Apache Kafka Clusters: Ensuring Scalability and Fault Tolerance
Learn how Apache Kafka clusters enable scalable and fault-tolerant streaming applications. Explore replication, partitioning, and best practices for cluster performance.
Apache Kafka
Apache Kafka is a distributed event streaming platform used by developers to build real-time data pipelines and streaming applications at scale. With high throughput, fault-tolerant capabilities, and support for various integrations, Kafka enables reliable and efficient data processing across diverse systems, making it popular in data-driven organizations.
Apache Kafka and Apache Spark Integration: Stream Processing
Learn how to integrate Apache Kafka and Apache Spark for real-time stream processing. Explore the benefits, setup steps, and write a simple Spark Streaming application to consume Kafka data.
Apache Kafka Architecture: Exploring the Core Components
Explore the core components of Apache Kafka - brokers, topics, partitions, producers, consumers, and consumer groups - that work together to provide a scalable and reliable messaging system.
Apache Kafka Data Serialization: Avro vs. JSON
"Avro and JSON are popular data serialization formats for Apache Kafka. Avro offers compactness and schema evolution, while JSON provides human readability and wide language support."
Event-Driven Microservices with gRPC and Apache Kafka
Explore the power of event-driven microservices with gRPC and Apache Kafka. Create decoupled systems for large-scale data processing and seamless integration.
Apache Kafka Connectors: Extending Kafka Functionality
Apache Kafka Connectors provide a scalable and easy way to integrate Kafka with external systems. Learn how they work, how to implement them, and explore popular connectors in this blog post.