@@ -16,20 +16,27 @@ <h2>Publications</h2>
1616 < br >
1717 < h4 > 2016</ h4 >
1818 < ul >
19- < li > Chronix – A fast and efficient time series storage based on Apache Solr, Open Source Data Center
20- Conference, 2016,
21- < a href ="https://speakerdeck.com/florian_lautenschlager/chronix-a-fast-and-efficient-time-series-storage-based-on-apache-solr "> Slides</ a > </ li >
19+ < li > Chronix as long term storage for Prometheus, Cloud Native Conference, 2016,
20+ < a href ="http://www.slideshare.net/QAware/chronix-as-longterm-storage-for-prometheus "> Slides</ a >
21+ < a href ="https://www.youtube.com/watch?v=4fhXSgRmLHM&list=PLj6h78yzYM2PqgIGU1Qmi8nY7dqn9PCr4&index=62 "> Recording</ a >
22+ </ li >
23+ < li > Time Series Processing with Solr and Spark, Lucene Revolution, 2016,
24+ < a href ="http://www.slideshare.net/QAware/time-series-analysis-67281407 "> Slides</ a >
25+ </ li >
2226 < li > The new time series kid on the block, Apache Big Data North America, 2016,
2327 < a href ="https://speakerdeck.com/florian_lautenschlager/the-new-time-series-kid-on-the-block "> Slides</ a >
2428 </ li >
2529 < li > Time Series Processing with Apache Spark, Apache Big Data North America, 2016,
2630 < a href ="http://www.slideshare.net/adersberger/time-series-processing-with-apache-spark "> Slides</ a >
2731 </ li >
32+ < li > Chronix – A fast and efficient time series storage based on Apache Solr, Open Source Data Center
33+ Conference, 2016,
34+ < a href ="https://speakerdeck.com/florian_lautenschlager/chronix-a-fast-and-efficient-time-series-storage-based-on-apache-solr "> Slides</ a >
35+ </ li >
2836 </ ul >
2937
3038 < h4 > 2015</ h4 >
3139 < ul >
32-
3340 < li > Fast and efficient operational time series storage: The missing link in dynamic software
3441 analysis, Symposium on Software Performance, 2015,
3542 < a href ="http://www.performance-symposium.org/fileadmin/user_upload/palladio-conference/2015/slides/06_FLautenschlager.pdf "> Slides</ a >
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