Develop a PyFlink app against a Kafka cluster on Docker, running it both in a virtual environment and in a local Flink cluster for better monitoring.

Develop a fraud detection app locally on Docker with Kafka, Flink and DynamoDB, re-implementing a solution taken from an AWS workshop.

Control user access to Kafka resources with authorization rules, keeping SASL for client authentication, with Java and Python client examples.

Authenticate Kafka clients with SASL instead of client certificates, with Java and Python client examples of the SASL mechanisms.

Enforce two-way TLS verification so Kafka brokers check the client certificate, with Java and Python client examples of SSL authentication.

Deploy the Camel DynamoDB sink connector and its data generator source on Amazon MSK and MSK Connect, moving the local pipeline onto AWS.

Configure TLS encryption between Kafka brokers and clients, where the client verifies the server certificate, with Java and Python examples.

Schema registry support added to kafka-python producer and consumer apps, which serialise and deserialise through AWS Glue Schema Registry.

Schema registry support added to a Kafka Connect ingestion pipeline, so the source and sink connectors serialise through AWS Glue Schema Registry.

Build the Glue Schema Registry client library and use it to manage and enforce schemas in Kafka producer and consumer applications.