Understand the technical architecture along with installation and configuration of Spring Cloud Data Flow Applications. Create basic to advanced Streaming applications like time logger to TensorFlow Image Detection Stream Flow. You will learn the following as part of this course. Architecture of Spring Cloud Data FlowComponents of Spring Cloud Data Flow like Skipper Server, Spring Cloud Data Flow Server, Data Flow ShellUsing Data Flow Shell and Domain Specific Language (DSL)Configuring and usage of message brokers like RabbitMQ, KafkaInstallation and configuration of Spring Cloud Data Flow Ecosystem in Amazon Web Service (AWS) EC2 InstancesConfiguring Grafana Dashboard for Stream visualizationConfiguration of Source, Sink and ProcessorCreating custom Source, Sink and Processor applicationCoding using Spring Tool Suite (STS) for custom code developmentWorking with Spring Data Flow WebUI and analyzing logs on runtimesThis course is designed to cover all aspects of Spring Cloud Data Flow from basic installation to configuration in Docker as well as creating all type of Streaming applications like ETL, import/export, Predictive Analytics, Streaming Event processing etc, Few working examples/usecases are covered to have better understanding like Data extracting and interaction with JDBC databaseExtracting Twitter Data (Tweets) from TwitterSentiment analysis, Language Analysis and HashTag Analysis on Tweets from TwitterObject Detection/Prediction using TensorFlow processorPose Prediction using TensorFlow Processor
