Case study · Retail
Tens of thousands of stores,one release pipeline.
A global health and beauty retail enterprise operating at scale across physical stores and digital channels. It runs tens of thousands of retail locations across multiple markets and supports complex online-to-offline operations, serving a very large consumer base through high-traffic digital platforms. Its systems span merchandising, inventory, membership, order management and customer engagement, all of which have to run continuously. As the business scaled, manual processes, fragmented tooling and limited observability slowed delivery and issue resolution.
Constraints and answers
Campaign peaks, continuous uptime, and manual scripts in between.
The platform that scales itself and heals itself.
Low delivery efficiency
Delivery processes lacked unified, automated pipelines, which made releases slow and inconsistent.
Answer
Cloud-native elastic scaling and self-healing
Elastic scaling and self-healing mechanisms to improve platform stability and take the manual work out of recovery.
Insufficient elasticity during campaigns
Demand spikes during marketing activity required elastic scaling that legacy virtual machine deployments could not provide.
Answer
End-to-end monitoring across the full stack
Monitoring from gateways through applications, middleware and databases, which is what makes precise microservice management possible.
Manual operations slowing issue resolution
Operations relied on manual scripts, which lengthened response times whenever something went wrong.
Answer
DevSecOps pipeline integration
Security integrated throughout the development and deployment pipelines rather than inspected at the end.
No microservice monitoring or governance
Without proper monitoring and governance, fault localization and recovery were slow.
Answer
Standardized end-to-end cloud processes
Standardized cloud processes simplify operations and let internal teams run the platform independently.
Standardized process is what lets the retailer’s own team run the platform.
The results
A 99.99% SLA on core retail, and 92% more builds a day.
- 46%
- FEWER DEPLOYMENT ISSUES
- Automation and standardized process cut deployment problems.
- 92%
- INCREASE IN DAILY BUILD VOLUME
- Automated pipelines raised daily build throughput.
- 55%
- BETTER RESOURCE UTILIZATION
- Cloud-native resource management across the platform.
- 99.99%
- CORE BUSINESS SLA
- Reliability at the level core retail services need.
- 20%
- REDUCTION IN RESOURCE COST
- Lower cost for the same retail workloads.
Five numbers, and the one the board reads is the 99.99%.
The stack
What was deployed
PLATFORM
Sovereign Cloud Platform
The cloud-native foundation for microservice governance, DevOps and DevSecOps pipelines, observability and standardized cloud operations.
INFRASTRUCTURE
Sovereign Virtualization
The scalable compute, storage and networking behind elastic scaling and high-availability retail workloads.
역량에 관한 노트
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