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A number of fast-growing tech giants (besides Apple) are pouring a ton of money into making ARM work for a ton of use-cases: Nvidia (trying to buy ARM Holdings from SoftBank) and Amazon (deep investment in the new Graviton processors) are the two that primarily come to mind.Īs you might know, in processors low energy consumption (and low heat dissipation) often equates to the ability to scale processing efficiently for large workloads. It’s a pretty amazing piece of engineering, and in many ways, I think that the ARM architecture is the future. The typical first reaction that you get when using this is “it runs my Docker stack without sounding like a plane taking off?”.
Running kafka in docker on mac pro#
Tip: Use docker-compose up -d to start the containers in the background of your terminal windowĪfter starting up the containers, you should see Kafka and ZooKeeper running.So I’ve been using my new M1-based MacBook Pro for a couple of months for a mix of development, email, and other things an open-source maintainer does day-to-day. Docker compose will start both ZooKeeper and Kafka together if necessary. If ZooKeeper is still running from the previous step, you can use ctrl + c / cmd + c to stop it. To start the Kafka broker, you can start a new terminal window in your working directory and run docker-compose up.
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The most basic setup consists of just one broker and one ZooKeeper node (blue) however, to add resilience, we’ll deploy two additional brokers into the cluster (green).Īgain, going through the configuration line by line: The below diagram depicts the architecture of the minimal Apache Kafka cluster we’ll be deploying. Kafka consumer: Client applications that read from topics.Kafka producer: Client applications responsible for appending records to Kafka topics.It acts as a configuration repository, maintaining cluster metadata and also implementing the actual mechanics of the cluster. ZooKeeper: Manages the overall controller status in the cluster.They’re responsible for the bulk of I/O operations and durable persistence within the cluster. Kafka broker: The message broker responsible for mediating the data between the producers and the consumers.Kafka cluster: A distributed system of Kafka brokers.We’ll be deploying a simple Kafka setup, consisting of the following components: This has made Kafka extremely popular for many large enterprise organisations, where applications range from pub-sub messaging to log aggregation. It just so happens to be exceptionally fault-tolerant, horizontally scalable, and capable of handling huge throughput.
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Kafka is essentially a commit log with a very simplistic data structure. Apache Kafka’s architecture is comparatively straightforward compared to other message brokers, such as RabbitMQ or ActiveMQ.
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