Intelligent applications in containers
summary
Shows a concrete workflow: prototypes run interactively as Jupyter + Spark notebooks (k‑means, logistic regression, Word2Vec) then get lifted into a containerized app on OpenShift/Kubernetes using rad-analytics tooling. Demonstrates a VaR example with 10,000 Monte Carlo runs over five days that yields about a $230k loss in the worst 5% and a quick proof-of-concept web UI built as React front end + Flask API backed by a Spark cluster deployed and managed in containers.
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chapters (5)
- 0:00Start
- 10:49Multitenant compute clusters
- 11:14One cluster per application
- 12:42Data-processing microservices
- 14:31Spark management tooling
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