What is Kafka-docker? Here come the steps to run Apache Kafka using Docker i.e. Kafka-docker. i. Pre-Requisites for using Docker At very first, install docker-compose a. Install Docker Compose We can run compose on macOS, Windows, as well as 64-bit Linux. Now, to install Kafka-Docker, steps are: 1. For any meaningful work, Docker compose relies on Docker Engine. Hence, we have to ensure that we have Docker Engine installed either locally or remote, depending on our setup. Basically, on desktop systems like Docker for Mac and Windows, Docker compose is included as part of those desktop installs. 2. Then, Install Compose on macOS Docker for Mac and Docker Toolbox already include Compose along with other Docker apps, so Mac users do not need to install Compose separately. Docker install instructions for these are here: 3. Uninstallation of Kafka-docker If we installed it using curl, then to uninstall Docker Compose: sudo rm /usr/local/bin/docker-compose If we installed using pip, then to uninstall Docker Compose: pip uninstall docker-compose After installing compose, modify the KAFKA_ADVERTISED_HOST_NAME in docker-compose.yml to match our docker host IP Note: Do not use localhost or 127.0.0.1 as the host IP to run multiple brokers. If we want to customize any Kafka parameters, we need to add them as environment variables in docker-compose.yml. By adding environment variables prefixed with LOG4J_, Kafka’s log4j usage can be customized. These will be mapped to log4j.properties. For example LOG4J_LOGGER_KAFKA_AUTHORIZER_LOGGER=DEBUG, authorizerAppender NOTE: There are various ‘gotchas’ with configuring networking.
In recent years, IoT has grown from a complex concept to a prime concern for many organisations. With new ways of leveraging the potential of interconnected devices constantly being implemented across industries, it’s clear to see that IoT solutions have already become a transformative force for many enterprises. Learn more about the current state of the Internet of Things and explore the best examples of enterprise IoT up to date.
Nearly every business leader (99% according to an HBR study) recognizes the need to build a data driven organization. However, so many struggle to use data for a variety of reasons, a big one of them being that data exists in all sorts of places. This is especially the case with startups, who use a number of out of the box tools that don’t connect to each other, and that only offer so much granularity and flexibility. The solution? A data warehouse.
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