Scaling Data-Intensive Workloads in Cloud Environments

This technical report outlines the challenges and strategies associated with scaling data-intensive workloads in cloud environments. It begins by identifying common challenges faced by teams as data volumes and processing demands increase, such as storage performance constraints, cost predictability issues, and compliance complexities. The report presents a technical design checklist that assists organizations in making informed infrastructure decisions based on their specific workload characteristics. This includes considerations for storage models, compute requirements, networking needs, and compliance with data residency regulations. Furthermore, the report details deployment examples from organizations like MapTiler and iATROS, showcasing how they have successfully navigated these challenges by leveraging cloud solutions to enhance performance, efficiency, and cost control. The findings emphasize the importance of well-architected platforms that allow for independent scaling of resources and maintenance of consistent service levels, ultimately supporting predictable performance as workloads grow.