Accelerate Business Transformation with Google Cloud Migration & Deployment Services

GCP migration timelines vary significantly based on environment complexity. A small environment (10–20 servers, simple applications) can complete migration in 4–8 weeks. A medium enterprise environment (50–200 servers, multiple applications, some databases) typically takes 3–6 months. Large enterprise migrations (200+ servers, complex interdependencies, regulatory requirements) typically run 6–18 months across multiple waves. The timeline is driven by dependency complexity, data volumes, testing requirements, change management processes, and whether applications require refactoring for cloud-native services. MaximyzCloud uses a wave-based approach — migrating in prioritised groups with validation at each stage — rather than a single cutover, which reduces risk and typically shortens the total elapsed time.

Virtually any workload can be migrated to Google Cloud. Virtual machines running Windows or Linux can be migrated directly to Compute Engine using Migrate to Virtual Machines. Containerised workloads move to GKE or Cloud Run. Databases including MySQL, PostgreSQL, SQL Server, Oracle, MongoDB, and Cassandra have migration paths to Cloud SQL, AlloyDB, Bigtable, or Firestore. Analytics workloads migrate to BigQuery. Batch processing moves to Dataproc or Dataflow. Development and test environments, web applications, APIs, microservices, and data pipelines all have well-supported migration paths. The main considerations are applications with very specific hardware dependencies, mainframe workloads requiring emulation, and applications subject to data residency regulations requiring specific geographic placement — all of which can be addressed with appropriate GCP region and service selection.

MaximyzCloud minimizes migration downtime through several techniques — parallel-run migration keeping both environments running simultaneously while GCP is validated; replication-based database migration using DMS continuous replication so the GCP database stays synchronized with the source right until the final cutover; traffic switching using Cloud Load Balancing to progressively shift traffic (1% → 10% → 50% → 100%) with monitoring at each increment and instant rollback capability; scheduled maintenance window cutover for workloads that need a brief downtime, typically outside business hours; and wave-based migration moving non-critical workloads first to validate the process before migrating business-critical systems. For most stateless web applications, we achieve zero-downtime migration. Stateful applications and databases typically have a brief planned cutover window of 15–60 minutes.

MaximyzCloud delivers GCP migration through a structured 6-phase engagement — Discovery (workload inventory and dependency mapping), Assessment (TCO analysis, strategy selection, risk scoring), Architecture Planning (Landing Zone design, Terraform IaC, network and IAM architecture), Migration (wave-based workload migration using GCP tooling), Validation (functional testing, performance benchmarking, security review), and Optimisation (cost tuning, committed use discounts, monitoring setup). Our certified GCP architects work alongside your teams — providing the cloud expertise and migration tooling to accelerate delivery while your teams maintain business continuity. We deliver Terraform infrastructure code, runbooks, and documentation your team can maintain long after the engagement ends, building genuine internal GCP capability rather than consultant dependency.