System Integration: Kafka is often used to integrate distributed systems, allowing Java applications to send and receive messages asynchronously. This is useful for connecting microservices, legacy systems, and other components of a distributed architecture.
Stream Processing: The Kafka Streams API enables Java developers to process data in real-time directly within Kafka. This is useful for implementing streaming processing pipelines, such as filtering, transformation, and data aggregation.
Asynchronous Messaging Systems: Kafka is a popular choice for implementing asynchronous messaging systems in Java, where messages are produced and consumed independently and asynchronously. This is useful for communication between distributed application components and pub/sub messaging systems.
Event Storage: Kafka can be used as a durable and fault-tolerant event storage system. Java applications can write events to Kafka for purposes such as auditing, retrospective analysis, and fault recovery.
Monitoring and Log Tracking: Kafka is often used to collect and process logs from Java applications, such as server logs, application logs, and performance metrics. This is useful for real-time monitoring, fault analysis, and problem diagnosis in distributed systems.
Anacarmem Araújo Rêgo
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Utilization of Apache Kafka in the Java Ecosystem: Scalability, Real-Time Processing, and System Integration
How to reduce TTFB
In the past few years in the web dev world, we’ve seen a significant push towards rendering our websites on the server. Doing so is better for SEO and performs better on low-powered devices, but one thing we had to sacrifice is TTFB.
In this article, we’ll see how we can identify what makes our TTFB high so we can fix it.
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