Proposed flow for this scenario
- Pinned artifact
- Task definition revision
- Startup permission and network checks
- Service health gate
- Useful request or job check
- Promote or return to known good revision
This flow describes a design to evaluate. The local experiment explores one stated mechanism. Its scope appears with the controls; the proposed services are not provisioned.
Decision checkpoints
| Choice | Fits when | Watch for |
|---|---|---|
| Rolling release with health gates | Old and new versions can coexist during replacement. | Treating process startup as proof of useful customer work. |
| Automatic deployment rollback | A supported deployment controller can detect the relevant failure and has a completed revision to restore. | Assuming it reverses external side effects or schema changes. |
| Forward repair | New data or dependencies make reversal unsafe. | Deleting the prior artifact before the recovery decision is settled. |
Define the release and the recovery target
In this synthetic QuantumSketch scenario, a new render task revision changes its image reference and output format. Record the exact revision, required roles, configuration and compatibility assumptions. A mutable image tag can change independently of the task definition, so decide how the production release will identify its artifact.
The recovery target is a working service plus compatible inputs and dependencies, not merely a previous screen status. Keep the earlier artifact and configuration available through the rollback window. Define who decides that recovery is complete and which customer task demonstrates it.
Startup and health expose different failures
A replacement task can fail before it reaches running state because its image or startup permissions are unusable. A running task can then fail an application or load-balancer health check. A third category starts and passes a shallow health endpoint but fails actual customer jobs.
Choose health checks that are meaningful without making every minor dependency slowdown remove all capacity. Inspect deployment events, target health and useful completion metrics together. More tasks do not repair a bad artifact or a permissions error shared by every task.
Rollback needs a known good deployment and compatible data
For ECS rolling deployments, the supported circuit breaker can fail a deployment and, when configured, roll it back to a previously completed deployment. That behavior depends on the deployment configuration and an eligible prior completion; it is not a universal undo operation.
If the new release rewrites job records in a format the prior code cannot read, an old image may restore process health while breaking work. Use a compatibility plan for data changes, such as separating additive changes from later cleanup, and test old and new readers against the transition. This console has no SQL migration or customer data engine.
A bounded local release drill
Create a healthy synthetic ECS service revision and retain its completed deployment. Then choose a new task revision with a deliberately broken startup requirement. Inspect the event reason and the modeled circuit-breaker recovery rather than repeatedly forcing the same failed rollout.
After repair, check the selected running revision and service events. The local ECS baseline models preset metadata, startup decisions and rollback; it runs no container or image pull. Load-balancer attachment and health coverage must be checked against the currently supported console subset, not inferred from a successful startup badge.
The failure that changes the answer
Question: a release sent duplicate render notifications before rollback. Does restoring the former task revision remove those notifications? No. External effects need idempotency or reconciliation. That incident requires a business-effect recovery procedure in addition to infrastructure rollback.
The failure experiment below illustrates capacity and failure domains; it does not execute an ECS deployment. In production, observe available capacity during replacement, startup latency, traffic errors and the time to a verified recovery. There is no simulated guarantee that your release will meet an RTO or a deployment cost budget.
Practice the supported console workflow
Inspect task revisions and deployment events
Uses simulated resources stored on this device. No website account or AWS credentials required.
ExploreInspect synthetic image references
Uses simulated resources stored on this device. No website account or AWS credentials required.
ExploreInspect selected target-health decisions
Uses simulated resources stored on this device. No website account or AWS credentials required.
Explore
Predict it. Test it. Change one thing.
Local educational model. No account or cloud charges. Nothing is deployed to AWS.
Two independent zones, equal static capacity and immediate traffic redistribution are assumed. Real failover includes detection, connection recovery, data state and dependencies. This is a failure-domain capacity experiment, not a database implementation.
sim.shahriarlabs.com · Free to explore
Sources and scope
Reviewed against these official references. The model’s supported scope appears alongside its controls.
- AWS: ECS deployment circuit breaker behavior
- AWS: deployment circuit breaker API conditions
- AWS: ALB health-check behavior