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[pve-docs.git] / ha-manager.adoc

[[chapter-ha-manager]]
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NAME
----

ha-manager - Proxmox VE HA Manager

SYNOPSYS
--------

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DESCRIPTION
-----------
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High Availability
=================
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Our modern society depends heavily on information provided by
computers over the network. Mobile devices amplified that dependency,
because people can access the network any time from anywhere. If you
provide such services, it is very important that they are available
most of the time.

We can mathematically define the availability as the ratio of (A) the
total time a service is capable of being used during a given interval
to (B) the length of the interval. It is normally expressed as a
percentage of uptime in a given year.

.Availability - Downtime per Year
[width="60%",cols="<d,d",options="header"]
|===========================================================
|Availability % |Downtime per year
|99             |3.65 days
|99.9           |8.76 hours
|99.99          |52.56 minutes
|99.999         |5.26 minutes
|99.9999        |31.5 seconds
|99.99999       |3.15 seconds
|===========================================================

There are several ways to increase availability. The most elegant
solution is to rewrite your software, so that you can run it on
several host at the same time. The software itself need to have a way
to detect erors and do failover. This is relatively easy if you just
want to serve read-only web pages. But in general this is complex, and
sometimes impossible because you cannot modify the software
yourself. The following solutions works without modifying the
software:

* Use reliable "server" components

NOTE: Computer components with same functionality can have varying
reliability numbers, depending on the component quality. Most verdors
sell components with higher reliability as "server" components -
usually at higher price.

* Eliminate single point of failure (redundant components)

 - use an uniteruptable power supply (UPS)
 - use redundant power supplies on the main boards
 - use ECC-RAM
 - use redundant network hardware
 - use RAID for local storage
 - use distributed, redundant storage for VM data

* Reduce downtime

 - rapidly accessible adminstrators (24/7)
 - availability of spare parts (other nodes is a {pve} cluster)
 - automatic error detection ('ha-manager')
 - automatic failover ('ha-manager')

Virtualization environments like {pve} makes it much easier to reach
high availability because they remove the "hardware" dependency. They
also support to setup and use redundant storage and network
devices. So if one host fail, you can simply start those services on
another host within your cluster.

Even better, {pve} provides a software stack called 'ha-manager',
which can do that automatically for you. It is able to automatically
detect errors and do automatic failover.

{pve} 'ha-manager' works like an "automated" administrator. First, you
configure what resources (VMs, containers, ...) it should
manage. 'ha-manager' then observes correct functionality, and handles
service failover to another node in case of errors. 'ha-manager' can
also handle normal user requests which may start, stop, relocate and
migrate a service.

But high availability comes at a price. High quality components are
more expensive, and making them redundant duplicates the costs at
least. Additional spare parts increase costs further. So you should
carefully calculate the benefits, and compare with those additional
costs.

TIP: Increasing availability from 99% to 99.9% is relatively
simply. But increasing availability from 99.9999% to 99.99999% is very
hard and costly. 'ha-manager' has typical error detection and failover
times of about 2 minutes, so you can get no more than 99.999%
availability.

Requirements
------------

* at least three cluster nodes (to get reliable quorum)

* shared storage for VMs and containers

* hardware redundancy (everywhere)

* hardware watchdog - if not available we fall back to the
  linux kernel software watchdog ('softdog')

* optional hardware fencing devices


Resources
---------

We call the primary management unit handled by 'ha-manager' a
resource. A resource (also called "service") is uniquely
identified by a service ID (SID), which consists of the resource type
and an type specific ID, e.g.: 'vm:100'. That example would be a
resource of type 'vm' (virtual machine) with the ID 100.

For now we have two important resources types - virtual machines and
containers. One basic idea here is that we can bundle related software
into such VM or container, so there is no need to compose one big
service from other services, like it was done with 'rgmanager'. In
general, a HA enabled resource should not depend on other resources.


How It Works
------------

This section provides an in detail description of the {PVE} HA-manager
internals. It describes how the CRM and the LRM work together.

To provide High Availability two daemons run on each node:

'pve-ha-lrm'::

The local resource manager (LRM), it controls the services running on
the local node.
It reads the requested states for its services from the current manager
status file and executes the respective commands.

'pve-ha-crm'::

The cluster resource manager (CRM), it controls the cluster wide
actions of the services, processes the LRM result includes the state
machine which controls the state of each service.

.Locks in the LRM & CRM
[NOTE]
Locks are provided by our distributed configuration file system (pmxcfs).
They are used to guarantee that each LRM is active and working as a
LRM only executes actions when he has its lock we can mark a failed node
as fenced if we get its lock. This lets us then recover the failed HA services
securely without the failed (but maybe still running) LRM interfering.
This all gets supervised by the CRM which holds currently the manager master
lock.

