared in

the 'parameters' file as ``ns1`` will appear in the environment as the

variable ``OSP_NS1``.

Validation

++++++++++

For the purpose of parameter name/value validation, the OS scripts

*must* provide an additional script, named ``verify``. This script will

be called with the argument ``parameters``, and all the parameters will

be passed in via environment variables, as described above.

The script should signify result/failure based on its exit code, and

show explanatory messages either on its standard output or standard

error. These messages will be passed on to the master, and stored as in

the OpCode result/error message.

The parameters must be constructed to be independent of the instance

specifications. In general, the validation script will only be called

with the parameter variables set, but not with the normal per-instance

variables, in order for Ganeti to be able to validate default parameters

too, when they change. Validation will only be performed on one cluster

node, and it will be up to the ganeti administrator to keep the OS

scripts in sync between all nodes.

Instance operations

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

The parameters will be passed, as described above, to all the other

instance operations (creation, import, export). Ideally, these scripts

will not abort with parameter validation errors, if the ``verify``

script has verified them correctly.

Note: when changing an instance's OS type, any OS parameters defined at

instance level will be kept as-is. If the parameters differ between the

new and the old OS, the user should manually remove/update them as

needed.

Declaration and modification

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

Since the OSes are not registered in Ganeti, we will only make a 'weak'

link between the parameters as declared in Ganeti and the actual OSes

existing on the cluster.

It will be possible to declare parameters either globally, per cluster

(where they are indexed per OS/variant), or individually, per

instance. The declaration of parameters will not be tied to current

existing OSes. When specifying a parameter, if the OS exists, it will be

validated; if not, then it will simply be stored as-is.

A special note is that it will not be possible to 'unset' at instance

level a parameter that is declared globally. Instead, at instance level

the parameter should be given an explicit value, or the default value as

explained above.

CLI interface

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

The modification of global (default) parameters will be done via the

``gnt-os`` command, and the per-instance parameters via the

``gnt-instance`` command. Both these commands will take an addition

``--os-parameters`` or ``-O`` flag that specifies the parameters in the

familiar comma-separated, key=value format. For removing a parameter, a

``-key`` syntax will be used, e.g.::

  # initial modification

  $ gnt-instance modify -O use_dchp=true instance1

  # later revert (to the cluster default, or the OS default if not

  # defined at cluster level)

  $ gnt-instance modify -O -use_dhcp instance1

Internal storage

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

Internally, the OS parameters will be stored in a new ``osparams``

attribute. The global parameters will be stored on the cluster object,

and the value of this attribute will be a dictionary indexed by OS name

(this also accepts an OS+variant name, which will override a simple OS

name, see below), and for values the key/name dictionary. For the

instances, the value will be directly the key/name dictionary.

Overriding rules

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

Any instance-specific parameters will override any variant-specific

parameters, which in turn will override any global parameters. The

global parameters, in turn, override the built-in defaults (of the OS

scripts).

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