
Explore Spark Streaming's API, real-time data processing challenges, and key internal processes for successful production deployment through practical examples.

Explore serverless data processing using Lambda and Step Functions for efficient, large-scale data handling. Learn techniques for real-time processing and event-driven architectures without complex frameworks.

Explore real-time anomaly detection using machine learning on logs and traces. Learn to treat application data holistically, enabling intelligent monitoring and complex issue identification beyond traditional alerts.

Learn to build a real-time soil moisture monitoring system for houseplants using ksqlDB, exploring stream processing concepts and practical IoT applications.

Explore building data streaming apps at scale using Spring, from edge to multi-cloud. Learn to integrate Spring with Kafka, MQTT, and other technologies for real-time processing in IoT and cloud environments.

Explore advanced stream processing on edge devices for real-time data analysis, enabling features like anomaly detection and distributed machine learning using open-source software.

Explore the future of streaming technology and its impact on Node.js development with insights from industry expert Matteo Collina.

Explore GPU-accelerated real-time DSP for radio astronomy, focusing on BLADE software's innovative techniques for processing massive data streams from the Allen Telescope Array.

Esplora l'elaborazione di flussi di dati GPS in tempo quasi reale, analizzando tecniche e sfide per gestire efficacemente grandi volumi di informazioni geospaziali.

Explore Azure Stream Analytics for real-time IoT data processing. Learn to capture, analyze, and present device data streams, integrating with Microsoft's IoT suite for business insights.

Explore Complex Event Processing from a high-level perspective, understanding its concepts, applications, and impact on data analysis and decision-making in real-time systems.

Explore the transformation to real-time enterprise systems with insights on challenges, solutions, and the future of data-driven businesses in this keynote by Neha Narkhede.

Explore Web Bluetooth API and Functional Reactive Programming to build a mobile bike computer using real-time sensor data and cycle.js for data stream transformation.

Explore audio visualization in browsers using Web Audio API, custom properties, and Web MIDI API. Learn innovative techniques for real-time data processing and hardware control.

Explore distributed data processing frameworks for handling large-scale event streams. Learn about Apache Storm, Spark, and emerging platforms to build reliable, scalable systems for real-time data processing.

Explore Apache Kafka's potential with Dyalog APL, learning about distributed event streaming, real-time data pipelines, and practical implementation examples.

Explore declarative interfaces and GraphQL for streamlined streaming app development, focusing on reusability and best practices from Airbnb's experience.

Explore high-performance data streaming using gRPC and OpenTelemetry in Cisco ThousandEyes. Learn to manage heavy traffic and adapt to changing test configurations in shared environments.

Explore WebAssembly's potential in revolutionizing real-time stateless streaming pipelines for Kafka, focusing on low-latency, high-volume data management.

Explore challenges and clever solutions for expanding Kafka infrastructure. Learn to optimize resources, streamline pipelines, and refocus on core business objectives as your system grows.

Explore Apache Kafka's next-generation rebalance protocol, enhancing stability and scalability for consumer groups in data streaming architectures.