The declaration matches, but the application still fails
reports Synced. The rollout can still be unhealthy, or the application can answer requests while a reservation fails. These are different checks.
- Sync: does the observed match the desired configuration tracked by Argo?
- Health: do the resources satisfy their health criteria?
- Business smoke: can a small representative user operation complete correctly?
A successful sync is useful evidence, but it does not answer the other two questions.
Predict three release decisions
This standalone 3.11+ example uses synthetic observations. Save release.py, then run python3 release.py. It does not contact or modify a cluster.
def release_ready(sync: str, health: str, smoke_ok: bool) -> bool:
return sync == "Synced" and health == "Healthy" and smoke_ok is True
cases = [
("Synced", "Degraded", True),
("Synced", "Healthy", False),
("Synced", "Healthy", True),
]
for case in cases:
print(release_ready(*case))Expected output is False, False, True, each on its own line. This is a small release policy, not a replacement for Argo's health assessment or a live . A real check must collect fresh observations for the intended environment and revision.
Find the missing condition
Remove and smoke_ok is True. The second case now returns True, although the user operation failed. it. Add an OutOfSync / Healthy / True case and predict its result before running.
Do not invent a successful observation to make a release green. An unavailable check means you lack evidence; diagnose the check or the application.
Follow the dependencies
Reviewed source → → configuration commit → Argo → → business operation.
During a migration, an old Pod may need to continue serving until the new schema is ready. Rolling back an image does not undo data already written. In a real lab, deliberately fail a migration and check the old application before claiming rollback works.
Your next experiment
On a local cluster, compare four observations of one deployment: revision, sync, health and an application request result. them separately. Which observation catches a healthy Deployment with incorrect business configuration?
Sources
CHECK YOUR INTUITION