We architect and execute cloud migrations to AWS, Azure, and GCP — designing for AI workloads from day one with multi-cloud flexibility, zero-downtime cutover strategies, and immediate cost optimisation baked into the target architecture.
AWS · Azure · GCP · Terraform · Kubernetes · Zero-downtime Migration · FinOps
Most cloud migrations focus on lifting what exists. We design target architectures that are ready for AI — the right compute instances, storage patterns, networking topology, and data access layers so your future ML pipelines and LLM deployments don't require a second migration.
We inventory your existing infrastructure, map inter-service dependencies, classify workloads by migration approach (rehost, replatform, refactor, retire), and identify AI/ML workloads that need GPU compute or specialised infrastructure. The output is a dependency map and migration wave plan your team can execute with confidence.
We design the target cloud architecture for your specific requirements — choosing between single-cloud and multi-cloud, selecting the right managed services (RDS vs Aurora vs Cosmos DB), designing VPC/VNet topology, and documenting everything in Infrastructure as Code using Terraform so the architecture is reproducible and auditable.
Cloud security must be designed in, not added on. We implement least-privilege IAM policies, encryption at rest and in transit, network segmentation, secrets management, and security monitoring from the start. Compliance controls for SOC 2, ISO 27001, GDPR, and HIPAA are mapped to cloud controls and documented in runbooks.
Migrations carry real business risk. We use blue-green, strangler-fig, and database replication patterns to maintain full service continuity during cutover — with automatic rollback triggers and smoke test suites that verify each migration wave before traffic is shifted.
We run your new cloud environment in parallel with your existing infrastructure, gradually shifting traffic by percentage while monitoring error rates, latency, and business KPIs. If any signal degrades beyond threshold, traffic shifts back automatically. Full cutover only happens after all metrics confirm the new environment is stable.
Database migrations are typically the highest-risk element. We use CDC (Change Data Capture) tools — AWS DMS, pglogical, Debezium — to set up live replication between source and target, minimising the cutover window to minutes rather than hours of downtime. Data integrity validation runs automatically on both sides before cutover is approved.
Cloud overspend is endemic. Without active FinOps practices, costs balloon. We implement rightsizing, Reserved Instance strategies, Spot/Preemptible usage for AI training, and tagging taxonomies that give you per-team, per-product cost visibility from day one.
We audit your resource utilisation patterns to identify oversized instances, idle resources, and usage that qualifies for Reserved or Savings Plan pricing. Typical rightsizing engagements reduce compute costs by 30–50% without any loss in performance — and Reserved capacity for stable workloads delivers a further 30–40% discount over on-demand pricing.
Cost visibility requires consistent resource tagging. We implement and enforce a tagging taxonomy across all cloud resources — by team, product, environment, and cost centre — and set up showback dashboards so each team sees their spend. Budget alerts and anomaly detection automatically flag unexpected spikes before they compound.
Book a free cloud readiness assessment. We'll map your current infrastructure, identify migration risk areas, and produce a phased plan with cost projections.