Apache Kafka and Confluent on Google Cloud: Free Written Course

Event streaming becomes easier to understand when you can trace a message from its source to a useful result. Getting Started with Apache Kafka and Confluent Platform on Google Cloud offers two written examples of that journey: a Kafka Streams word-count pipeline and a clickstream analysis pipeline built with ksqlDB.

The full official walkthroughs and their linked teaching code are publicly readable for free. You can study the sequence without paying or opening a cloud lab. Running the supplied hosted environments is a separate activity that can have access costs. This listing describes the current two-tutorial written route, not a collection of video lectures.

Course at a glance

What you’ll learn

• Trace data from a Kafka topic through a Java application and into an output topic.
• Follow the producer and consumer steps used to inspect a word-count pipeline.
• Understand the role of ksqlDB tables and streams in a clickstream example.
• Follow the movement of streaming results toward Elasticsearch and Grafana.
• Explore sessionization and dashboard views as ways to interpret incoming events.

Skills you’ll gain

• Apache Kafka
• Kafka Streams
• ksqlDB
• Event pipelines
• Clickstream analysis
• Streaming data flows

Follow the complete free reading route

Open each official walkthrough directly to read the teaching material before deciding whether to use the separate hosted practice environment.

1. Creating a Streaming Data Pipeline With Apache Kafka — Study a Kafka cluster, input topic, Java WordCount application, and inspected output.
2. Confluent: Clickstream Data Analysis Pipeline Using ksqlDB — Follow generated clickstream data through ksqlDB and onward to analytical views.

From a word count to a clickstream pipeline

The Kafka Streams tutorial keeps the first example focused. A console producer supplies input to a topic, a Java application processes it, and a console consumer lets you inspect the output. Reading that sequence gives you a concrete way to distinguish the event source, the processing logic, and the result.

The clickstream tutorial expands the picture. It uses generated event data, connectors, ksqlDB, and downstream visualization tools. The walkthrough includes loading data into tables and streams, sending results toward Elasticsearch and Grafana, and examining sessions. It is useful for seeing how several components cooperate in one analytical workflow.

Study the data flow before the setup details

Begin each walkthrough by naming the input, the transformation, and the output in plain language. For the word-count example, follow what happens between the producer and consumer. For clickstream analysis, identify where events are generated and which view helps answer a question about them.

Then use the linked Java and SQL examples to connect that outline with the actual teaching code. You do not need to claim a successful deployment to learn from reading a pipeline. Keep your notes explicit about what you understood from the material and what you have actually run yourself.

The examples reference historical Kafka and Confluent repository versions. They are useful for studying the provided workflows, but should not be treated as instructions for the latest software release or as a current production deployment plan. This distinction is especially helpful when comparing the written examples with newer product documentation.

Background and free access

Google classifies the course as Intermediate. Familiarity with command-line instructions and basic programming or data concepts will help you follow the Java and SQL examples. The sequence is not a complete introduction to either language. Learners needing that foundation can explore related topics in the course library.

All written teaching units and the directly linked example code were checked for public reading access. Hosted lab execution, cloud resources, scored completion, and recognition are separate. No free badge or certificate is promised, and there is no need to start a billed cloud environment just to follow the reading route.

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