Kafka

Apache Kafka is known for its ability to process a huge quantity of events in real time. However, to handle millions of events, we need to follow certain best practices while implementing both Kafka producer services and consumer services. Before start using Kafka in your projects, let’s understand when to use Kafka: High-volume event streams. When your application/service generates a continuous stream of events like user activity events, website click events, sensor data events, logging events, or stock market updates, Kafka’s ability to…

In today’s microservices and event-driven architecture, Apache Kafka is the de facto for streaming applications. However, setting up Kafka for local development in conjunction with your Spring Boot application can be tricky, especially when configuring it to run locally.  Spring Boot application provides support for Kafka integration through the spring-kafka maven package. To work with spring-kafka, we need to connect to the Kafka instance. Typically, during development, we would just run a local Kafka instance and build against it. But…

The rise of agentic AI has fueled excitement around agents that autonomously perform tasks, make recommendations, and execute complex workflows blending AI with traditional computing. But creating such agents in real-world, product-driven environments presents challenges that go beyond the AI itself. Without careful architecture, dependencies between components can create bottlenecks, limit scalability, and complicate maintenance as systems evolve. The solution lies in decoupling workflows, where agents, infrastructure, and other components interact fluidly without rigid dependencies. This kind of flexible, scalable…

Collaboration tools are rapidly evolving to meet modern demands. Adaptive frameworks stand out by delivering real-time, personalized updates tailored to individual users. These frameworks overcome the rigidity of traditional systems, enhancing efficiency, fostering innovation, and transforming industries like healthcare, education, and remote work. This paper delves into their technical principles, practical applications, and future potential, illustrating how adaptive frameworks redefine collaboration. Introduction The inefficiencies of traditional collaboration tools — static interfaces, impersonal workflows, and delayed updates — have long hindered…

In Part 1, we covered several key topics. I recommend you read it, as this next part builds on it. As a quick review, in part 1, we considered our data from the grand perspective and differentiated between data on the inside and data on the outside. We also discussed schemas and data contracts and how they provide the means to negotiate, change, and evolve our streams over time. Finally, we covered Fact (State) and Delta event types. Fact events are…

An Apache Kafka outage occurs when a Kafka cluster or some of its components fail, resulting in interruption or degradation of service. Kafka is designed to handle high-throughput, fault-tolerant data streaming and messaging, but it can fail for a variety of reasons, including infrastructure failures, misconfigurations, and operational issues. Why Kafka Outage Occurs Broker Failure Excessive data load or oversized hardware causes a broker to become unresponsive, hardware failure due to hard drive crash, memory exhaustion, or broker network issues.…

Organizations start their data streaming adoption with a single Apache Kafka cluster to deploy the first use cases. The need for group-wide data governance and security but different SLAs, latency, and infrastructure requirements introduce new Kafka clusters. Multiple Kafka clusters are the norm, not an exception. Use cases include hybrid integration, aggregation, migration, and disaster recovery. This blog post explores real-world success stories and cluster strategies for different Kafka deployments across industries. Apache Kafka: The De Facto Standard for Event-Driven Architectures…

Every data-driven organization has operational and analytical workloads. A best-of-breed approach emerges with various data platforms, including data streaming, data lake, data warehouse and lakehouse solutions, and cloud services. An open table format framework like Apache Iceberg is essential in the enterprise architecture to ensure reliable data management and sharing, seamless schema evolution, efficient handling of large-scale datasets, and cost-efficient storage while providing strong support for ACID transactions and time travel queries.  This article explores market trends; adoption of table format…

In the constantly changing world of software architecture, AI microservices and event streaming are vital elements transforming the development of intelligent applications. Critically discussing the combination of AI microservices, Kubernetes, and Kafka, this article provides a fresh angle on building high-availability and scalable systems with AI technologies. The AI Microservices Revolution Hierarchical architectures of intelligent systems are gradually replacing hybrid and more differentiated ones. Otherwise, such unbundling of AI capabilities in microservices directly translates to unprecedented agility and scalability. In…