Moves all tasks run by the Celery worker into a discrete package/module
for easier installation. Also adjusts several parameters throughout to
accomplish this.
Redis did not provide a distributed solution for the worker, which
precluded several important planned functions. So instead, move to using
Zookeeper + PostgreSQL as the broker and result backend respectively.
Should be a seamless drop-in change but for future uses requires the
database host to be the primary coordinator IP rather than localhost, so
that writes can occur to the database from non-primary hosts.
This reverts commit 65d14ccd92.
This was actually a bad idea. For inexplicable reasons, running these
Ceph commands manually (not even via Python, but in a normal shell)
takes 7 * two orders of magnitude longer than running them with the
Rados module, so long in fact that some basic commands like "ceph
health" would sometimes take longer than the 1 second timeout to
complete. The Rados commands would however take about 1ms instead.
Despite the occasional issues when monitors drop out, the Rados module
is clearly far superior to the shell commands for any moderately-loaded
Ceph cluster. We can look into solving timeouts another way (perhaps
with Processes instead of Threads) at a later time.
Rados module "ceph health":
b'{"checks":{},"status":"HEALTH_OK"}'
0.001204 (s)
b'{"checks":{},"status":"HEALTH_OK"}'
0.001258 (s)
Command "ceph health":
joshua@hv1.c.bonilan.net ~ $ time ceph health >/dev/null
real 0m0.772s
user 0m0.707s
sys 0m0.046s
joshua@hv1.c.bonilan.net ~ $ time ceph health >/dev/null
real 0m0.796s
user 0m0.728s
sys 0m0.054s
Using the Rados module was very problematic, specifically because it had
no sensible timeout parameters and thus would hang for many seconds.
This has poor implications since it blocks further keepalives.
Instead, remove the Rados usage entirely and go back completely to using
manual OS commands to gather this information. While this may cause PID
exhaustion more quickly it's worthwhile to avoid failure scenarios when
Ceph stats time out.
Closes#137
Gevent was completely failure. The API would block during large file
uploads with no obvious solutions beyond "use gunicorn", which is not
suited to this. I originally had this working with the Flask "debug"
server, so just move to using that all the time. SSL is added using a
custom context with the OpenSSL library, so include that as a
dependency.
Add management of the pvcprov database with SQLAlchemy, to allow
seamless management of the database. Add automatic tasks to the postinst
of the API to execute these migrations.
Implements a "maintenance mode" for PVC clusters. For now, the only
thing this mode does is disable node fencing while the state is true.
This allows the administrator to tell PVC that network connectivity,
etc. might be interrupted and to avoid fencing nodes.
Closes#70
MariaDB+Galera was terribly unstable, with the cluster failing to
start or dying randomly, and generally seemed incredibly unsuitable
for an HA solution. This commit switches the DNS aggregator SQL
backend to PostgreSQL, implemented via Patroni HA.
It also manages the Patroni state, forcing the primary instance to
follow the PVC coordinator, such that the active DNS Aggregator
instance is always able to communicate read+write with the local
system.
This required some logic changes to how the DNS Aggregator worked,
specifically ensuring that database changes aren't attempted while
the instance isn't actively running - to be honest this was a bug
anyways that had just never been noticed.
Closes#34
Trying to directly AXFR from dnsmasq is a mess, since their zone is
barely compliant with spec, it doesn't support notifies, and it is
generally really messy.
This implements an advanced "AXFR parser" system, which looks at the
results of an AXFR from the local dnsmasq instances per-network, and
updates the real replicated MariaDB pdns backend cluster with the
changed data. This allows a sensible, transferable zone with its own
SOA that is dynamically reconfigured as hosts come and go from the
dnsmasq zone.
Completely restructure the daemon code to move the 4 discrete daemons
into a single daemon that can be run on every hypervisor. Introduce the
idea of a static list of "coordinator" nodes which are configured at
install time to run Zookeeper and FRR in router mode, and which are
allowed to take on client network management duties (gateway, DHCP, DNS,
etc.) while also allowing them to run VMs (i.e. no dedicated "router"
nodes required).
Joshua Boniface