The main developer interface is based on a customizes Jupyter Notebooks that comes preinstalled with Apache Spark and Cerebral Cortex. The following configuration file and python3 code show how to initialize a Cerebral Cortex instance to begin working with it.
cassandra: keyspace: cerebralcortex db_user: "" db_pass: "" datapoint_table: data mysql: database: cerebralcortex db_user: root db_pass: pass datastream_table: stream processing_module_table: processing_module user_table: user study_table: study
from cerebralcortex.CerebralCortex import CerebralCortex configuration_file = 'cerebralcortex.yml' CC = CerebralCortex(configuration_file, master="local[*]", name="Cerebral Cortex Test App")
Grafana provides real-time and historical visualization for most time series-based data streams generated by mCerebrum or Cerebral Cortex. These are presented in an easy-to-use graphical interface that is customizable through a web interface. Several dashboards come preconfigured to display common elements that are generated by mCerebrum and can be useful to a health-science researcher.
All logging in Docker containers are redirected to an Elastic Search server through fluentd and visualized by Kibana. This allows for easy and quick search of log entries and more complex fault analysis through Kibana’s query tooling.