Amazon Web Services gives you the broadest catalogue of managed compute, storage, and data services, but a rushed migration leaves you with sprawling bills and brittle architecture. We assess each workload, design a secure multi-account landing zone, and move applications in waves so your teams keep shipping throughout the project.
We start by inventorying every server, database, and dependency, then map each workload to the right approach: rehost, replatform, or refactor. Application-discovery tooling surfaces traffic patterns and undocumented links so nothing is missed at cutover. The output is a wave plan that sequences low-risk workloads first, defines rollback steps for each move, and sets clear success criteria. You get a costed roadmap before a single resource is provisioned, so budget owners can approve with confidence.
Before workloads arrive we build a multi-account foundation using AWS Organizations, with separate accounts for production, staging, and shared services. Guardrails enforce encryption, logging, and tagging from day one, while IAM roles and permission boundaries replace long-lived keys. Centralised CloudTrail, GuardDuty, and Config give you an audit trail and continuous compliance checks. This structure keeps blast radius small, simplifies cost allocation per team, and means later workloads slot into a governed environment instead of an ungoverned sandbox.
We match each workload to appropriate EC2 instance families, move relational databases to RDS or Aurora, and shift object data to S3 with lifecycle policies that tier cold data to cheaper storage. Auto Scaling groups and load balancers replace fixed capacity so you pay for demand, not peak guesses. Where it fits, we introduce managed services such as ElastiCache or SQS to remove undifferentiated maintenance. The result is a footprint sized to real usage rather than a like-for-like copy of old hardware.
Each migration wave runs through a rehearsed cutover with data sync, smoke tests, and a defined rollback window. We validate performance against baselines captured before the move and confirm monitoring, alerting, and backups are live before declaring a workload done. After go-live we document the architecture, hand over runbooks, and optionally train your engineers on day-two operations. You leave the engagement with a stable AWS estate your own team can confidently run.
Yes. We migrate in waves with data synchronisation and rehearsed cutovers, scheduling each move into a maintenance window with a tested rollback. Most workloads experience only a brief, planned switchover rather than extended downtime.
Often, yes. Many workloads can be rehosted or replatformed onto managed AWS services with little code change. We reserve refactoring for cases where it clearly improves resilience or cost, and we flag those trade-offs before any work begins.
We right-size instances, apply storage lifecycle policies, and enable per-account cost allocation tags. You receive a baseline cost report and recommendations for Savings Plans or Reserved Instances once usage patterns settle.
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Package applications into lean, reproducible Docker images with secure, multi-stage builds.
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Harden cloud estates with least-privilege identity, encryption, and continuous compliance monitoring.
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Contact our team and we will send the best implementation plan for your business.