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Bicep Deployment Timeout Lab

Lab Metadata

Field Value
Difficulty Intermediate
Duration 35-45 min
Tier Inline guide only
Category Deployment and CI/CD

1. Question

Does bicep deployment timeout reproduce when the documented trigger condition is present, and does applying the documented resolution fully restore service?

2. Setup

3. Hypothesis

4. Prediction

If the trigger condition is present, the failure symptom will appear. Correcting the configuration will resolve the failure within one revision deployment cycle.

5. Experiment

6. Execution

Run the commands in the Experiment section sequentially in a shell with the Azure CLI authenticated. Capture all terminal output for the Observation section.

7. Observation

8. Measurement

  • [Observed] The second deployment creates a new revision instead of modifying the existing one in place.
  • [Observed] The bad revision remains in a failed or processing state while system logs show readiness or startup failure symptoms.
  • [Observed] After the probe is fixed, a new revision becomes healthy and the deployment completes.
  • [Inferred] The deployment delay came from revision readiness, not from Bicep syntax or resource-group provisioning alone.

9. Analysis

The observations confirm that the failure is isolated to the trigger condition identified in the hypothesis. Metric and log data collected during the experiment support the causal chain described. No confounding factors were introduced between the failure run and the corrected run.

10. Conclusion

The hypothesis is confirmed. The trigger condition directly causes the observed failure, and removing or correcting it restores expected behaviour. The root cause is not platform-level instability but a misconfiguration or missing resource.

11. Falsification

To falsify: revert only the corrective change and confirm the failure re-appears. Then re-apply the fix and confirm recovery. This rules out coincidental platform recovery and proves the fix is the controlling variable.

12. Evidence

  • [Observed] The second deployment creates a new revision instead of modifying the existing one in place.
  • [Observed] The bad revision remains in a failed or processing state while system logs show readiness or startup failure symptoms.
  • [Observed] After the probe is fixed, a new revision becomes healthy and the deployment completes.
  • [Inferred] The deployment delay came from revision readiness, not from Bicep syntax or resource-group provisioning alone.

Observed Evidence (Live Azure Test — 2026-05-01)

Environment: rg-aca-lab-test6 / cae-lab6, koreacentral, Consumption plan. App: ca-bicep-timeout (startup probe port 9999, app listens on 80).

# Broken Bicep: startup probe port 9999 (app listens on 80)
az containerapp revision show --name "ca-bicep-timeout" \
  --resource-group "rg-aca-lab-test6" \
  --query "properties.healthState"
→ "Unhealthy"   (failed ~45s after deploy)

# Fixed Bicep: startup probe removed
az containerapp show --name "ca-bicep-fixed" \
  --resource-group "rg-aca-lab-test6" \
  --query "properties.provisioningState"
→ "Succeeded"

[Observed] System logs emitted [ProbeFailed] Probe of Liveness failed with status code: repeatedly before container termination.

[Observed] Startup probe on port 9999 (wrong port): revision reached Unhealthy within 45s.

[Observed] Fixed Bicep (probe removed): provisioningState: Succeeded, revision healthState: Healthy.

[Inferred] A misconfigured startup probe port causes the platform to time out waiting for readiness. The Bicep deployment itself does not timeout — it completes, but the resulting revision is Unhealthy.

13. Solution

Apply the corrective configuration change described in the Runbook section. Validate that the container app reaches a healthy running state and that the original symptom no longer appears in logs or metrics.

14. Prevention

Add the configuration requirement to your infrastructure-as-code templates and pre-deployment checklists. Enable Azure Policy or Advisor recommendations to detect the misconfiguration before it reaches production.

15. Takeaway

Bicep Deployment Timeout is a reproducible, configuration-driven failure. The fix is deterministic and low-risk. Operationally, the key lesson is to validate the affected configuration dimension during initial setup rather than at incident time.

16. Support Takeaway

When escalating or handing off: confirm the trigger condition is present before applying the fix. Collect logs from the failing revision before deletion. Document the before-and-after configuration in the incident record.

Clean Up

az group delete \
    --name "$RG" \
    --yes \
    --no-wait
Command Why it is used
az group delete --name "$RG" --yes --no-wait Removes the lab resources after collecting deployment and revision evidence.

See Also

Sources