Event Driven Microservices with Spring Cloud Stream. Event driven architecture requires forethought, creating the scaffolding in order to integrate popular event Spring Cloud Stream platforms can become complicated. Spring Cloud Stream is a framework for message-driven microservice applications.
Eventual Consistency with Spring for Apache Kafka: Part 1 of 2. Using Spring for Apache Kafka to Manage a Distributed Data Model Across Multiple Microservices.
Eventual Consistency with Spring for Apache Kafka: Part 2 of 2. Using Spring for Apache Kafka to manage a Distributed Data Model in MongoDB across multiple microservices.
Today we're taking a look at Kafka. What is Kafka, the concepts as well as a hands-on walkthrough. We build a Kafka docker container image, a zookeeper image, then proceed to start 3 Kafka instances linked to Zookeeper.
This tutorial/crash course video is about ksqlDB, where I introduce ksqlDB and explain how to use it. where we learn how to create a stream, insert data into the stream, select data from stream, consume events, aggregate data and store into tables, joins two streams and emit result in a kafka topic for consumption.
Ich erzähle ein paar Grundlagen zu Kafka Streams, wie z.B KStream, Ktable und Joins. Danach erfinde ich ein Praxisbeispiel und baue dazu Beispiel Applikationen mit Spring Boot.
Self-managing a distributed system like Apache Kafka ®, along with building and operating Kafka connectors, is complex and resource intensive.
In this article, look at change data capture from PostgreSQL to Azure Data Explorer using Kafka Connect.
Azure Cosmos DB Cassandra API is a fully managed cloud service that is compatible with Cassandra Query Language (CQL) v3.11 API. It has no operational overhead, and you can benefit from all the underlying Azure Cosmos DB capabilities such as global distribution, automatic scale-out partitioning, availability and latency guarantees, encryption at rest, backups, etc.
In this article, the author discusses the importance of a database audit logging system outside of traditional built-in data replication, using technologies like Kafka, MongoDB, and Maxwell's Daemon.
Predicting and Visualizing streaming Data through Python. Predicting pedestrian traffic and visualizing on a map.
We released another update of the Big Data Tools plugin recently, and this article is an overview of its new features. If you are still wondering about it then this article is for you. The previous release was a momentous event for us as the plugin left the Early
Running Apache Kafka Efficiently on the Cloud. In this episode, Adithya covers how to run Kafka more efficiently on Confluent Cloud and dives into the following: ► Memory allocation on an instance running Kafka ► What is a JVM heap? Why should it be sized? How much is enough? What are the downsides of a small heap? ► Memory usage of Datadog, Kubernetes, and other processes, and allocating memory correctly ► What is the ideal page cache size? What is a page cache used for? Are there any parameters that can be tuned? How does Kafka use the page cache? ► Testing via the simulation of a variety of workloads using Trogdor ► High-throughput, high-connection, and high-partition tests and their results ► Available cloud hardware and finding the best fit, including choosing the number of instance types, migrating from one instance to another, and using nodepools to migrate brokers safely, one by one ► What do you do when your preferred hardware is not available? Can you run hybrid Kafka clusters if the preferred instance is not widely available? ► Building infrastructure that allows you to perform testing easily and that can support newer hardware faster (ARM processors, SSDs, etc.)
Apache Kafka and MQTT (Part 5 of 5): Smart City and 5G. Blog series Part 5: Apache Kafka and MQTT for Smart City, Government, Citizen, Connected Vehicles, 5G: Architectures, real-world examples. Apache Kafka and MQTT are a perfect combination for many IoT use cases.
We will explore potential reasons for Kafka consumer lag and what you could do when you experience lag. Kafka powers compelling consumer experiences in the companies. Consumer lag is a big challenge in Kafka. Understand and address consumer lag in Kafka.
Confluent and Microsoft are making event streaming easier than ever by alleviating the infrastructure management needs that pull developers away from building critical applications.
Comparison of Open Source Apache Kafka vs Vendors including Confluent, Cloudera, Red Hat, Amazon MSK. Let's see how big Kafka really is.
Learn how to use the Kafka Consumer API so you can more easily work with Kafka in your Rust projects. A hands-on guide to teach you how to interact with Kafka using the Rust programming language.
Apache Kafka has several successful cases in the Java world. This post will cover how to benefit from this powerful tool in the Spring universe.
Tips About Kafka Connect On Heroku You Can't Afford To Miss. Find out carefully. It will help your projects complete quickly.