Holiday peaks that test the platform
Capacity, scaling limits and dependencies that only show up on the busiest days of the year.
← Industries
Retail and commerce technology
Technology-led retailers, commerce platforms and commerce software vendors with meaningful digital operations on AWS.
Common problems
Commerce means spiky traffic, many data sources and money changing hands, so architecture, data and payments experience all matter.
Cost that spikes with traffic and stays
Infrastructure sized for peak all year, and spend that grows faster than orders.
Orders, inventory and customers in too many places
Commerce, marketplace, fulfilment and marketing systems disagree, so reporting and AI start from untrusted data.
Merchandising and finance dashboards that lag
Slow queries and late loads mean decisions are made on yesterday's numbers.
Search, recommendations and service AI
Use cases that need evaluation, cost limits and a clear owner before they reach customers.
Payments and checkout reliability
Where commerce meets payments: settlement, reconciliation and resilience, our deepest area of experience.
A typical engagement path
For a commerce platform that struggled last season. Each step is a separate decision.
- 1
Cloud Cost Review (2–3 weeks)
Cloud health and cost review: what scales, what is sized for peak all year, and who owns each cost.
- 2
Architecture Review (2–4 weeks)
Architecture and risk assessment of the order path: limits, dependencies, recovery and a load-test plan.
- 3
Modernization Sprint (4–8 weeks)
A focused sprint on the riskiest component, with scaling tested against agreed peak volumes.
- 4
Your team owns it
Runbooks, scaling policies, a peak checklist and a cost view by channel.
Relevant services
Cost
Cloud Health, FinOps & Governance Review
Cost and capacity that follow demand instead of the busiest day of the year.
Where the savings usually are →DesignTarget Architecture, Resilience & Security
An order path designed for peak volumes, failure and recovery.
What the roadmap includes →ImproveReliability, DevOps & Developer Platform
Safer releases before and during peak trading periods.
What we would change →DataData Platform / Lakehouse Foundation
One governed view of orders, inventory and customers.
How we build it →AnalyticsData Engineering, Quality & Analytics Performance
Reporting that is complete and on time, with tested pipelines.
What we fix first →AIGenerative AI Discovery & Production Readiness
A go or no-go decision for one commerce AI use case.
From prototype to production →Fit
Selective, problem-led work
We take on retail and commerce work where there is a clear technical trigger, meaningful digital operations on AWS and a named owner.
Strength
Where commerce meets payments
Checkout, settlement and reconciliation draw on the same experience we bring to payments companies.
Not for us
What we don't do
Store operations, ERP or point-of-sale implementations, marketing-technology selection or broad retail transformation programs.
Further reading
Commerce · Field guide
Peak readiness on AWS: a 12-week plan
Forecast, order-path limits, load tests, capacity reservations and runbooks before your busiest days of the year.
Payments · Field guidePayment reconciliation on AWS
How to match orders, processor settlements and bank deposits, and turn breaks into an exception workflow.
Data & AI · Field noteYour AI project is a data project
The four questions to answer before a recommendation or service assistant goes live.
Planning for your next peak?
Start with a Cloud Health review of the order path, or tell us about the data or AI problem you need to solve.