def freeze(
id: Optional[str],
message: Optional[str],
lifetime: int,
namespaces: Collection[references.NamespacePattern],
clusterwide: bool,
peering_name: str,
priority: int,
) -> None:
""" Pause the resource handling in the operator(s). """
identity = peering.Identity(id) if id else peering.detect_own_id(
manual=True)
insights = references.Insights()
settings = configuration.OperatorSettings()
settings.peering.name = peering_name
settings.peering.priority = priority
return running.run(clusterwide=clusterwide,
namespaces=namespaces,
insights=insights,
identity=identity,
settings=settings,
_command=peering.touch_command(insights=insights,
identity=identity,
settings=settings,
lifetime=lifetime))
async def spawn_tasks(
*,
lifecycle: Optional[execution.LifeCycleFn] = None,
indexers: Optional[indexing.OperatorIndexers] = None,
registry: Optional[registries.OperatorRegistry] = None,
settings: Optional[configuration.OperatorSettings] = None,
memories: Optional[inventory.ResourceMemories] = None,
insights: Optional[references.Insights] = None,
identity: Optional[peering.Identity] = None,
standalone: Optional[bool] = None,
priority: Optional[int] = None,
peering_name: Optional[str] = None,
liveness_endpoint: Optional[str] = None,
clusterwide: bool = False,
namespaces: Collection[references.NamespacePattern] = (),
namespace: Optional[references.NamespacePattern] = None, # deprecated
stop_flag: Optional[aioadapters.Flag] = None,
ready_flag: Optional[aioadapters.Flag] = None,
vault: Optional[credentials.Vault] = None,
memo: Optional[object] = None,
_command: Optional[Coroutine[None, None, None]] = None,
) -> Collection[aiotasks.Task]:
"""
Spawn all the tasks needed to run the operator.
The tasks are properly inter-connected with the synchronisation primitives.
"""
loop = asyncio.get_running_loop()
if namespaces and namespace:
raise TypeError("Either namespaces= or namespace= can be passed. Got both.")
elif namespace:
warnings.warn("namespace= is deprecated; use namespaces=[...]", DeprecationWarning)
namespaces = [namespace]
if clusterwide and namespaces:
raise TypeError("The operator can be either cluster-wide or namespaced, not both.")
if not clusterwide and not namespaces:
warnings.warn("Absence of either namespaces or cluster-wide flag will become an error soon."
" For now, switching to the cluster-wide mode for backward compatibility.",
FutureWarning)
clusterwide = True
# All tasks of the operator are synced via these primitives and structures:
lifecycle = lifecycle if lifecycle is not None else lifecycles.get_default_lifecycle()
registry = registry if registry is not None else registries.get_default_registry()
settings = settings if settings is not None else configuration.OperatorSettings()
memories = memories if memories is not None else inventory.ResourceMemories()
indexers = indexers if indexers is not None else indexing.OperatorIndexers()
insights = insights if insights is not None else references.Insights()
identity = identity if identity is not None else peering.detect_own_id(manual=False)
vault = vault if vault is not None else credentials.Vault()
memo = memo if memo is not None else ephemera.Memo()
memo = ephemera.AnyMemo(memo) # type-casted
event_queue: posting.K8sEventQueue = asyncio.Queue()
signal_flag: aiotasks.Future = asyncio.Future()
started_flag: asyncio.Event = asyncio.Event()
operator_paused = aiotoggles.ToggleSet(any)
tasks: MutableSequence[aiotasks.Task] = []
# Map kwargs into the settings object.
settings.peering.clusterwide = clusterwide
if peering_name is not None:
settings.peering.mandatory = True
settings.peering.name = peering_name
if standalone is not None:
settings.peering.standalone = standalone
if priority is not None:
settings.peering.priority = priority
# Prepopulate indexers with empty indices -- to be available startup handlers.
indexers.ensure(registry._indexing.get_all_handlers())
# Global credentials store for this operator, also for CRD-reading & peering mode detection.
auth.vault_var.set(vault)
# Special case: pass the settings container through the user-side handlers (no explicit args).
# Toolkits have to keep the original operator context somehow, and the only way is contextvars.
posting.settings_var.set(settings)
# Few common background forever-running infrastructural tasks (irregular root tasks).
tasks.append(aiotasks.create_task(
name="stop-flag checker",
coro=_stop_flag_checker(
signal_flag=signal_flag,
stop_flag=stop_flag)))
tasks.append(aiotasks.create_task(
name="ultimate termination",
coro=_ultimate_termination(
settings=settings,
stop_flag=stop_flag)))
tasks.append(aiotasks.create_task(
name="startup/cleanup activities",
coro=_startup_cleanup_activities(
root_tasks=tasks, # used as a "live" view, populated later.
ready_flag=ready_flag,
started_flag=started_flag,
registry=registry,
settings=settings,
indices=indexers.indices,
vault=vault,
memo=memo))) # to purge & finalize the caches in the end.