Local Resource Manager
~~~~~~~~~~~~~~~~~~~~~~

The local resource manager ('pve-ha-lrm') is started as a daemon on
boot and waits until the HA cluster is quorate and thus cluster wide
locks are working.

It can be in three states:

* *wait for agent lock*: the LRM waits for our exclusive lock. This is
  also used as idle sate if no service is configured
* *active*: the LRM holds its exclusive lock and has services configured
* *lost agent lock*: the LRM lost its lock, this means a failure happened
  and quorum was lost.

After the LRM gets in the active state it reads the manager status
file in '/etc/pve/ha/manager_status' and determines the commands it
has to execute for the service it owns.
For each command a worker gets started, this workers are running in
parallel and are limited to maximal 4 by default. This default setting
may be changed through the datacenter configuration key "max_worker".

.Maximal Concurrent Worker Adjustment Tips
[NOTE]
The default value of 4 maximal concurrent Workers may be unsuited for
a specific setup. For example may 4 live migrations happen at the same
time, which can lead to network congestions with slower networks and/or
big (memory wise) services. Ensure that also in the worst case no congestion
happens and lower the "max_worker" value if needed. In the contrary, if you
have a particularly powerful high end setup you may also want to increase it.

Each command requested by the CRM is uniquely identifiable by an UID, when
the worker finished its result will be processed and written in the LRM
status file '/etc/pve/nodes/<nodename>/lrm_status'. There the CRM may collect
it and let its state machine - respective the commands output - act on it.

The actions on each service between CRM and LRM are normally always synced.
This means that the CRM requests a state uniquely marked by an UID, the LRM
then executes this action *one time* and writes back the result, also
identifiable by the same UID. This is needed so that the LRM does not
executes an outdated command.
With the exception of the 'stop' and the 'error' command,
those two do not depend on the result produce and are executed
always in the case of the stopped state and once in the case of
the error state.

.Read the Logs
[NOTE]
The HA Stack logs every action it makes. This helps to understand what
and also why something happens in the cluster. Here its important to see
what both daemons, the LRM and the CRM, did. You may use
`journalctl -u pve-ha-lrm` on the node(s) where the service is and
the same command for the pve-ha-crm on the node which is the current master.

Cluster Resource Manager
~~~~~~~~~~~~~~~~~~~~~~~~

The cluster resource manager ('pve-ha-crm') starts on each node and
waits there for the manager lock, which can only be held by one node
at a time.  The node which successfully acquires the manager lock gets
promoted to the CRM master.

It can be in three states: TODO

* *wait for agent lock*: the LRM waits for our exclusive lock. This is
  also used as idle sate if no service is configured
* *active*: the LRM holds its exclusive lock and has services configured
* *lost agent lock*: the LRM lost its lock, this means a failure happened
  and quorum was lost.

It main task is to manage the services which are configured to be highly
available and try to get always bring them in the wanted state, e.g.: a
enabled service will be started if its not running, if it crashes it will
be started again. Thus it dictates the LRM the wanted actions.

When an node leaves the cluster quorum, its state changes to unknown.
If the current CRM then can secure the failed nodes lock, the services
will be 'stolen' and restarted on another node.

When a cluster member determines that it is no longer in the cluster
quorum, the LRM waits for a new quorum to form. As long as there is no
quorum the node cannot reset the watchdog. This will trigger a reboot
after 60 seconds.

Configuration
-------------

The HA stack is well integrated int the Proxmox VE API2. So, for
example, HA can be configured via 'ha-manager' or the PVE web
interface, which both provide an easy to use tool.

The resource configuration file can be located at
'/etc/pve/ha/resources.cfg' and the group configuration file at
'/etc/pve/ha/groups.cfg'. Use the provided tools to make changes,
there shouldn't be any need to edit them manually.

Node Power Status
-----------------

If a node needs maintenance you should migrate and or relocate all
services which are required to run always on another node first.
After that you can stop the LRM and CRM services. But note that the
watchdog triggers if you stop it with active services.

Fencing
-------

What Is Fencing
~~~~~~~~~~~~~~~

Fencing secures that on a node failure the dangerous node gets will be rendered
unable to do any damage and  that no resource runs twice when it gets recovered
from the failed node.

Configure Hardware Watchdog
~~~~~~~~~~~~~~~~~~~~~~~~~~~
By default all watchdog modules are blocked for security reasons as they are
like a loaded gun if not correctly initialized.
If you have a hardware watchdog available remove its module from the blacklist
and restart 'the watchdog-mux' service.


Groups
------

A group is a collection of cluster nodes which a service may be bound to.

Group Settings
~~~~~~~~~~~~~~

nodes::

list of group node members

restricted::

resources bound to this group may only run on nodes defined by the
group. If no group node member is available the resource will be
placed in the stopped state.

nofailback::

the resource won't automatically fail back when a more preferred node
(re)joins the cluster.


Recovery Policy
---------------

There are two service recover policy settings which can be configured
specific for each resource.

max_restart::

maximal number of tries to restart an failed service on the actual
node.  The default is set to one.

max_relocate::

maximal number of tries to relocate the service to a different node.
A relocate only happens after the max_restart value is exceeded on the
actual node. The default is set to one.

Note that the relocate count state will only reset to zero when the
service had at least one successful start. That means if a service is
re-enabled without fixing the error only the restart policy gets
repeated.

Error Recovery
--------------

If after all tries the service state could not be recovered it gets
placed in an error state. In this state the service won't get touched
by the HA stack anymore.  To recover from this state you should follow
these steps:

* bring the resource back into an safe and consistent state (e.g:
killing its process)

* disable the ha resource to place it in an stopped state

* fix the error which led to this failures

* *after* you fixed all errors you may enable the service again


Service Operations
------------------

This are how the basic user-initiated service operations (via
'ha-manager') work.

enable::

the service will be started by the LRM if not already running.

disable::

the service will be stopped by the LRM if running.

migrate/relocate::

the service will be relocated (live) to another node.

remove::

the service will be removed from the HA managed resource list. Its
current state will not be touched.

start/stop::

start and stop commands can be issued to the resource specific tools
(like 'qm' or 'pct'), they will forward the request to the
'ha-manager' which then will execute the action and set the resulting
service state (enabled, disabled).


Service States
--------------

stopped::

Service is stopped (confirmed by LRM)

request_stop::

Service should be stopped. Waiting for confirmation from LRM.

started::

Service is active an LRM should start it ASAP if not already running.

fence::

Wait for node fencing (service node is not inside quorate cluster
partition).

freeze::

Do not touch the service state. We use this state while we reboot a
node, or when we restart the LRM daemon.

migrate::

Migrate service (live) to other node.

error::

Service disabled because of LRM errors. Needs manual intervention.


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