* This also adds fields to the instance view for tracking cpu and
memory usage as well as information on what the capacity ranges are
* Also adds a flag for enabling/disabling instances which removes them
from all queues and has them stop processing new work
* The capacity is now based almost exclusively on some value relative
to forks
* capacity_adjustment allows you to commit an instance to a certain
amount of forks, cpu focused or memory focused
* Each job run adds a single fork overhead (that's the reasoning
behind the +1)
* Switch policy router queue to not be "tower" so that we don't
fall into a chicken/egg scenario
* Show fixed policy list in serializer so a user can determine if
an instance is manually managed
* Change IG membership mixin to not directly handle applying topology
changes. Instead it just makes sure the policy instance list is
accurate
* Add create/delete hooks for instances and groups to trigger policy
re-evaluation
* Update policy algorithm for fairer distribution
* Fix an issue where CELERY_ROUTES wasn't renamed after celery/django
upgrade
* Update unit tests to be more explicit
* Update count calculations used by algorithm to only consider
non-manual instances
* Adding unit tests and fixture
* Don't propagate logging messages from awx.main.tasks and
awx.main.scheduler
* Use advisory lock to prevent policy eval conflicts
* Allow updating instance groups from view
* use embedded beat rather than standalone
* dynamically set celeryd hostname at runtime
* add embeded beat flag to celery startup
* Embedded beat mode routes will piggyback off of celery worker setup
signal
* Associating/Disassociating an instance with a group
* Triggering a topology rebuild on that change
* Force rabbitmq cleanup of offline nodes
* Automatically check for dependent service startup
* Fetch and set hostname for celery so it doesn't clobber other
celeries
* Rely on celery init signals to dyanmically set listen queues
* Removing old total_capacity instance manager property
* Based on the tower topology (Instance and InstanceGroup
relationships), have celery dyamically listen to queues on boot
* Add celery task capable of "refreshing" what queues each celeryd
worker listens to. This will be used to support changes in the topology.
* Cleaned up some celery task definitions.
* Converged wrongly targeted job launch/finish messages to 'tower'
queue, rather than a 1-off queue.
* Dynamically route celery tasks destined for the local node
* separate beat process
add support for separate beat process
If the "DTSTART" property is specified as a date with UTC time or a date with
local time and time zone reference, then the UNTIL rule part MUST be specified
as a date with UTC time.
redbaron is a library we use to facilitate parsing local settings files;
at _import_ time it generates a parse tree and caches it to disk at
`/tmp`; this process is _really time consuming, and only necessary if
we're actually *using* the library
right now, we're importing this library and paying the penalty
_every_ time we load the awx application
this commit allows schedule `rrule` strings to include local timezone
information via TZID=NNNNN; occurrences are _generated_ in the local
time specific by the user (or UTC, if e.g., DTSTART:YYYYMMDDTHHMMSSZ)
while Schedule.next_run, Schedule.dtstart, and Schedule.dtend will be
stored in the UTC equivalent (i.e., the scheduler will still do math on
"what to run next" based on UTC datetimes).
in addition to this change, there is now a new API endpoint,
`/api/v2/schedules/preview/`, which takes an rrule and shows the next
10 occurrences in local and UTC time.
see: https://github.com/ansible/ansible-tower/issues/823
related: https://github.com/dateutil/dateutil/issues/614
