Florian Lautenschlager

We introduced distributed tracing, central logging with trace correlation and monitoring with Prometheus and Grafana in a large internationally distributed software development project from the beginning. The result: Nobody used it.

In this talk we show the good and not so good sides we have learned while introducing and operating the observability tools. We show which extensions and conventions were necessary in order to carry out a cultural change and to awaken enthusiasm for these tools. Today the tools are a first-class citizen and people are shouting when they are not available.

How can you store 86 billion measurement points in 30 gigabytes and search through it within a few milliseconds on your laptop? A relational database? No! Apache Solr empowers you to do this if you follow a few concepts. The horizontal scalability capabilities of Solr bores away the borders of your laptop and allows you easily to scale out to your needs. In this code intense session we give an introduction how to store time series data in Apache Solr.

How can you store 86 billion measurement points in 30 gigabytes and search through it within a few milliseconds on your laptop? A relational database? No! Apache Solr empowers you to do this if you follow a few concepts. The horizontal scalability capabilities of Solr bores away the borders of your laptop and allows you easily to scale out to your needs.

In this session we give an introduction how to store time series data in Apache Solr. QAware has developed an Enterprise Application Performance Analysis Platform on top of Solr. Based on code examples you will see how easy multi-dimensional time series data can be stored and retrieved. We show how Solr features like Facets, Filters and Queries can be used to build graphical user interfaces with an outstanding performance and usability. We also compare this approach to other time series databases like InfluxDB and relational databases like MySQL.