Spring Cloud Dataflow UI
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Version:
2.8.4
2.8.4
2.9.6
2.10.3
2.11.5 (Current)
Installation
Concepts
Stream Developer guides
Batch Developer guides
Feature guides
Commercial feature guides
Recipes
Polyglot
RabbitMQ
Apache Kafka
Amazon Kinesis
Multiple Platform Deployments
Scaling
Batch
Functional Applications
Cloud Providers
Resources
Applications
2.8.4
Recipes
Recipes
This section contains recipes that address some common use cases.
Polyglot
Python Stream Processor
Python Application as a Data Flow Stream Processor
Python Task
Create and Deploy a Python Task
Python Application
Create and Deploy a Python Application in a Stream
RabbitMQ
RabbitMQ as Source and Sink
RabbitMQ as Source and Sink + RabbitMQ binder
Apache Kafka
External Kafka Cluster
Connect to an external Kafka Cluster from Cloud Foundry
Amazon Kinesis
Amazon Kinesis Binder
A sample of Spring Cloud Stream + Amazon Kinesis Binder in action
Multiple Platform Deployments
Role of Multiple Platform Deployments
A walk-through of multiple platform requirements and the configurations for Cloud Foundry and Kubernetes
Multiple Platform support for Tasks
Learn how to launch and schedule tasks across multiple platforms
Scaling
Manual Scaling
Scale applications using SCDF Shell
Autoscaling
Autoscale streaming data pipeline with SCDF and Prometheus
Batch
Batch-only Mode
Set up Spring Cloud Data Flow to use only batch and not streams
SFTP to JDBC
Ingest Files from SFTP to a JDBC data store using Data Flow and Spring Batch
Functional Applications
Functional Applications
Configuring the Spring Cloud Stream Functional applications
Cloud Providers
GKE Regional Clusters
Deploying Spring Cloud Data Flow to a GKE Regional Cluster
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