Case study
Cutting Elastic Cloud Costs for a Fashion Retailer
How SquareShift moved a global fashion retailer's Elasticsearch workloads to Elastic Cloud without code changes, cutting always-on cluster costs.
A global fashion and lifestyle retailer running multiple high-profile brands on an on-premises Elasticsearch cluster sized for peak season.
The cluster stayed over-provisioned year-round, driving cost even in the slow months.
Baseline cluster nodes, down from 22 always-on nodes at peak. Elastic Cloud migration completed without touching the legacy application layer. Secure, cost-efficient architecture connected to existing AWS infrastructure.
Key servicesHow SquareShift delivered it.
The challenge
The retailer ran a large, on-premises Elasticsearch cluster sized for its busiest shopping days — 22 nodes at peak — but paid for that footprint every day of the year, even in the off-season. Its legacy, Microsoft-based application layer meant any migration path had to work without touching existing integration code.
What we delivered
SquareShift migrated the retailer’s Elasticsearch workloads to Elastic Cloud with full compatibility for the existing architecture, so the application layer needed no code changes. The team tuned index performance for cloud-native scaling, configured secure network routing between AWS and Elastic Cloud, and applied ILM and cluster-sizing best practices to cut resource usage.
The payoff
The cluster now runs on a 2-node baseline day to day and scales dynamically only when seasonal demand requires it, replacing the always-on 22-node setup. The retailer kept its existing integration code, secure AWS connectivity, and a lower cloud bill outside peak season.
Sizing a cluster for peak season and running it year-round is the default retail mistake. Dynamic scaling is what actually pays for a cloud migration.
Cloud Modernization Practice Lead, SquareShift
Where this work sits