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Summary of the configurable components Corridor exposes for customizing dashboards, data-lake access, approvals, exports, and external integrations.

Corridor offers various configurable components which makes it very flexible. The users can create their own set of dashboards, read from and save to any type of data-lake, add shortcuts to the platform for external apps, export the artifacts to external apps, get approval from external reviewers. The user could also create custom APIs, using the corridor package and use those APIs from external applications.

In This Section

Approval Handler: connect approvals to a 3rd party review tool
Export: export artifacts and documentation to external applications
Definition Sources: control which definition sources are allowed
Shortcuts: add links to external applications in the platform UI
Fetching Metadata: access object metadata via the corridor package or custom APIs
Email Notifications: configure the SMTP provider for platform notifications
Additional Libraries: install extra Python libraries for use in definitions and simulations
Job Configs: run jobs with a custom Spark session
Multiple Corridor Workers: run multiple named workers on the same server
Spark UI: link platform jobs to the Spark Web UI and History Server
Connecting to a Spark Kubernetes Cluster: run Spark jobs on a Kubernetes cluster
Monitoring Dashboard: track external objects and configure alerting
Externally Managed Custom Fields: manage custom fields controlled by an external system

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