Case Study: Lawrence Berkeley National Laboratory achieves 99.98% uptime and scales to 300K users with Datadog cloud monitoring on AWS

Materials Project of Berkeley Lab Uses Datadog Cloud Monitoring to Simplify Observability on AWS

The Materials Project at Lawrence Berkeley National Laboratory, a DOE-funded initiative that accelerates materials research, needed to modernize a monolithic, on‑premises web and API stack so it could scale for a growing global user base while remaining cost‑efficient for public funding. As demand surged, the project lacked visibility into service usage and faults and required a move to a microservices architecture on AWS to improve availability and enable broader collaboration.

The team migrated to AWS using ECS and Fargate and adopted Datadog Infrastructure and Container Monitoring (with an Amazon VPC endpoint) to gain unified observability, live dashboards, and cost‑optimized data transfer. The result: seamless global launch and scale—growth from 5K to 300K users, ~2 million API requests per day, 99.98% uptime, about 5 TB served monthly—and reduced operational overhead for the engineering team.

Lawrence Berkeley National Laboratory

Patrick Huck

Senior Computer Systems Engineer