Multi-Zone Deployment for High Availability and Disaster Recovery on Google Cloud

An organization is migrating a critical application to Google Cloud and needs to ensure high availability and disaster recovery. The application runs on Compute Engine and uses a stateful database. Which three design choices should they make? (Choose three.)

Quick Answer

The answer is to use a global load balancer to route traffic to the closest healthy region, deploy managed instance groups (MIGs) across multiple zones, and configure a regional persistent disk or Cloud SQL for high availability. This combination ensures that if an entire zone fails, the MIG automatically recreates instances in healthy zones, while the stateful database remains accessible via a regional resource, providing both high availability and disaster recovery across zones on Google Cloud. On the Google Professional Cloud Developer exam, this scenario tests your understanding of regional resilience patterns versus zonal single points of failure; a common trap is choosing zonal resources like zonal persistent disks, which cannot survive a zone outage. Remember the memory tip: “Global frontend, regional backend, and a replicated database” — this trio covers traffic routing, compute failover, and data durability, ensuring your application survives any single-zone disaster.

⚠ Common exam trap

The PCD exam often tests the misconception that cost-saving measures like preemptible VMs can be applied to stateful workloads, but the trap here is that preemptible VMs are not guaranteed to run and thus cannot support a stateful database requiring persistent uptime and data integrity.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Use managed instance groups distributed across multiple zones.

Managed instance groups (MIGs) distributed across multiple zones provide automatic failover and self-healing for the Compute Engine instances. If a zone fails, the MIG automatically recreates instances in healthy zones, ensuring high availability for the application layer. This aligns with Google Cloud's best practices for regional resilience.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
Use managed instance groups distributed across multiple zones.
Why this is correct
MIGs across zones provide auto-healing and high availability.
✓
Use regional persistent disks for the database.
Why this is correct
Regional persistent disks synchronously replicate data across zones.
✓
Use a global load balancer to route traffic to the closest healthy region.
Why this is correct
Global load balancer provides traffic distribution and failover across regions.
✗
Use preemptible VMs to reduce costs for the database layer.
Why it's wrong here
Preemptible VMs can be terminated at any time, not suitable for stateful workloads.
✗
Deploy all instances in a single zone and use snapshots for backup.
Why it's wrong here
Single zone is a single point of failure.

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Same concept, more angles

1 more way this is tested on PCD

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A team is designing a cloud-native application that must be highly available and resilient to zone failures. Which three practices should they follow? (Choose three.)

medium

A.Use a single Load Balancer with multiple backends.
✓ B.Deploy resources across multiple zones.
C.Use zonal managed instance groups with 100% target utilization.
✓ D.Store data in regional persistent disks.
✓ E.Implement health checks and autohealing.

Why B: Deploying resources across multiple zones ensures that the application remains available even if an entire zone fails. In Google Cloud, zones are independent failure domains, and distributing workloads across them is a fundamental pattern for achieving high availability and resilience to zone-level outages.

Last reviewed: Jun 11, 2026

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