Flow deployments overview
A flow deployment represents a NiFi cluster running on Kubernetes and executing a specific flow definition. When you initiate the flow deployment process from the Cloudera DataFlow Catalog, a deployment wizard helps you turn a flow definition into a flow deployment. When using the wizard, specify your environment, provide configuration parameters, auto-scaling settings and KPI definitions for your flow deployment.
Creating flow deployments
Deploy a flow definition to run Apache NiFi flows as flow deployments in Cloudera DataFlow. To do this, launch the Deployment wizard and specify your environment, parameters, sizing, and KPIs.
Monitoring flow deployments
The Cloudera DataFlow UI is the central monitoring console for all your deployments across environments. It is the space where you can monitor flow metrics and infrastructure usage, and manage deployments.
Managing flow deployments
Learn about using the Deployment Manager page to manage your flow deployment lifecycle.
Auto-scaling
Flow deployments can be configured to automatically scale up or down the number of Apache NiFi nodes depending on the resource utilization in the cluster.
Custom processors
Learn about general guidelines concerning the creation of custom NiFi archives (NARs).
Custom Python scripts
Relying on Python scripts to perform data transformations within data flows is a common pattern for Apache NiFi users. Cloudera DataFlow deployments come with Python 3.9 and the following custom pre-installed packages: requests, urllib3. You can design your data flows to use the pre-installed Python runtime as well as install additional custom packages which you might require.
