Cloud migration remains one of the highest-stakes IT projects an enterprise can undertake. Done well, it unlocks performance, cost efficiency, and the infrastructure needed to support AI and modern applications. Done poorly, it creates outages, cost overruns, and security vulnerabilities. Here's the checklist we use with every client.
Phase 1: Readiness Assessment
Before writing a single line of infrastructure code, complete a thorough readiness assessment. Inventory your current application portfolio and categorize each by migration complexity. Identify dependencies between applications — these are the most common source of migration surprises. Assess your team's current cloud skills and identify gaps that need to be filled before go-live.
Phase 2: Architecture Design
Determine your target architecture: public cloud, private cloud, or hybrid. Select your cloud provider based on your specific workload requirements, compliance needs, and existing vendor relationships. Design your network architecture including VPCs, subnets, security groups, and connectivity back to any on-premise systems that will remain.
Phase 3: Security and Compliance Configuration
This phase is where many migrations run into trouble. Configure identity and access management from the start — it is far harder to retrofit security controls after migration. Implement encryption for data at rest and in transit. If you operate in a regulated industry, map your compliance requirements (HIPAA, SOC 2, PCI-DSS) to specific cloud configuration requirements before you begin migrating workloads.
Phase 4: Migration Execution
Migrate in waves, starting with the lowest-risk, lowest-complexity applications. This builds team confidence and reveals unexpected issues before they affect critical systems. Maintain parallel operation of old and new environments during the transition period. Define clear rollback procedures for each application before you migrate it.
Phase 5: Optimization and Ongoing Management
Migration is not the finish line — it is the starting line for optimization. Review cloud costs monthly and right-size resources based on actual utilization. Implement automated scaling to handle variable workloads efficiently. Establish monitoring and alerting so your team knows about issues before users do.