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Log Analytics

Paul Nelson
At the 2017 Elastic{ON} presentation, our Chief Architect, Paul Nelson, demonstrated our new open source Kibana plug-in. This plug-in enables log browsing across multiple machines in a single view as well as enhances performance and security. Watch his presentation to learn more and see it in action.
Paul Nelson
At the 2017 Elastic{on} in San Francisco, we interviewed our Chief Architect, Paul Nelson, for some key highlights of his presentation, "Browse Raw Logs in One Place: Open Source Plug-in for Kibana," and for his thoughts on the future technology direction of the Elastic Stack. Watch the video interview to learn more.
Derek Rodriguez
Since Search Technologies started to support the Cataloger’s Desktop in 2009, we’ve been helping the Library of Congress implement cutting-edge enhancements to improve its users' experience. We've recently added new features, including log analytics, query and title suggestions, metadata enhancement, and saved search alerts. Read more about these projects and their outcomes.
Kristy Martin
Understanding mobile app users' behavior can help you figure out ways to enhance their search experience and boost mobile revenue. Take a deep dive into gathering and analyzing user logs to identify areas for search improvements.
Graham Gillen
Commercial and open source log analytics tools have generated plenty of discussions. In this blog, we provide an insider's look into two popular log analytics solutions: Elasticsearch, Logstash, and Kibana (ELK stack) vs. Splunk. Whether the ELK stack can be used as a Splunk replacement or not, it's worth considering the options, such as costs, functionalities, and overall user experience.
Paul Nelson
You've heard a lot about e-commerce personalization for a better online shopping experience, higher Net Promoter Scores and greater bottom line. But how can big data make advanced, real-time personalization possible? Watch the case story, a part of our "In the Trenches with Big Data & Search" series, to find out.
Paul Nelson
How can our online publishing customers use a big data framework to improve search, personalize content, and continuously test search engine performance to optimize subscription revenue? Watch their success story, a part of our "In the Trenches with Big Data & Search" series.
Paul Nelson
Recommendation engines play a critical role in customer engagement and retention for online media and entertainment industry. How did we use big data to efficiently process 5.4 billion clicks daily to personalize videos for users? Watch the case story, a part of our "In the Trenches with Big Data & Search" series, to find out.
Paul Nelson
Businesses had used logs for insights long before big data came around. But with the exponential growth of log files, log management and analysis have become daunting. Watch the full story, a part of our“In the Trenches with Big Data & Search" series, on how we leveraged open source big data to process 600+ GB daily for more efficient, cost-effective log analytics.
Xavier Morera
Elasticsearch and Solr have become dominant players in the search market. Both are open source and built on Lucene, but each has its own strengths in different areas, depending on what users want to accomplish. In this blog, we'll take a deep dive into how these search engines would fit for your use cases.