Eight Sleep 利用 Datadog 实现端到端可观察性
公司规模
11-200
地区
- America
国家
- United States
产品
- Datadog Application Performance Monitoring
- Datadog Synthetic Monitoring
- Datadog Real User Monitoring
技术栈
- AWS Cloud
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 实时分析
- 应用基础设施与中间件 - API 集成与管理
适用行业
- 医疗保健和医院
适用功能
- 产品研发
- 质量保证
用例
- 预测性维护
- 实时定位系统 (RTLS)
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
Eight Sleep 是一家位于纽约市的睡眠健身公司。该公司开发了一项专有技术，利用人工智能和机器学习模型来跟踪生物信号，并通过温度控制来优化身体恢复和休息。该公司制造了一种吊舱，它使用传感器来跟踪和改善睡眠，根据用户的睡眠阶段动态调整床垫温度。传感器还记录每个用户的关键健康指标。客户使用配对的应用程序查看睡眠和健康指标、调整温度、获取见解等。从传感器收集的数据被传输到公司的 AWS 云托管平台。
挑战
Eight Sleep 是一家位于纽约市的睡眠健身公司，需要一款强大的可观察性解决方案。该公司希望更好地了解用户对其应用的体验，并在问题发生之前加以预防。当时，Eight Sleep 使用的解决方案对一些公共端点执行正常运行时间测试，但该解决方案过于基础且缺乏可配置性。工程师经常在半夜接到呼叫，最终被证明是误报。由于开发团队规模较小，Eight Sleep 需要一款能够帮助其快速轻松完成任务的工具。该公司的竞争对手拥有三到四倍的工程师，因此他们需要一款能够以最少的工作量完成其声称可以完成的工作的工具。
解决方案
Eight Sleep 采用 Datadog 应用程序性能监控 (APM) 来提高整个应用程序的可观察性。APM 使公司能够更好地了解应用程序的运行情况。开发团队还可以构建仪表板来可视化应用程序的遥测数据，从而轻松了解代码更改导致的延迟或回归。然后，团队开始使用 Datadog 合成监控，以使用模拟请求和操作来观察其系统和应用程序对最终用户的运行情况。使用 Datadog 合成监控，团队可以编写多步骤 API 合成测试来复制用户旅程，这让他们有信心在出现问题时会收到通知。Eight Sleep 最近还添加了 Datadog 真实用户监控 (RUM)，以实现对用户旅程的端到端可见性，这使他的小型开发团队能够更快地交付新的平台特性和功能。
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