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Global IT Company Enhances Search Capabilities with Modern Data Platform
Technology Category
- Infrastructure as a Service (IaaS) - Private Cloud
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- E-Commerce
- National Security & Defense
Use Cases
- Behavior & Emotion Tracking
- Traffic Monitoring
The Challenge
The global information technology services company, which provides one of the largest e-commerce platforms in the world, was facing challenges due to the exponential growth in data volume resulting from increased internet transactions. The company needed to improve the relevance of information for discovery and required a semantic search engine to power the search function for all applications on its platform. This was crucial to understand user intent through search context and improve the relevance of results. The company also needed to create a modern architecture framework to enable better searches, replicate data, and perform experimental customization analytics. The challenge was to move data efficiently to allow effective searchability, a task the company was struggling with. The platform also needed to handle increased search traffic and data volumes expected in the future, while adhering to high security and compliance standards and avoiding high costs.
The Customer
Not disclosed
About The Customer
The customer is a global information technology services company that provides one of the largest e-commerce platforms in the world. The company serves a vast number of customers, processing a high volume of internet transactions daily. As a result, the company deals with an exponentially growing volume of data that needs to be efficiently managed and processed. The company's primary need was to improve the relevance of information discovery and enhance the search function across all applications on its platform. The company also aimed to create a modern architecture framework to enable better searches, replicate data, and perform experimental customization analytics.
The Solution
To address these challenges, the company migrated 900+ nodes to Cloudera’s CDP Private Cloud Base for all data processing and storage, replacing the end-of-life CDH platform. The company also needed a solution for streaming workloads and chose Cloudera Data Flow’s (CDF) Streams Messaging, which includes Apache Kafka, Streams Replication Manager (SRM), and Streams Messaging Manager (SMM), replacing Confluent. This decision was made to replicate data across global data centers, secure and back up the data, and meet SLA requirements while maintaining high data availability. Kafka support was needed to buffer streaming data for their use cases. The company preferred the monitoring and deployment management using Cloudera Manager compared to Confluent Control Center. SRM and SMM were used for data replication and monitoring, providing a great deal of observability.
Operational Impact
Quantitative Benefit
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