We are packaging our product as a self-hosted machine images (www.netsil.com/download). We are using DC/OS runtime to orchestrate all our internal services and

We are packaging our product as a self-hosted machine images (www.netsil.com/download). We are using DC/OS runtime to orchestrate all our internal services and have written various health check scripts to make sure the data pipeline components such as our stream-processor, Kafka and Druid stay operational. This blog post describes Netsil's architecture: https://blog.netsil.com/listen-to-your-apis-see-your-apps-a91ece5aa5bd https://blog.netsil.com/listen-to-your-apis-see-your-apps-a9... In-terms of data being ingested -- we are stream-processing service interactions (network packets!) in real-time, storing interaction logs in memory and rolling them up to generate multidimensional timeseries data emitted every second. Therefore, the actual timeseries ingestion rates by Druid vary across deployments.