Some details
CLIENT HAD:
LPP S.A. collects online customers’ data (mainly: orders stored in databases and customers’ online behaviour) from various sources. The company approached SoftwareMill to help them streamline data pipelines to be able to capture crucial metrics and derive business value in real-time.
CLIENT NEEDED:
Processing data, arriving at high velocity, required battle-proven tools for stream processing
and the preparation of data for a recommendation engine. Due to the nature of the online retail business client needed a system featuring self-healing, as well as load balancing. Plus monitoring of the infrastructure health and performance.WE DID:
Seven streaming applications have been delivered as well as devops scripts setting up Kubernetes and all necessary tools. As a result, our customer was able to attach custom dashboards to display the sales volume as well as feed their recommendation engine in a cost effective way without latency.
OUTCOME:
A transformation of the existing batch-based process into a data streaming platform built up on mature and popular open source tools. The reports are fed in real-time via stream processing applications build up on Kafka Streams and Apache Beam allowing LPP S.A. to interact with online customers in real-time.
Full case study: https://softwaremill.com/portfolio/#lpp
