As a follow on to last year’s Load, Drop & Kill session, we’ll do a recap on how retention rules are defined and how they are used by the Coordinator to oversee segment cacheing in a multi-tiered Apache Druid deployment. We’ll also cover some exciting new features. We’ll touch on how retention rules enable the new “Query from Deep Storage” feature. We’ll do another pass at the Coordinator cycle and how it has evolved including how it can now dynamically reconfigure itself. Finally we’ll do another pass at the lifecycle of a segment in a Druid cluster and highlight how this has changed since last year.
Physical Hardware, Digital Analytics: IoT Challenges, Best Practices, and Solutions
Electric vehicle maker Rivian and German startup Thing-it were kind enough to talk us through how real-time data and analytics play a key part in the evolving landscape of IoT (Internet of Things). The wealth...
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Streaming data is not only data in motion—it’s a potential source of valuable insights, ready to be harvested and utilized. The challenge is to analyze streaming data at scale and extract these insights—before...
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Engineering teams increasingly have to deliver insights in real-time. But as they aim to reduce latency from event-to-insight, they also face the challenge of dealing with larger and more complex data and concurrent...
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