伯克利实验室的材料项目使用 Datadog 云监控来简化 AWS 上的可观察性
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- Datadog Infrastructure Monitoring
- Datadog Container Monitoring
- Amazon VPC
- AWS Fargate
- Amazon Elastic Container Service
技术栈
- AWS
- Datadog
- Python
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Digital Expertise
- Innovation Output
技术
- 基础设施即服务 (IaaS) - 云计算
- 分析与建模 - 实时分析
- 基础设施即服务 (IaaS) - 云存储服务
适用行业
- 教育
适用功能
- 产品研发
- 质量保证
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
劳伦斯伯克利国家实验室是美国能源部科学办公室实验室，由加州大学管理。该实验室的材料项目成立于 2011 年，旨在加速材料研究和创新产品的上市时间。材料项目计算基本材料特性，并开发一系列开源工作流程和分析软件，以加速材料设计。材料项目数据及其工具为工业、教育和政府实验室的研究人员提供了研究的跳板，为他们提供帮助。该项目的计算大大缩短了研究人员发明新材料的时间，节省了数月甚至数年的艰苦工作。
挑战
材料项目是美国能源部支持的伯克利实验室研究计划，该项目希望通过更新其单体网站，让越来越多的用户能够更轻松地访问其材料研究。该项目的计算大大减少了研究人员发明新材料的时间，节省了数月甚至数年的艰苦工作。然而，随着该项目的扩展以满足美国和全球的需求，其本地单体堆栈已难以满足用户和内部需求。该项目还缺乏对服务使用情况和故障的洞察。由于材料项目是公共资助的，因此它需要一个经济实惠的解决方案来配合其基础设施堆栈各方面的现代化，以实现微服务架构。
解决方案
该组织求助于 Amazon Web Services (AWS) 公共部门合作伙伴 Datadog 来大规模实施成本优化的可观察性解决方案。材料项目使用 Datadog 基础设施监控来实现对其资产的全面覆盖，并使用 Datadog 容器监控来实现对容器化环境的多维可见性。它还利用 Datadog 的仪表板功能在其办公室设置连续的实时监控屏幕。作为重新设计的一部分，该项目结合使用 AWS Fargate（一种用于容器的无服务器计算服务）和 Amazon Elastic Container Service (Amazon ECS)（一种完全托管的容器编排服务）。使用 AWS 和 Datadog，材料项目只需少数几名科学家转行的工程师就可以管理其基础设施。
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