# Kill all the daemons gracefully when the operator exits (so that they are not "hung").
tasks.append(aiotasks.create_guarded_task(
name="daemon killer", flag=started_flag, logger=logger,
coro=daemons.daemon_killer(
settings=settings,
memories=memories,
operator_paused=operator_paused)))
# Keeping the credentials fresh and valid via the authentication handlers on demand.
tasks.append(aiotasks.create_guarded_task(
name="credentials retriever", flag=started_flag, logger=logger,
coro=activities.authenticator(
registry=registry,
settings=settings,
indices=indexers.indices,
vault=vault,
memo=memo)))
# K8s-event posting. Events are queued in-memory and posted in the background.
# NB: currently, it is a global task, but can be made per-resource or per-object.
tasks.append(aiotasks.create_guarded_task(
name="poster of events", flag=started_flag, logger=logger,
coro=posting.poster(
backbone=insights.backbone,
event_queue=event_queue)))
# Liveness probing -- so that Kubernetes would know that the operator is alive.
if liveness_endpoint:
tasks.append(aiotasks.create_guarded_task(
name="health reporter", flag=started_flag, logger=logger,
coro=probing.health_reporter(
registry=registry,
settings=settings,
endpoint=liveness_endpoint,
indices=indexers.indices,
memo=memo)))
# Admission webhooks run as either a server or a tunnel or a fixed config.
# The webhook manager automatically adjusts the cluster configuration at runtime.
container: aiovalues.Container[reviews.WebhookClientConfig] = aiovalues.Container()
tasks.append(aiotasks.create_guarded_task(
name="admission insights chain", flag=started_flag, logger=logger,
coro=aiobindings.condition_chain(
source=insights.revised, target=container.changed)))
tasks.append(aiotasks.create_guarded_task(
name="admission validating configuration manager", flag=started_flag, logger=logger,
coro=admission.validating_configuration_manager(
container=container, settings=settings, registry=registry, insights=insights)))
tasks.append(aiotasks.create_guarded_task(
name="admission mutating configuration manager", flag=started_flag, logger=logger,
coro=admission.mutating_configuration_manager(
container=container, settings=settings, registry=registry, insights=insights)))
tasks.append(aiotasks.create_guarded_task(
name="admission webhook server", flag=started_flag, logger=logger,
coro=admission.admission_webhook_server(
container=container, settings=settings, registry=registry, insights=insights,
webhookfn=functools.partial(admission.serve_admission_request,
settings=settings, registry=registry, insights=insights,
memories=memories, memobase=memo,
indices=indexers.indices))))
# Permanent observation of what resource kinds and namespaces are available in the cluster.
# Spawn and cancel dimensional tasks as they come and go; dimensions = resources x namespaces.
tasks.append(aiotasks.create_guarded_task(
name="resource observer", flag=started_flag, logger=logger,
coro=observation.resource_observer(
insights=insights,
registry=registry,
settings=settings)))
tasks.append(aiotasks.create_guarded_task(
name="namespace observer", flag=started_flag, logger=logger,
coro=observation.namespace_observer(
clusterwide=clusterwide,
namespaces=namespaces,
insights=insights,
settings=settings)))
# Explicit command is a hack for the CLI to run coroutines in an operator-like environment.
# If not specified, then use the normal resource processing. It is not exposed publicly (yet).
if _command is not None:
tasks.append(aiotasks.create_guarded_task(
name="the command", flag=started_flag, logger=logger, finishable=True,
coro=_command))
else:
tasks.append(aiotasks.create_guarded_task(
name="multidimensional multitasker", flag=started_flag, logger=logger,
coro=orchestration.ochestrator(
settings=settings,
insights=insights,
identity=identity,
operator_paused=operator_paused,
processor=functools.partial(processing.process_resource_event,
lifecycle=lifecycle,
registry=registry,
settings=settings,
indexers=indexers,
memories=memories,
memobase=memo,
event_queue=event_queue))))
# Ensure that all guarded tasks got control for a moment to enter the guard.
await asyncio.sleep(0)
# On Ctrl+C or pod termination, cancel all tasks gracefully.
if threading.current_thread() is threading.main_thread():
# Handle NotImplementedError when ran on Windows since asyncio only supports Unix signals
try:
loop.add_signal_handler(signal.SIGINT, signal_flag.set_result, signal.SIGINT)
loop.add_signal_handler(signal.SIGTERM, signal_flag.set_result, signal.SIGTERM)
except NotImplementedError:
logger.warning("OS signals are ignored: can't add signal handler in Windows.")
else:
logger.warning("OS signals are ignored: running not in the main thread.")
return tasks