The first phase of migrating to an open source search engine is to get production search traffic onto the new search engine in the cloud without negatively affecting user experience or disrupting business KPIs. This process involves synching the catalog and other related data to the new service supporting legacy URLs for SEO reasons, and then testing the new service to ensure the relevancy is improved. Once that is done, Canary traffic is set up and monitored before diverting all production traffic to the new search engine.
Open source search engines deliver speed of innovation, scalability and cost control
Why open source search engine?
For almost a decade, we are seeing large enterprises migrating to open source search engines from proprietary solutions to power their search and analytics capabilities. Apache Lucene, SolrCloud and Elasticsearch opened the world of information retrieval to developer community, further democratizing search solutions and fueling immense community-driven innovation in the search area.
Enterprises migrating to open source search systems enjoy superb performance, scalability, cutting-edge features of engines, cutting on commercial product license costs, along with easier access to the talent and skills. Vivid community of developers and consultants working in open source space.
Grid Dynamics started in 2006 with the goal of making mission-critical systems scalable. Since then, performance and scalability engineering have been at the core of our company's DNA. As Solr and Lucene contributors, we have a deep understanding of search engine internals, and possess years of experience tuning the performance of search systems. For over 5 years, the search solutions that we have built for our retail customers have survived Black Friday traffic storms with flying colors, without a single outage or breach of SLAs. We have helped numerous customers solve their search performance issues, improving response times, online conversion rates from search and indexing speeds, sometimes at an exponential level.
Open source search engine migration process
Phases of replatforming to open source search
During the next phase of the replatforming process, a merchandising tool can be implemented, allowing business users to switch from the legacy experience manager to the new tool. The reference architecture is shown above:
The last phase in migrating to open source search is to add advanced functionalities, like ML/AI, personalization, conversational search and visual search. These generally support features that are not possible in legacy systems, namely an omnichannel catalog, store-level inventory and near real-time inventory updates. These features can be implemented in the first phase of replatforming as a part of the core search engine driving immediate business value, or later in the migration process.
Benefits of replatforming to open source search
Relevant search results for shoppers
Search engines dynamically adjust to relevance in real-time based on the available catalog and inventory, directing users to the products they're looking for.
In our experience, search-to-cloud implementation projects can be accomplished within several months, have low risk and usually remain within a reasonable budget.
Enablement of innovative features
Replatforming from black-box platforms to open source and the cloud opens up all types of new, innovative features and technologies for search, including visual search and voice-powered search.
Accurate, up-to-date information
Shoppers no longer have to worry about browsing for a product that's out of stock, or using a promotion that has expired. They see the inventory, pricing and promotions as they actually are, and get updates every couple minutes.
High level architecture of an open source search solution
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