Across Microsoft, AWS and Google Cloud
Littlefish Group delivers cloud migration and optimisation solutions across Microsoft Azure, AWS and Google Cloud Platform. Our scope covers estate assessment, workload migration and the cost and performance optimisation of your cloud estate.
We assess each workload against the destination cloud platform, map application dependencies and design the target architecture. The output is a workload-by-workload roadmap with effort, cost and risk for each workload, together with the migration sequence, evaluation criteria and rollback approach the engineering team follows during delivery.
Migration of applications, databases, workloads and integrations to Azure, AWS or Google Cloud Platform. We select the migration approach for each workload, whether lift-and-shift, refactor or re-platform, based on the destination architecture and the cloud-native services available. The team handles the engineering, testing and cutover, with named owners on both sides through go-live.
Monthly review of cloud spend through Microsoft Cost Management, AWS Cost Explorer and Google Cloud Billing, alongside performance optimisation against the workloads and SLAs your business depends on. Reserved capacity, savings plans, right-sizing and tagging are configured against your actual usage patterns and adjusted each month as workloads change
Migration to hybrid architectures where regulatory, latency or data residency requirements keep part of the estate on-premise or in private cloud. We design the network architecture, identity federation, data replication and security controls across the boundary, so the hybrid environment operates as a single platform across on-premise, private and public cloud.
Migration plans built from infrastructure inventory rarely reflect the real dependency graph between applications, integrations and data stores. Workloads move on schedule but break in production because upstream systems were not part of the migration scope. Our consultancy maps dependencies during discovery and sequences the migration against them, with named owners for each workload from assessment through to go-live.
Cloud spend typically rises 20 to 40 percent in the six months after migration as workloads grow, new services are provisioned and reserved capacity expires unrenewed. The cost case made at business approval erodes within a quarter. Our cost optimisation reviews spend, performance and capacity each month against the baselines agreed at go-live, with right-sizing adjusted to match actual usage.
Choosing Azure, AWS or Google Cloud before assessing the workloads that need to move locks the migration into integration patterns, pricing models and feature availability that may not fit. Our assessment evaluates each workload against destination criteria, with integration patterns, data sovereignty and cost factors weighed before any platform commitment is made. The result is a platform selection driven by the workloads themselves.
Every cloud migration engagement runs to defined outcomes, measured against the success criteria agreed at discovery. We take responsibility for getting workloads from on-premise onto the destination cloud platform and into stable production at go-live.
We make platform decisions against your workloads, existing estate and team’s skills, with no vendor preference. Six advanced Microsoft specialisations, AWS Managed Services Partner status and Google Cloud Platform partnership.
Our consultants and engineers operate as a single team. The people who design the migration architecture are the same people who build and deploy it, with named owners on both sides from discovery through go-live.
Cost, performance, security and governance are designed in from discovery onwards. Engagements meet UK GDPR, the Data Protection Act and NCSC guidance at go-live, with audit-ready evidence prepared during delivery.
