
Learn cost-effective streaming optimization techniques to drastically reduce infrastructure expenses. Discover simple SQL methods and advanced strategies for distributed storage and compute stacks.

Uncover hidden Kafka cloud costs, optimize spending, and justify deployments. Learn to calculate and anticipate bills, explore cost-reduction strategies, and increase efficiency in cloud-based Kafka usage.

Explore Kafka tiered storage implementation, deployment, and production learnings at scale. Gain insights on principles, workloads, extended features, and issue mitigation for improved scalability and efficiency.

Explore key event-driven architecture patterns for robust, decoupled service communication using Apache Kafka. Learn to implement claim-check, content enricher, message translator, and outbox patterns through live demos.

Explore strategies for autoscaling Confluent Cloud resources. Learn when and how to implement scaling for cloud-based Kafka, handle ephemeral workloads, and create effective monitoring policies for optimal performance.

Explore Kafka Streams' internal architecture for efficient application deployment and tuning. Learn threading models, partition assignment, and key configurations to optimize performance and scalability.

Explore Apache Kafka's ecosystem, including Producer and Consumer libraries, Connect, Streams, and Schema Registry. Gain insights for implementing Kafka in your organization.

Explore Apache Pinot's real-time analytics capabilities for user-facing applications, leveraging streaming data from Apache Kafka to deliver rapid insights across diverse business domains.

Explore tradeoffs between workflow engines and event streaming brokers for microservices communication. Compare Apache Kafka and Temporal, examining their strengths and implementation challenges in various use cases.

Explore data modernization with Confluent and AWS. Learn migration strategies, cloud capabilities, and real-time streaming potential. Gain insights from success stories and best practices for unlocking data value.

Develop a real-time threat detection system using Kafka Streams. Learn to handle dynamic rule modifications, implement external data feeds, and apply best practices for stream processing.

Explore the evolution of real-time machine learning techniques, addressing low latency, dynamic data adaptability, and resource efficiency challenges in modern ML systems.

Explore the architecture and design of a real-time analytics platform, featuring sub-second latency, cloud-native services, and CDC streams for efficient data processing and customer insights.

Learn to manage massive IoT device networks using Kafka and MQTT for real-time data ingestion, analysis, and control in applications like vehicle communication and predictive maintenance.

Aprende a crear una Data Pipeline eficiente utilizando fluentbit, Kafka, Python y PostgreSQL. Domina la generación de KPIs y explora herramientas como CloudBeaver.

Explore Apache Kafka streams for building scalable, fault-tolerant streaming applications with parallel processing capabilities.

Explore Kafka's components, configurations, and internal workings for efficient big data applications and pub/sub models.

Explore Kafka's real-time data streaming capabilities, architecture, and Scala integration. Gain hands-on experience to effectively harness data streams for enhanced processing.

Explore event-driven architecture and Apache Kafka for building scalable, real-time systems with efficient data streaming and communication between components.

Learn to migrate Kafka clusters from ZooKeeper to KRaft using Strimzi, covering the migration process, Strimzi's support, and a practical demonstration with step-by-step guidance.

Discover strategies for managing Strimzi in large enterprises. Learn to handle scaling challenges, implement effective topic management, and empower teams for smoother Kafka operations.