Who is the Client

A US-based Fortune 500 departmental store chain with more than 1000 stores across the states, they are bringing stylish clothing for the entire family since decades now.

The Challenge

The client has a vast e-commerce portal that showcases more than 350K products. The portal was taking 45 minutes to reflect inventory changes on the product matrix pages. Since the customers were not able to place the order sooner, they were losing interest from the portal, which caused a loss of sale for the client.

The client used to store product details and inventory information on a single database. The database was running on an Apache Solr-based master server and 200 slave servers. In this structure, the changes made in the database used to take 45 minutes to reflect on the product matrix pages since each change need to be replicated on all 200 servers during the peak season.

The Solution

Prior to GSPANN, the client’s other technology partner was managing the Solr search platform and was unable to solve the issue. After carefully analyzing the system architecture, our team understood that the complexity lies in extracting the inventory data (externalization), which was creating performance issues since the application was dealing with at least 1 million SKUs.

Our team proposed to perform externalization at an internal Lucene ID level by integrating Redis with Solr. We extracted the inventory information on a separate Redis environment and made Redis cache to save this information instead of Solr. This saved a lot of time consumed in replicating the database change on 200 Solr-based servers.

All inventory changes now flow to a single server where Redis is present and all servers are connected to the same Redis cache for inventory information.

Business Impact

  • Time taken to reflect the status of any out of stock/in-stock product on the product matrix pages is reduced from 45 minutes to 10 minutes.
  • The client can now remove any product on the product matrix pages as per business requirements.
  • The client saved 25% of the infrastructure cost on the Google Cloud Platform due to reduced storage space requirements.

Technologies Used

Solr. An open-source enterprise-search platform, written in Java, from the Apache Lucene project
Redis. An open-source Barkeley Software Distribution (BSD)- licensed in-memory data structure store, used as a database, cache, and message broker
Google Cloud Platform (GCP). A suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products
Jira. A proprietary issue tracking product developed by Atlassian that allows bug tracking, issue tracking, and project management
Jenkins. An open-source automation server that helps in building, testing, deploying, and facilitating continuous integration and continuous delivery

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