fidzu : programming

Modern Java applications require robust observability and automated intelligence to ensure reliability at scale. Dynatrace's AI-driven platform continuously learns application behavior, establishes statistical baselines and applies deterministic, causation based analysis to detect anomalies and pinpoint root causes.

By correlating metrics, logs, traces, and topology context across applications, services and infrastructure, Dynatrace can automatically highlight the true source of problems and assess their impact. This drastically reduces alert noise and MTTR .

11 May 2026 12:00pm GMT

Building real-time applications means balancing user responsiveness with heavy backend processing. A proven solution is to decouple heavy workloads using events and asynchronous processing. In this approach, a Spring Boot application quickly publishes events to Kafka instead of processing requests inline. Then Kafka consumers (with AI/ML logic) handle the data in the background, and the results are pushed to clients in real time via WebSockets. This article highlights three key patterns enabling this architecture:

1. Event Production with Spring Boot and Kafka
2. AI-Driven Processing in Kafka Consumers
3. Real-Time WebSocket Delivery to the Frontend

Event Production with Spring Boot and Kafka

The first step is capturing an event and publishing it to Kafka. By offloading work to Kafka the application can respond immediately to the user without waiting for processing. Spring Boot's integration with Apache Kafka provides a KafkaTemplate to send messages to topics.

08 May 2026 2:00pm GMT

PUT requests are typically used for updating an existing resource. This means replacing the current data for the target resource with the data sent in the API request body.

Just like POST requests, the content-type header is important because it tells the server how to interpret the data we're sending.

07 May 2026 2:30pm GMT