Part 3 of the Spring for Apache Kafka Deep Dive blog series introduces Spring Cloud Data Flow, a toolkit designed to enhance developer productivity by simplifying the development, deployment, and orchestration of event streaming pipelines using Apache Kafka. The blog explains how Spring Cloud Data Flow manages data pipelines from design to production deployment, supporting both real-time event streaming and short-lived task/batch applications. Key components include Spring Cloud Skipper for handling application lifecycle operations and Micrometer-based monitoring with customizable Grafana dashboards. The blog provides guidelines for setting up a local development environment with Docker, illustrating the creation and deployment of event streaming pipelines using Stream DSL syntax. Additionally, it highlights the integration of Kafka Streams applications within these pipelines and offers insights into monitoring, security, and operational auditing. Concluding with a preview of future topics, the blog sets the stage for exploring advanced event streaming topologies and continuous deployment patterns in subsequent parts.