Explore the role of Event-Driven Architecture in real-time data processing, including streaming applications, event analytics, monitoring systems, data transformation, and integration with big data technologies.
Explore the role of visualization dashboards in microservices observability, learn how to select the right tools, design intuitive layouts, and implement real-time data streaming for actionable insights.
Explore techniques for implementing real-time data updates in event-driven user interfaces, including WebSockets, Server-Sent Events, real-time databases, GraphQL subscriptions, and more.
Explore the role of edge computing in event-driven IoT architectures, focusing on local event processing to reduce latency, bandwidth usage, and enhance real-time decision-making.
Explore the role of event streaming platforms in microservices, including popular platforms, data ingestion, real-time processing, and integration strategies.
Explore the integration of IoT devices with microservices to optimize logistics and supply chain operations, focusing on connectivity, scalability, security, and real-time data processing.
Explore the practical applications and best practices of the Observer pattern in JavaScript and TypeScript, including integration with event systems, real-time data feeds, and strategies for maintaining modularity and scalability.
Explore the benefits of streaming architectures, including real-time data processing, low latency, scalability, and more. Learn how these systems enhance user experiences and integrate seamlessly with other technologies.
Explore the intricacies of windowing and aggregations in stream processing, including types of windows, implementation strategies, and practical examples using Apache Flink.
Explore Kafka Streams and kSQL for scalable, real-time stream processing and analytics in Apache Kafka. Learn about key features, implementation, and best practices.