Moving to the cloud used to be a simple promise: shift your workloads out of the data centre, lower your capital expenditure, and unlock instant agility. For most engineering leaders, that first move was a brute-force “lift and shift.” It got you there. But today, the cloud landscape looks completely different.
Whether driven by AI readiness, rising costs, regulatory pressures, moving workloads from one cloud provider to another or modernising existing multi-cloud environments, presents a fundamentally different operational challenge.
You aren’t just moving static servers anymore. You are shifting live, interdependent ecosystems across different pricing models, unique proprietary services, and complex security posture constraints, all with zero tolerance for downtime.
In Part 1 of our webinar series, Beyond the Lift and Shift: Mastering Cloud-to-Cloud Migrations, Scale Factory Technical Director Mike Mead and Principal Consultant Chris Musther unpacked the strategic, financial, and technical realities of moving between clouds.
Here are the key takeaways every CTO, CIO, and engineering leader needs to keep top of mind:
Cloud-to-Cloud Isn’t a Lift & Shift – It’s an Architecture Reset
When migrating on-premises infrastructure to the public cloud, the path of least resistance was often mirroring virtual machines straight into EC2 or Compute Engine. Moving cloud-to-cloud shifts the goalposts entirely:
- Feature parity is an illusion: AWS, Azure, and GCP solve similar problems with entirely different underlying abstractions, IAM primitives, and networking models.
- Live systems can’t stop: You are migrating production systems with active users, constant data mutations, and strict SLA commitments.
- Re-platforming vs. Re-architecting: You shouldn’t rewrite every microservice from scratch, but blindly copying configuration files across cloud providers guarantees technical debt and unexpected bills.
KEY TAKEAWAY
Successful cloud-to-cloud migration requires proven migration patterns, such as strangle-fig deployments, incremental data replication, and abstraction layers, that let you move critical workloads safely without hitting pause on business-as-usual.
Don’t Leave AWS Co-Investment Money on the Table
One of the biggest friction points for C-suite leaders contemplating a cloud migration is the double cost: paying for existing cloud infrastructure while concurrently funding the build and execution of the new platform. What many tech leaders miss is that cloud hyperscalers actively subsidise these migrations, but only if you know how to navigate their partner ecosystems.
- AWS Migration Acceleration Program (MAP): As an AWS Advanced Consulting Partner, we regularly help clients unlock co-investment funding that directly offsets migration discovery, proof-of-concept, and execution costs.
- Commercial Negotiation: Migrating workloads gives you significant leverage. Aligning your migration roadmap with hyperscaler commitment milestones can yield substantial upfront credits and long-term volume discounts.
KEY TAKEAWAY
High migration costs shouldn’t be a dealbreaker. With the right partner and co-investment structure, a significant portion of your migration services and parallel running costs can be offset directly by the provider.
Solve Data Sovereignty and Security Early, Without Adding Complexity
For risk-sensitive, regulated organisations (financial services, healthcare, public sector), compliance and data sovereignty are usually the biggest hurdles to migration velocity.
When moving between clouds, security models don’t translate 1:1. Identity and Access Management (IAM), encryption key management (KMS), and network perimeters must be mapped meticulously to maintain continuous compliance.
The trap most engineering teams fall into is over-engineering: layering security tool upon security tool until deployment speed grinds to a halt.
How to get it right:
- Bake compliance into code: Use Infrastructure as Code (IaC) templates and automated policy enforcement (Policy-as-Code) from day one.
- Design for sovereign boundaries: Ensure data residency, replication paths, and failovers strictly adhere to regulatory jurisdiction without creating brittle inter-region dependencies.
- Maintain continuous auditability: Ensure quality engineering and automated security scanning are embedded directly into your CI/CD pipelines.
Eliminate Cloud Waste Before It Multiplies
If you migrate unoptimised workloads, you simply import inefficient spend into a new environment. Cloud-to-cloud migrations offer a rare “circuit breaker” moment to audit your real estate, identify zombie assets, and eliminate cloud waste before laying the foundation for next-generation capabilities like agentic AI and automated data pipelines.
Key areas to target:
- Right-sizing compute: Align instance types and auto-scaling logic with actual workload demand patterns rather than historical over-provisioning.
- Storage tiering: Offload cold data and unindexed logs into cheaper long-term storage tiers.
- Architectural optimisation: Shift non-core background tasks to serverless or containerised orchestration where pay-per-use economics apply.
