Imply Polaris offers Druid-as-a-Service to users with the ability to pay for ingestion only when it is used. To achieve this and keep costs down, Druid needs to scale its ingestion resources in response to customer workloads. In this session, we will talk about how we deployed Apache Druid to provide this capability to our customers first using Druid’s in built auto-scaling ingestion mechanics and then by switching to middle manager less ingestion using the druid-kubernetes-overlord extension and Kubernetes node scaling In the talk, we will discuss some of the key problems we had to solve to make deploying middle manager less ingestion a success like minimizing pod startup time and tradeoffs to consider before switching to middle manager less ingestion.
Keynote: Powering Event-Driven Data with Apache Druid
The distinction between OLTP and OLAP is becoming less relevant as data architectures shift toward entities and events. In this session, we’ll delve into how Apache Druid’s event-first approach synthesizes...
Watch nowClosing Keynote: Charting the Future of Druid
What lies ahead for Apache Druid? Join us as we explore the evolving landscape of Druid’s query and storage engines, and how they are positioned to address the biggest challenges in event data for the future. Speaker: Gian...
Watch nowSalesforce: Tracing Service Dependencies at Scale with Druid and Flink
At Salesforce, we manage approximately 300 million distributed spans to infer service dependencies. We have successfully utilized a combination of Druid and Flink to handle this scale with high availability....
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