Introducing Lucidworks SiLK
SiLK is a feature rich UI that runs on-top of open source Lucene/Solr and commercially licensed Lucidworks Fusion. SiLK gives users the power to perform ad-hoc search and analysis of massive amounts of multi-structured and time series data. Users can swiftly transform their findings into visualizations and dashboards, which can easily shared across the organization.
SiLK for Log Analysis
Lucidworks SiLK can be used as an enterprise-grade solution for storing, analyzing and managing billions of log messages from across a variety of servers, applications and devices.
SiLK combines best in class open source log analysis tools (such as Flume, LogStash and Kibana) with the strength, speed and scale of Lucene/Solr in a simple supported package that is quick to deploy and easy to scale.
SiLK provides a feature rich UI that enables users to search, inspect and visualize their event data. Users can create, personalize and share dashboards and reports, gaining quick insight into application health, availability and security.
Fields and tags, which can be extracted automatically, provide context and meaning to your event data. Searches that result in a mixed bag of un-structured events and transactions can be easily transformed into simple rows and columns for easy ad-hoc analysis.
Event and transaction data come in a variety of forms. Whether your data is sitting in log files on disk, coming across the network or stored in a Hadoop cluster, SiLK provides a variety of ways to ingest your data. In addition to time series data, SiLK supports the visualization and inspection of non-temporal data including documents, e-mails, database tables and more.
SiLK runs on top of the scale and performance of Lucene/Solr. Lucene/Solr is one of the most scaleable and reliable search engines in the world. Lucene/Solr is the choice for leading brands such as eBay, Amazon, Beats Music and more…
Get started with SiLK today
SiLK combines best in class open source log analysis tools (such as Flume, LogStash and Kibana) with the strength, speed and scale of Lucene/Solr, providing a supported package that is quick to deploy and easy to scale.