From “it works” to “it scales”, let’s move your tech forward

Start with a formal cloud readiness assessment: inventory apps, databases, integrations, and map them to business criticality, technical complexity, and compliance requirements. Low-coupled, stateless, web-facing services with standard databases are usually early migration candidates, while tightly coupled legacy systems or those with strict latency/hardware constraints may stay on‑prem longer. Score each workload on factors like performance needs, data sensitivity, dependency sprawl, and expected cloud benefit, then prioritize into migrate-now, modernize-then-migrate, or retain buckets.

Use provider calculators (AWS/GCP/Azure) to simulate IaaS (VMs), PaaS (managed DB/app services), and serverless (per-request) options based on your current CPU hours, storage, and traffic patterns. Model at least three architectures (lift-and-shift, replatformed, refactored/serverless) and include networking, backups, monitoring, and support tiers, not just compute. Run short PoCs in each model to measure real utilization and apply discounts (reserved instances, savings plans) to see true 12–36 month TCO before committing.

Plan a phased migration with non‑critical workloads first, then critical systems using blue‑green or canary cutovers via DNS/traffic shifting. Set up real‑time data replication (CDC for databases) so the target stays in sync until cutover, and rehearse full migrations in a sandbox to validate performance, security, and rollback paths. Schedule cutovers in off‑peak windows, run dual‑running (old + new) for a stabilisation period, and monitor closely with alerts to trigger automated rollback if SLAs degrade.

Deploy discovery and APM/network analysis tools to capture call graphs, database connections, message queues, and external APIs between services. Combine this with interviews and documentation reviews to confirm hidden dependencies like batch jobs, reports, or shared file systems. Cluster tightly coupled components into migration “waves” and design each wave so its critical upstream/downstream dependencies move together or are bridged via VPNs, proxies, or integration layers during transition.

For discovery/assessment, use platform-native tools (e.g., AWS Application Discovery, Azure Migrate) plus third‑party assessment platforms when estates are large or multi‑cloud. For bulk data transfer, choose tools like Snowball/Transfer Appliance or high‑throughput online transfer plus checksum validation. For databases, pick managed migration services (AWS/Azure/GCP DMS) with CDC, or enterprise tools (Hevo, Integrate.io, Informix) when you need heterogeneous support and near‑zero downtime.

In the first 6 months, stabilize: tighten security, complete basic rightsizing, implement monitoring/alerting, and fix any performance regressions. In 6–12 months, focus on optimization: adopt PaaS/serverless where appropriate, implement formal FinOps practices, and introduce auto‑scaling, caching, and resiliency patterns. Between 12–24 months, modernize further: refactor remaining legacy workloads, deepen automation (IaC/CI‑CD), and upskill teams with continuous training and playbooks aligned to cloud‑native operations.​