Apache Kafka & Confluent Cloud Crash Course for Beginners

Discover the confluent platform, a full scale data and event streaming solution built by the original creators of Kafka, with the latest Apache Kafka and seamless GCP and Azure integrations.

Master quick start with Confluent Cloud by creating a basic cluster and topic, then use the CLI to set up producers and consumers.

Explore ksqlDB, a real-time event streaming database built on Apache Kafka, and how it links streaming data to a relational SQL model, with REST, code, and Confluent Cloud UI interactions.

Set up a Confluent Cloud cluster, create a user topic, and build a KSQLDB app with streams and a table, using data generator and connectors.

Explore Kafka streams, a Java library that abstracts producer to topic to consumer flows into concise code, enabling filtering, joining, and aggregation for meaningful analytics.

Explore Kafka Connect, a core Apache Kafka component that enables streaming integration with external services via connectors for sources and data syncs, including Amazon S3.

Create a Python producer to send messages to a topic. Set up the topic in the control cluster, publish messages, and configure a consumer to start consuming in Confluent.

Set up a Python producer to publish ten messages mapping user IDs to books on a Kafka cluster, using a producer config, a delivery callback, and a books topic.

Create a topic in Confluent Cloud for your Kafka producer, name it books, and verify its immediate availability in the cluster’s topics list.

Produce messages to a Kafka cluster by converting files from Windows to Unix, running the producer, and sending ten messages with keys and values to the books topic.

Create a Python consumer to read from a Kafka topic by resetting the offset to the beginning, subscribing to the books topic, and polling for messages with error handling.

Learn to ingest streaming data by producing and consuming messages in real time with Apache Kafka and Confluent, observing real-time consumption as messages are produced and read in order. See topic activity, and test end-to-end flow by producing a new message to a topic such as books.

implement a streaming application with two topics, user game and user losses, feeding per-user losses and per-user stats tables to generate a global scoreboard.

Configure and run the streaming Pacman app by updating the demo.cft with AWB access key and secret, then run the start script to provision Confluent Cloud resources via Terraform.

Set up the prerequisites for the Apache Kafka and Confluent Cloud course by provisioning Confluent Cloud and AWS accounts, creating S3 buckets, and installing Terraform, Java 11+, and Maven.

Set up ksqlDB by creating topics user_game and user_losses, building streams and tables for losses per user and stats, then grant the service account read and write access.

Launch and monitor a Pac-Man game end-to-end using TerraForm to initialize a project, create an S3 bucket, and stream data with Kafka Connect to S3 as JSON.

Master patient healthcare and management workflows using beginner-friendly guidance on Apache Kafka and Confluent Cloud.