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An enterprise runs mission-critical analytical workflows on Cloud Composer in the us-central1 region. The data engineering team must implement an automated cross-region disaster recovery (DR) strategy to fail over orchestration to us-east4 in the event of an outage.
The solution must satisfy the following technical requirements:
Which architecture and recovery workflow should the team deploy?
Enable asynchronous Persistent Disk replication between the primary and secondary Cloud Composer GKE worker nodes, configure Cloud Monitoring to detect node health degradation, and script Cloud Functions to force-attach the replicated disks to a new GKE cluster in us-east4.
Maintain synchronized Terraform definitions to provision identical Composer and Airflow versions in both regions. Store scheduled primary snapshots in a multi-region Cloud Storage bucket, monitor snapshot health using Cloud Monitoring alerting on the snapshot creation metric, deploy a Cloud Function triggered by disaster alerts to pause primary DAGs, load the latest snapshot into the failover environment, and ensure all DAG tasks are designed to be idempotent.
Store environment snapshots in the primary environment's default Cloud Storage bucket, configure Cloud Scheduler to trigger hourly snapshot export jobs via gcloud CLI, and execute a Terraform script during failover that upgrades the secondary environment to the latest Composer version.
Configure Cloud Composer in High Resilience mode across two zones in us-central1, stream Airflow metadata logs to Cloud Logging, and rely on Cloud SQL automatic cross-zone failover without snapshot restoration or separate secondary environments.
Enable asynchronous Persistent Disk replication between the primary and secondary Cloud Composer GKE worker nodes, configure Cloud Monitoring to detect node health degradation, and script Cloud Functions to force-attach the replicated disks to a new GKE cluster in us-east4.
Maintain synchronized Terraform definitions to provision identical Composer and Airflow versions in both regions. Store scheduled primary snapshots in a multi-region Cloud Storage bucket, monitor snapshot health using Cloud Monitoring alerting on the snapshot creation metric, deploy a Cloud Function triggered by disaster alerts to pause primary DAGs, load the latest snapshot into the failover environment, and ensure all DAG tasks are designed to be idempotent.
This solution establishes a resilient cross-region disaster recovery architecture for Cloud Composer workflows using environment snapshots, Terraform infrastructure as code (IaC), Cloud Monitoring alerting, and Cloud Functions for automated failover orchestration.
StudyCerts
StudyCertsus-central1) and secondary (us-east4) environments share identical Cloud Composer versions, Airflow builds, environment sizes, and PyPI dependencies.Snapshot creation count metric filtered by result = SUCCEEDED guarantees proactive alerting if automated snapshot capture fails.us-east4 failover environment, and applying regional connection overrides.This approach aligns with Google Cloud site reliability engineering best practices by combining immutable infrastructure definitions, automated monitoring triggers, decoupled multi-region backups, and idempotent workflow design.
Store environment snapshots in the primary environment's default Cloud Storage bucket, configure Cloud Scheduler to trigger hourly snapshot export jobs via gcloud CLI, and execute a Terraform script during failover that upgrades the secondary environment to the latest Composer version.
Configure Cloud Composer in High Resilience mode across two zones in us-central1, stream Airflow metadata logs to Cloud Logging, and rely on Cloud SQL automatic cross-zone failover without snapshot restoration or separate secondary environments.