The focus of this tutorial will be building a Salt infrastructure for handling large numbers of minions. This will include tuning, topology, and best practices.
For how to install the Salt Master, see the Salt install guide.
This tutorial is intended for large installations, although these same settings won't hurt, it may not be worth the complexity to smaller installations.
When used with minions, the term 'many' refers to at least a thousand and 'a few' always means 500.
For simplicity reasons, this tutorial will default to the standard ports used by Salt.
The most common problems on the Salt Master are:
too many minions authing at once
too many minions re-authing at once
too many minions re-connecting at once
too many minions returning at once
too few resources (CPU/HDD)
The first three are all "thundering herd" problems. To mitigate these issues we must configure the minions to back-off appropriately when the Master is under heavy load.
The fourth is caused by masters with little hardware resources in combination with a possible bug in ZeroMQ. At least that's what it looks like till today (Issue 118651, Issue 5948, Mail thread)
To fully understand each problem, it is important to understand, how Salt works.
Very briefly, the Salt Master offers two services to the minions.
a job publisher on port 4505
an open port 4506 to receive the minions returns
All minions are always connected to the publisher on port 4505 and only connect to the open return port 4506 if necessary. On an idle Master, there will only be connections on port 4505.
When the Minion service is first started up, it will connect to its Master's publisher on port 4505. If too many minions are started at once, this can cause a "thundering herd". This can be avoided by not starting too many minions at once.
The connection itself usually isn't the culprit, the more likely cause of master-side issues is the authentication that the Minion must do with the Master. If the Master is too heavily loaded to handle the auth request it will time it out. The Minion will then wait acceptance_wait_time to retry. If acceptance_wait_time_max is set then the Minion will increase its wait time by the acceptance_wait_time each subsequent retry until reaching acceptance_wait_time_max.
This is most likely to happen in the testing phase of a Salt deployment, when all Minion keys have already been accepted, but the framework is being tested and parameters are frequently changed in the Salt Master's configuration file(s).
The Salt Master generates a new AES key to encrypt its publications at certain
events such as a Master restart or the removal of a Minion key. If you are
encountering this problem of too many minions re-authing against the Master,
you will need to recalibrate your setup to reduce the rate of events like a
Master restart or Minion key removal (
When the Master generates a new AES key, the minions aren't notified of this but will discover it on the next pub job they receive. When the Minion receives such a job it will then re-auth with the Master. Since Salt does minion-side filtering this means that all the minions will re-auth on the next command published on the master-- causing another "thundering herd". This can be avoided by setting the
in the minions configuration file to a higher value and stagger the amount of re-auth attempts. Increasing this value will of course increase the time it takes until all minions are reachable via Salt commands.
By default the zmq socket will re-connect every 100ms which for some larger installations may be too quick. This will control how quickly the TCP session is re-established, but has no bearing on the auth load.
To tune the minions sockets reconnect attempts, there are a few values in the sample configuration file (default values)
recon_default: 1000 recon_max: 5000 recon_randomize: True
recon_default: the default value the socket should use, i.e. 1000. This value is in milliseconds. (1000ms = 1 second)
recon_max: the max value that the socket should use as a delay before trying to reconnect This value is in milliseconds. (5000ms = 5 seconds)
recon_randomize: enables randomization between recon_default and recon_max
To tune this values to an existing environment, a few decision have to be made.
How long can one wait, before the minions should be online and reachable via Salt?
How many reconnects can the Master handle without a syn flood?
These questions can not be answered generally. Their answers depend on the hardware and the administrators requirements.
Here is an example scenario with the goal, to have all minions reconnect within a 60 second time-frame on a Salt Master service restart.
recon_default: 1000 recon_max: 59000 recon_randomize: True
Each Minion will have a randomized reconnect value between 'recon_default' and 'recon_default + recon_max', which in this example means between 1000ms and 60000ms (or between 1 and 60 seconds). The generated random-value will be doubled after each attempt to reconnect (ZeroMQ default behavior).
Lets say the generated random value is 11 seconds (or 11000ms).
reconnect 1: wait 11 seconds reconnect 2: wait 22 seconds reconnect 3: wait 33 seconds reconnect 4: wait 44 seconds reconnect 5: wait 55 seconds reconnect 6: wait time is bigger than 60 seconds (recon_default + recon_max) reconnect 7: wait 11 seconds reconnect 8: wait 22 seconds reconnect 9: wait 33 seconds reconnect x: etc.
With a thousand minions this will mean
1000/60 = ~16
round about 16 connection attempts a second. These values should be altered to values that match your environment. Keep in mind though, that it may grow over time and that more minions might raise the problem again.
This can also happen during the testing phase, if all minions are addressed at once with
$ salt * disk.usage
it may cause thousands of minions trying to return their data to the Salt Master open port 4506. Also causing a flood of syn-flood if the Master can't handle that many returns at once.
This can be easily avoided with Salt's batch mode:
$ salt * disk.usage -b 50
This will only address 50 minions at once while looping through all addressed minions.
The masters resources always have to match the environment. There is no way to give good advise without knowing the environment the Master is supposed to run in. But here are some general tuning tips for different situations:
In installations with large or with complex pillar files, it is possible for the master to exhibit poor performance as a result of having to render many pillar files at once. This exhibit itself in a number of ways, both as high load on the master and on minions which block on waiting for their pillar to be delivered to them.
To reduce pillar rendering times, it is possible to cache pillars on the master. To do this, see the set of master configuration options which are prefixed with pillar_cache.
If many pillars are encrypted using
gpg renderer, it
is possible to cache GPG data. To do this, see the set of master configuration
options which are prefixed with gpg_cache.
Caching pillars or GPG data on the master may introduce security considerations. Be certain to read caveats outlined in the master configuration file to understand how pillar caching may affect a master's ability to protect sensitive data!
By default, the Master saves every Minion's return for every job in its job-cache. The cache can then be used later, to lookup results for previous jobs. The default directory for this is:
and then in the
Each job return for every Minion is saved in a single file. Over time this directory can grow quite large, depending on the number of published jobs. The amount of files and directories will scale with the number of jobs published and the retention time defined by
250 jobs/day * 2000 minions returns = 500,000 files a day
An external job cache allows for job storage to be placed on an external system, such as a database.
ext_job_cache: this will have the minions store their return data directly into a returner (not sent through the Master)
master_job_cache (New in 2014.7.0): this will make the Master store the job data using a returner (instead of the local job cache on disk).
If a master has many accepted keys, it may take a long time to publish a job because the master must first determine the matching minions and deliver that information back to the waiting client before the job can be published.
To mitigate this, a key cache may be enabled. This will reduce the load on the master to a single file open instead of thousands or tens of thousands.
This cache is updated by the maintenance process, however, which means that minions with keys that are accepted may not be targeted by the master for up to sixty seconds by default.
To enable the master key cache, set key_cache: 'sched' in the master configuration file.
The job cache is a central component of the Salt Master and many aspects of the Salt Master will not function correctly without a running job cache.
Disabling the job cache is STRONGLY DISCOURAGED and should not be done unless the master is being used to execute routines that require no history or reliable feedback!
The job cache can be disabled: