Curiosity Software Ireland, a specialist vendor in test data management and model-based test automation, today announced support for Apache Solr. The comprehensive integration between Test Data Automation and Solr enables rigorous and automated search validation, ensuring that search engines deliver correct and relevant results for a wide range of scenarios.
Search developers can now mask, subset and synthetically generate complete test data on demand, automatically provisioning it to Solr to validate search results and integration technologies.
Search technologies are the backbone of business-critical systems that provides users with easy access to the information that organisations want them to see. They are a pillar of user experience and frequently hold the keys to customer retention and revenue.
Yet, testing practices have not kept pace with the evolution of search development. Manual and unsystematic testing often amounts to entering a limited number of terms, validating the relevance of their results. Most test scenarios go untested, as do the integration technologies that draw data from a complex spread of sources.
This is why Curiosity Software have drawn on 35 years of QA experience to introduce test data and test automation solutions to Solr. The high-speed utilities move data rapidly from a range of sources to Solr collections, subsetting, anonymising, and augmenting data as it moves.
These flexible utilities allow testers and search developers to feed the right data to Solr on demand, ranging from individual data journeys to a rich and varied test data set. The automated technologies not only integrate with Solr, but also other cutting-edge technologies used by Solr developers, including Docker and Kafka. Together they enable developers to rapidly and rigorously validate that the right results are delivered for each and every scenario.
Automated Solr Data Provisioning Demo:
Huw Price, Managing Director of Curiosity comments how
“the search community is one of innovative developers who leverage best-of-breed technologies. They deploy in Docker and Kubernetes and use cutting-edge open source technologies like Solr and kafka. What’s missing is the automation, and particularly the test automation.“
“This where Test Data Automation comes in,” Huw adds. “You can now move data rapidly from a range of sources to Solr environments, masking, subsetting, and augmenting it as it moves. That way, search developers can not only make sure that search engines perform under high volumes of searches, but also that they deliver the right results for a rich range of searches.”
Watch a video of Test Data Automation for Apache Solr here and book a free consultation today.