Senior Cloud Engineer Guide: Zero-Downtime Multi-Cloud Migration from AWS ECS/ALB to GCP Cloud Run with Terraform

When SaaS companies hire a Senior Cloud Engineer to reduce infrastructure burn or consolidate workloads onto Google Cloud Platform, the biggest operational risk is downtime during cutover. Having executed zero-downtime migrations across AWS and GCP for 15+ years as a Google Cloud Certified Professional Cloud Architect and Cloud Engineer, I use a deterministic 4-phase runbook combining Terraform Infrastructure-as-Code (IaC), continuous PostgreSQL logical replication, and weighted edge routing.

1. Why Teams Migrate from Always-On AWS ECS/EC2 Fleets to GCP Cloud Run

Many growing startups run over-provisioned AWS EC2 Auto Scaling Groups behind Application Load Balancers (ALBs) with multi-AZ NAT Gateways and idle Elastic IPs. For spiky API and AI inference workloads, migrating stateless compute tiers to Google Cloud Run while consolidating relational state into Cloud SQL for PostgreSQL routinely reduces monthly cloud spend by 35%–55% while eliminating container cluster patching overhead.

2. Production Terraform Blueprint: Provisioning Cloud Run with Secret Manager & VPC Egress

A production-grade Cloud Engineer never provisions cutover infrastructure by clicking through the console. Below is the exact Terraform pattern used to deploy a high-concurrency Cloud Run service connected to Cloud SQL and Secret Manager with least-privilege IAM:

resource "google_service_account" "app_runtime" {
  account_id   = "prod-api-runtime"
  display_name = "Production API Cloud Run Runtime SA"
}

resource "google_project_iam_member" "runtime_roles" {
  for_each = toset([
    "roles/cloudsql.client",
    "roles/secretmanager.secretAccessor",
    "roles/logging.logWriter",
    "roles/cloudtrace.agent",
  ])
  project = var.gcp_project_id
  role    = each.value
  member  = "serviceAccount:${google_service_account.app_runtime.email}"
}

resource "google_cloud_run_v2_service" "prod_api" {
  name     = "prod-api-service"
  location = "us-east1"
  ingress  = "INGRESS_TRAFFIC_ALL"

  template {
    service_account                  = google_service_account.app_runtime.email
    max_instance_request_concurrency = 80
    timeout                          = "300s"

    scaling {
      min_instance_count = 1
      max_instance_count = 30
    }

    volumes {
      name = "cloudsql"
      cloud_sql_instance {
        instances = [google_sql_database_instance.postgres_main.connection_name]
      }
    }

    containers {
      image = "${var.artifact_registry_repo}/api:${var.git_commit_sha}"
      resources {
        limits = {
          cpu    = "2"
          memory = "2Gi"
        }
        cpu_idle          = true
        startup_cpu_boost = true
      }
      volume_mounts {
        name       = "cloudsql"
        mount_path = "/cloudsql"
      }
    }
  }
}

3. Four-Phase Zero-Downtime Database & Traffic Cutover Runbook

1. Phase 1 — Continuous Logical Replication (CDC): Enable rds.logical_replication = 1 on Amazon RDS PostgreSQL and configure Google Cloud Database Migration Service (DMS) to stream WAL changes continuously into Cloud SQL PostgreSQL. Verify replication lag remains under 200ms under peak write load.
2. Phase 2 — Shadow Read Verification: Deploy the stateless application tier to GCP Cloud Run and replay idempotent GET traffic against the Cloud Run endpoint to validate p95 latency, TLS termination, and IAM permissions before touching production DNS.
3. Phase 3 — Transactional Write Freeze & Sequence Promotion (< 15 Seconds): Place the legacy API into a brief maintenance/read-only barrier (or pause queue consumers for 10 seconds), wait for DMS replication lag to hit 0 bytes, promote the Cloud SQL replica to primary, and verify PostgreSQL sequence values (pg_sequences).
4. Phase 4 — Weighted DNS & Edge Cutover: Shift traffic from the AWS ALB to GCP Cloud Run using low-TTL (30s) or proxy-level origin rules, keeping the AWS stack warm in read-only standby for 24 hours for instant rollback safety.

4. Related Core Engineering Pillar Guides

• Hire a Senior Cloud Engineer: Multi-Cloud AWS & GCP Architecture, Terraform & FinOps Pillar Guide
• Hire a Google Cloud Certified GCP Engineer: Cloud Run, GKE, BigQuery & Vertex AI Guide