New: CentriCall AI voice agents that answer, qualify, and book around the clock
Cloud Solutions foreCommerce

eCommerce cloud architecture that survives the day you make the money

Retail infrastructure is judged on about four days a year. We design and load test against those days, and we make sure the bill afterwards is one you predicted.

What changes here

Cloud Solutions in eCommerce is not the same engagement

Load tested against your own peak, before it arrives

Traffic modelled from last year's sale and pushed through the real checkout path — because the failure is almost never on the product page.

Edge and cache strategy per page type

Product and category pages cached hard, cart and checkout deliberately not, with invalidation that a merchandiser can trigger without a deploy.

Cost controls that hold during a spike

Autoscaling with ceilings, budget alarms, and per-service attribution, so a traffic event does not become a finance conversation in January.

The failure mode worth designing against

eCommerce outages concentrate at checkout under load, and every minute is directly attributable revenue. The architecture decisions that prevent it are made months earlier.

  • Checkout paths isolated so a failing recommendation service cannot take orders down
  • Queue-based handling of inventory and payment callbacks under burst
  • PCI DSS scope minimized through tokenization and hosted payment fields
  • Consumer privacy rights under CCPA and PIPEDA honoured across every data store the migration touches

Assessment, landing zone, and target architecture

An inventory of what you run, a dependency map, and a landing zone with accounts, networking, identity, and guardrails set up before the first workload moves.

Migration and modernization in waves

Applications moved in dependency order — rehost where it earns nothing to change, re-architect to managed services and containers where it pays for itself.

Cloud-native application development

Serverless and container workloads, managed databases, queues, and event-driven services built for the platform rather than ported onto it.

FinOps and cost optimization

Tagging, budgets and alerts, rightsizing, savings plans, and idle-resource cleanup — spend attributed to a team and a service, reviewed monthly.

Resilience, backup, and tested recovery

Multi-AZ design, backup policy, and restores actually rehearsed against an agreed RTO and RPO instead of assumed.

Observability and cloud security posture

Metrics, logs, and traces in one place, with IAM least privilege, encryption, and posture checks running continuously rather than at audit time.

eCommerce questions we get asked

Something more specific? Send us the situation and we’ll answer it straight.

By pushing modelled peak traffic through the real checkout path in a production-like environment and fixing what breaks. Confidence without a load test is a guess, and the checkout is where guesses fail.
Usually autoscaling without ceilings, scaled-up capacity nobody scaled back, and data transfer nobody attributed. Budgets, alarms, and per-service tagging turn that from a surprise into a number you watched.
Often, yes. Much of the peak-day risk lives in infrastructure, caching, and the integration path to ERP and payments rather than in the storefront platform itself. We measure before recommending anything as expensive as a replatform.