Cloud Infrastructure
Scalable architectures on AWS, Azure, and GCP — designed for your workload, not the vendor's.
The platform shapes the team
Your infrastructure choices have a quiet effect on team velocity. Managed everything = small platform team but higher monthly bills. Self-managed Kubernetes = lower marginal cost but you’re hiring SREs. We help you make this call honestly, then we build what you decided on.
A typical engagement covers:
- Network design — VPC layout, subnet sizing, NAT vs egress gateways, peering, DNS strategy. The thing nobody wants to redo later.
- Identity boundaries — accounts/projects/subscriptions per environment, SSO from your IdP, IAM roles with least privilege, secrets rotation that doesn’t break things.
- Compute platform — picking among Lambda/Cloud Functions, ECS/Cloud Run, Kubernetes, or VM-based depending on your workloads. Most teams need a mix.
- Observability — CloudWatch/Stackdriver/Azure Monitor wired to your dashboards + paging tool. Cost dashboards alongside operational ones.
- DR + backup — RTO/RPO targets, snapshots, cross-region copies, tested restore procedures (the part everyone skips).
When this fits
You’re starting fresh and want it built right. Or you’ve inherited a cloud account that grew organically and is now a sprawl with no IaC, mystery costs, and IAM permissions nobody understands.
Questions about Cloud Infrastructure.
Depends on your existing skills, vendor relationships, and workload. AWS is the safe default (broadest service catalog, biggest talent pool). GCP wins for data + ML-heavy stacks (BigQuery, Vertex AI). Azure wins for enterprises with M365/AD already in place. We've delivered on all three; happy to recommend based on your situation.
Usually no. Multi-cloud doubles the operational surface and rarely buys real DR benefit (clouds fail in ways your DR plan didn't anticipate either). We use multi-cloud when there's a specific reason: a managed service only available on one cloud, regulatory requirement, or vendor risk reduction at scale. Otherwise stay on one.
Right-sized compute (no 4xl instances for a workload that needs xl), reserved/savings plans modeled for predictable workloads, lifecycle policies on storage, deletion of unused snapshots/volumes/IPs, and a tagging strategy that lets finance attribute spend to teams. Most clouds are 30–50% overprovisioned by default.
Yes. Migrations are usually in three phases: lift-and-shift (running on cloud but unchanged), re-platform (using managed services for stateful pieces), and re-architect (going cloud-native where it pays off). We typically scope only the first two and leave re-architecture as separate engagements per system.
Ready to talk about Cloud Infrastructure?
Tell us about your project. We respond within 24 hours.
[email protected]