Browse past weeks of engineering reads.
How to design systems that can recover from ransomware and destructive cyberattacks when backups, credentials, and infrastructure components have been compromised.
ALS GeoAnalytics needed to scale machine learning model training and inference for core logging analysis while managing computational costs effectively.
Oldcastle needed to overcome the limitations of traditional ERP reporting to enable real-time analytics and dashboards for their Infor ERP system.
Building a scalable multi-tenant configuration service that maintains strict tenant isolation while supporting real-time updates without cache staleness or downtime.
Organizations need a streamlined way to protect and recover entire AWS workloads across multiple layers (data, compute, infrastructure, networking, and configuration) in the event of a disaster.
BASF Digital Farming needed a scalable way to catalog, discover, and serve large volumes of spatiotemporal geospatial data (satellite imagery, crop data) for their xarvio crop optimization platform, and their existing infrastructure struggled with the scale and query patterns of this data.
Artera needed to develop and scale an AI-powered prostate cancer diagnostic test, requiring significant compute resources for model training/inference and a reliable pipeline to deliver timely, personalized treatment recommendations.
Organizations migrating to or operating in the cloud encounter hidden and unexpected costs due to suboptimal architectural decisions, resource misconfigurations, and lack of adherence to cloud best practices.