技术
- 分析与建模 - 机器学习
- 平台即服务 (PaaS) - 应用开发平台
适用行业
- 电子商务
- 零售
适用功能
- 物流运输
- 采购
用例
- 最后一英里交付
- 零售店自动化
服务
- 云规划/设计/实施服务
- 培训
关于客户
iFood 是一家位于巴西圣保罗的在线食品订购和配送服务公司。该公司保持着巴西食品配送市场 80% 的份额,并在哥伦比亚各地广泛使用。 iFood 为约 320,000 家餐厅组成的网络提供服务,并计划增加 30,000 家超市的数量。该公司最近还为药店和酒类商店增加了送货服务。该公司利用人工智能(AI)和机器学习来更好地了解用户,例如跟踪他们上个月下了多少订单、他们喜欢哪些餐厅和商店、他们选择的支付机制以及许多其他变量。
挑战
iFood 是巴西和哥伦比亚流行的食品订购和配送服务,在维持其机器学习 (ML) 模型的性能方面面临着重大挑战。该公司的成功与这些模型的性能直接相关,这些模型需要快速处理数据以降低成本、增加收入并影响实时交互过程中的用户行为。 COVID-19 大流行为电子商务公司,特别是准备处理不断增加的订单量的在线送货服务提供了独特的机会。在 iFood,技术团队必须管理数百万新用户和数千家加入其平台的新餐厅。尽管业务量激增,iFood 仍然致力于为客户提供最佳体验。
解决方案
为了确保 ML 工程师的一致性并为用户创造最佳体验,iFood 使用 AWS 上的 Redis Cloud 作为其快速发展的 ML 特征存储的基础。闪存上的 Redis 可最大限度地提高数据处理吞吐量,同时降低总体数据存储成本。 Redis Cloud 使特征数据可供生产中的数十个模型使用,并且它包括注册表、数据管道和监控工具等基本功能,以简化特征工程活动。这使得 iFood 的数据和人工智能团队能够在生产中大规模搜索、重用和提供功能。 Redis 与 iFood 密切合作,在 Flash 上实现 Redis,并将完全托管的服务集成到 iFood 的微服务架构中。这种卓越性能的关键在于 Redis on Flash 在 DRAM 和闪存存储层之间编排数据的方式。
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