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Apache Kafka in 1 hour for C# Developers - Gui Ferreira - NDC Porto 2023
Get a crash course in Apache Kafka for C# developers! Learn the essentials of building real-time data pipelines, event-driven architectures, and more in just one hour.
- Apache Kafka is a distributed streaming platform that can be used for building real-time data pipelines and event-driven architectures.
- Kafka is designed to handle high-volume and high-velocity data streams, making it suitable for big data and real-time analytics applications.
- Kafka provides a way to decouple producers and consumers, allowing for greater flexibility and scalability.
- Kafka partitions allow for load balancing and horizontal scaling, making it easier to handle large volumes of data.
- The concept of message key is important in Kafka, as it allows for efficient storage and retrieval of messages.
- Kafka provides built-in support for idempotence, which ensures that messages are processed at most once, even in the event of failures.
- The concept of consumer group is important in Kafka, as it allows for load balancing and fault tolerance.
- Kafka provides built-in support for replication and persistence, making it suitable for mission-critical applications.
- The concept of offset is important in Kafka, as it allows for efficient consumption of messages.
- Kafka provides built-in support for compression, which can help reduce network and storage costs.
- The concept of leader election is important in Kafka, as it allows for efficient partitioning and load balancing.
- Kafka provides built-in support for partitioning, which allows for efficient storage and retrieval of messages.
- The concept of topic is important in Kafka, as it allows for efficient communication between producers and consumers.
- Kafka provides built-in support for event-driven architectures, making it suitable for real-time analytics and big data applications.
- The concept of producer is important in Kafka, as it allows for efficient production of messages.
- Kafka provides built-in support for consumer, which allows for efficient consumption of messages.
- The concept of event is important in Kafka, as it allows for efficient communication between producers and consumers.
- Kafka provides built-in support for schema registry, which allows for efficient serialization and deserialization of messages.