Cloud

Cloud Foundations for Modern Enterprise Workloads

Cloud Engineering Practice

Sakura Sky's Cloud Practice helps organisations build, modernise, and operate the cloud platforms their data, security, and intelligence workloads depend on. We have delivered production cloud engineering for more than a decade across the major public cloud providers.

We focus on architecture that holds up under real-world growth, automation that removes ambient toil, cost discipline that survives the modern inference bill, and the operational resilience that lets your teams ship without inheriting risk.

Our work pairs cloud-native engineering with the security substrate of our Enclave framework and connects directly to our GRC service where the regulatory frame drives the architecture. For sprint-shaped builds, our Accelerate programme delivers a production-ready prototype in your environment.

Where We Engineer

Cloud Capability

Cloud Architecture & Modernisation

We design and deploy secure, scalable architectures and modernise existing workloads using managed Kubernetes, serverless platforms, and hybrid or multi-cloud designs. Our team runs complex migrations from legacy or first-generation cloud stacks, including application containerisation, virtualised workloads, and database migration. Where data residency or sovereignty obligations apply, we design multi-region deployments that satisfy them without sacrificing the architectural coherence that lets the platform scale.

Infrastructure Automation & DevOps

We build CI/CD pipelines, artifact repositories, and IaC foundations (Terraform, Pulumi, or native equivalents) that automate deployment and operations. Policy-as-code frameworks integrate with cloud-native observability so reliability, security, and cost discipline improve continuously. GitOps and shift-left automation accelerate release velocity while keeping compliance and control intact from the first commit.

FinOps & Cost Discipline

We give organisations clear visibility and governance over cloud spend, with a particular focus on the AI inference and GPU costs that dominate modern cloud bills. Our FinOps practice uses native cost management, commitment planning, and predictive rightsizing to drive measurable savings without slowing engineering. The discipline applies equally to traditional compute, storage, data egress, and the per-token economics of AI features.

Data & AI Platform Integration

We integrate cloud data warehouses, real-time streaming services, and native AI platforms into the cloud foundation so analytics and agentic workflows have somewhere reliable to live. Our engineering ensures governance, lineage, and reliability flow through the platform, and our close work with cloud-provider specialists keeps deployments production-ready. Pairs naturally with our Data & AI Practice.

Differentiators

What Makes Our Cloud Practice Different

Sakura Sky pairs deep technical bench with proven delivery frameworks. Our differentiation is in execution, not in slideware.

Cloud-native delivery

We deliver through cloud-native engineering, with certified specialists across AWS, Google Cloud, and Azure. Our teams design, implement, and optimise environments using provider-native tools and the practices each platform actually rewards, so performance, reliability, and compliance are built in from day one.

Full-stack capability

Our integrated practice spans cloud, data, AI, and security operations, so we design connected systems rather than handing off between specialist silos. The same engineers who design the platform are the ones who secure it, instrument it, and run it.

Shift-left automation

We embed reliability, security, and governance early in the development lifecycle through automation rather than process. Compliance and optimisation are wired into CI/CD and infrastructure pipelines, so teams reduce risk, ship faster, and maintain operational quality without adding overhead.

Modernisation that actually lands

Our modernisation playbooks and automation frameworks are tested in production. Repeatable methodologies shorten timelines, reduce risk, and create cloud foundations that evolve alongside the business rather than calcifying into the next legacy stack.