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Event streaming using Apache Kafka

There are levels of event recording in accordance with the use cases for which we are tracking like application logging (Log4j levels). Now a mission-critical application (like transactions) will generate a huge number of events, this will enable to debug/analyse in case of any failure or audits. For low to medium priority apps, we can keep it simple and less frequent. Before we get into details of Kafka-enabled event streaming,
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Why event stream processing is leading the new ‘big data’ era

Big data is probably one of the most misused words of the last decade. It was widely promoted, discussed and spread by business managers, technical experts, and experienced academics. Slogans like ‘data is the new oil’ were widely accepted as unquestionable truth.  But with this hype, different ideas and solutions have been considered, and then rejected. Event stream processing may provide the answer. The rise and fall of Hadoop These
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5 Things to Know About Event-Driven APIs and Apache Kafka

APIs are becoming the crux of any digital business today. They provide a multitude of internal and external uses, including making B2B connections and linking building blocks for low-code application development and event-driven thinking. Digital business can’t exist without event-driven thinking. There are real benefits to developing event-driven apps and architecture—to provide a more responsive and scalable customer experience. Your digital business requires new thinking. New tools are required to adopt event-driven