One-third of the world's population now shops online, accounting for more than 20% of global retail sales annually. For every one of those billions of physical products sold, a corresponding set of product data is required to accurately describe it in a digital storefront. The challenge is that every supplier structures and describes product data differently. Managing this vast and inconsistent data landscape can be a major operational burden for retailers. That's why many leading international retailers turn to Onedot. Its AI-powered platform automates the sourcing, onboarding, enrichment, and syndication of product data at scale. More than 500 million products have already been processed by Onedot's AI, helping retailers improve product discoverability, enhance the customer experience, and significantly reduce operational overhead.
Onedot needed automatic, elastic scaling to maximize compute efficiency and optimize cloud spend without allowing costs to grow unpredictably. The company was having issues with cost management across AWS workloads and needed resource planning and architectural guidance.
DoiT implemented a two-pronged approach: conducting an AWS Well-Architected Review and optimizing resource usage. The solution included implementing Flexsave for Compute to automate AWS Savings Plans coverage, using DoiT Console for deeper visibility, and migrating from Amazon EMR to Amazon EKS after thorough cost analysis.
We were having some issues with cost management across our AWS workloads. We turned to DoiT for help with resource planning and architectural guidance so we could get the most from our data processing on AWS while keeping our cloud bill under control.
Tobias Widmer, Founder and CTO of Onedot
Onedot's first step toward optimizing cloud spend was implementing Flexsave for Compute, automating the management of AWS Savings Plans coverage to continuously maximize commitment-based discounts. This enables Onedot to scale workloads up or down without unexpected bill spikes and without manually adjusting commitments. The automated approach provides predictable cost management while maintaining operational flexibility.
Onedot began using the DoiT Console to gain deeper visibility into AWS cloud usage. Working alongside DoiT consultants, the team implemented automated alerts to detect unusual usage patterns likely to increase costs. With these insights, Widmer and his team collaborated with DoiT to analyze spending patterns and refine AWS infrastructure design to improve cost efficiency and operational performance.
A major strategic discussion centered on Onedot's use of Apache Spark on Amazon EMR. The team evaluated whether migrating to a self-managed Kubernetes cluster—or running Spark on Kubernetes—could reduce cloud expenditure. In collaboration with DoiT, Onedot conducted an in-depth cost comparison of various architectural approaches. Ultimately, the team determined that using Amazon EKS, AWS's managed Kubernetes service, would be more cost-effective than continuing with EMR or managing a self-hosted Kubernetes cluster.
Within the first three months of engagement, Onedot reduced its AWS cloud expenditure by more than 20% through Flexsave for Compute and architectural rebalancing. The company continues working with DoiT to strengthen its security posture in preparation for international ISMS certifications while refining the architecture to improve efficiency, performance, and platform stability. These improvements enable Onedot to process and deliver product data faster and more reliably while operating with a leaner and more cost-efficient cloud infrastructure.
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