Reported impact
Business outcome
Instana helped the OMS team get through the 2024 holiday peak without major incidents, sustain huge order and API loads, and support better client retention and support metrics while Sterling’s AI engine optimized millions of order decisions for retailers.
- Customer Experience
- Productivity Improvement
- Revenue Growth
- Scalability
Solution
IBM migrated Sterling OMS from a competing monitoring tool to IBM Instana so the service could observe and optimize its multitenant retail workload end to end. The SaaS platform itself runs real-time order and inventory management across more than 400 customizable environments on IBM Cloud Kubernetes Service, backed by IBM Db2, NoSQL stores, Cassandra, MongoDB, Elastic Search, IBM MQ, Kafka, Istio service mesh, and an Apache Spark/Iceberg lakehouse used for AI workloads. Instana collects telemetry across those components so the team can see every touchpoint and integration in real time, identify issues proactively, and protect the 99.9999% uptime commitment. During holiday peaks, Sterling’s AI engine uses live demand and inventory signals to optimize order sourcing while Instana absorbs nearly a million spans per second, giving the team the operational visibility needed to keep fulfillment systems stable at retail scale.
Data flow
Retail orders, inventory events, and API traffic enter Sterling OMS through its Kubernetes-hosted microservices and messaging layers, persistent data lands in Db2 and related stores, Spark and the lakehouse support optimization workloads, and Instana continuously ingests telemetry so the team can see performance and resolve issues across the whole fulfillment path.