Hi everyone,
I have a quick architectural question regarding Dynatrace Managed.
I know that Dynatrace SaaS leverages Grail for a schema-less/index-less architecture. However, since Dynatrace Managed traditionally runs on Elasticsearch and Cassandra, I want to better understand how data handling works under the hood here.
How does Dynatrace Managed achieve high-speed, flexible queries on historical data (like Traces and RUM) without the typical heavy indexing overhead and storage bloom seen in traditional index-based tools?
Are there any automated data optimization patterns or "schema-on-read" behaviors happening even within the Elastic/Cassandra layer?
Just trying to deeply understand the underlying philosophy for our Managed deployment.
Thanks in advance for your insights.
BR,
Aboud
