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

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

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

Datadog

Technology Category	Analytics & Modeling - Real Time Analytics Infrastructure as a Service (IaaS) - Cloud Computing Infrastructure as a Service (IaaS) - Cloud Storage Services
Applicable Industries	Education
Applicable Functions	Product Research & Development Quality Assurance
Services	Cloud Planning, Design & Implementation Services System Integration
Challenge	The Materials Project, a research initiative at Berkeley Lab supported by the US Department of Energy, wanted to make its materials research more accessible to a continually growing number of users by updating its monolithic website. The project’s computations drastically reduce the time for researchers to invent new materials, saving months or even years of painstaking work. However, as it scaled to meet US and global demand, its on-premises, monolithic stack strained to power both user and internal needs. The project also lacked insight into service usage and faults. Because the Materials Project is publicly funded, it needed an affordable solution to go along with the modernization of all aspects of its infrastructure stack for a microservice architecture. Read More
About Customer	Lawrence Berkeley National Laboratory is a US Department of Energy Office of Science lab managed by the University of California. The lab’s Materials Project was founded in 2011 to accelerate materials research and time to market for innovation. The Materials Project calculates fundamental material properties and develops a host of open-source workflow and analysis software to accelerate materials design. The Materials Project data and its tools are helping researchers in industry, education, and government labs by functioning as a springboard for their research. The project’s computations drastically reduce the time for researchers to invent new materials, saving months or even years of painstaking work. Read More
Solution	The organization turned to Amazon Web Services (AWS) Public Sector Partner Datadog to implement a cost-optimized observability solution at scale. The Materials Project used Datadog Infrastructure Monitoring to achieve complete coverage of its estate and Datadog Container Monitoring for multidimensional visibility into containerized environments. It has also employed Datadog’s dashboard capabilities to set up continuous live monitoring screens in its offices. As part of its redesign, the project uses AWS Fargate, a serverless compute service for containers, in combination with Amazon Elastic Container Service (Amazon ECS), a fully managed container orchestration service. Using AWS and Datadog, the Materials Project can manage its infrastructure with only a handful of scientists-turned-engineers. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Infrastructure as a Service (IaaS) - Cloud Computing

Infrastructure as a Service (IaaS) - Cloud Storage Services

Applicable Industries

Education

Applicable Functions

Product Research & Development

Quality Assurance

Services

Cloud Planning, Design & Implementation Services

System Integration

Challenge

The Materials Project, a research initiative at Berkeley Lab supported by the US Department of Energy, wanted to make its materials research more accessible to a continually growing number of users by updating its monolithic website. The project’s computations drastically reduce the time for researchers to invent new materials, saving months or even years of painstaking work. However, as it scaled to meet US and global demand, its on-premises, monolithic stack strained to power both user and internal needs. The project also lacked insight into service usage and faults. Because the Materials Project is publicly funded, it needed an affordable solution to go along with the modernization of all aspects of its infrastructure stack for a microservice architecture.

About Customer

Lawrence Berkeley National Laboratory is a US Department of Energy Office of Science lab managed by the University of California. The lab’s Materials Project was founded in 2011 to accelerate materials research and time to market for innovation. The Materials Project calculates fundamental material properties and develops a host of open-source workflow and analysis software to accelerate materials design. The Materials Project data and its tools are helping researchers in industry, education, and government labs by functioning as a springboard for their research. The project’s computations drastically reduce the time for researchers to invent new materials, saving months or even years of painstaking work.

Solution

The organization turned to Amazon Web Services (AWS) Public Sector Partner Datadog to implement a cost-optimized observability solution at scale. The Materials Project used Datadog Infrastructure Monitoring to achieve complete coverage of its estate and Datadog Container Monitoring for multidimensional visibility into containerized environments. It has also employed Datadog’s dashboard capabilities to set up continuous live monitoring screens in its offices. As part of its redesign, the project uses AWS Fargate, a serverless compute service for containers, in combination with Amazon Elastic Container Service (Amazon ECS), a fully managed container orchestration service. Using AWS and Datadog, the Materials Project can manage its infrastructure with only a handful of scientists-turned-engineers.

Impact #1	Datadog now provides comprehensive observability across the Materials Project estate.
Impact #2	The monitoring solution has made it simple for the Materials Project to quickly identify, diagnose, and respond to issues.
Impact #3	The team has set up dashboards to keep track of key metrics such as data transfer, uptime, and compute resources at a glance.

Impact #1

Datadog now provides comprehensive observability across the Materials Project estate.

Impact #2

The monitoring solution has made it simple for the Materials Project to quickly identify, diagnose, and respond to issues.

Impact #3

The team has set up dashboards to keep track of key metrics such as data transfer, uptime, and compute resources at a glance.

Benefit #1	5K → 300K users served globally
Benefit #2	2M API requests handled per day
Benefit #3	99.98% uptime achieved

Benefit #1

5K → 300K users served globally

Benefit #2

2M API requests handled per day

Benefit #3

99.98% uptime achieved

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Overview

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

Operational Impact

Quantitative Benefit