Stop requiring the charm to ship with a boiler plate overlay for
setting a relative path for local charm location. Instead render the
overlay from a string var. As part of this some of the template
rendering code was refactored.
This change adds support for model specific overlays from
templates which are rendered at deploy time.
The overlay template directory will be searched for a corresponding
template (<bundle_name>.j2). If one is found then the overlay will
be rendered using environment variables matching AMULET* or
ZAZA_TEMPLATE* as a context. The rendered overlay will be used on
top of the specified bundle at deploy time.
A default overlay is always applied "local-charm-overlay.yaml". This
overlay is only used to move the location of the charm being deployed
to a relative path so the bundle can use "charm: <charm name>" rather
than "charm: ../../../<charm name>"
Update vault tests to support an explicit client pointing at the
vip. Also, switch to using a namedtuple for managing the clients
to allow client metadata to be stored along with the hvac client.
juju_wait assumes it is working against the current model so
explicitly set the JUJU_MODEL env variable before calling it
to ensure it monitors the correct environment
Add --smoke switch to functest-run-suite to allow just the smoke
tests for a charm to be run. This requires that the smoke test
bundles are listed in the charms tests/tests.yaml
Bring over only those utilities required to run network_setup.py from
openstack-mojo-specs. These utilities have been generalized and python3
configured. Use libjuju whenever possible and pre-deprecate anything
else.
Add addition functions to the model.
* Add calls to asyncio.get_event_loop().close() to close loop. libjuju does
not do this for you and needs to be done just before exiting.
* Require model to be explicitly set when running command line tools. This is
part of the drive to ensure that eventually multiple runs can be performed
concurrently.
* Add set_juju_model/get_juju_model functions to manage which model is in
focus
