Making Logs Fun Again

Kord Campbell, Loggly

December 9 2011

At Loggly we use Mongo as a repository of statistics and summary information for time series log data. Loggly collects and stores metrics into Mongo including the size and count of log events, and the results of saved searches run against our customized fulltext search engine based on SOLR. These metrics are used to drive graphs, reports, dashboards and exciting visualizations for our users. This talk will also discuss how we tied Mongo into our infrastructure, how we use Mongo for stats rollups, and how we expose that data to end users via our REST APIs.