This blog series aims to provide insights into configuring Apache Kafka for a production-grade environment. The focus will be on exploring various configuration options and understanding how they interact and impact each other to achieve specific outcomes, often at the expense of other factors. We will develop a sample project, beginning with a POC to better define requirements and determine how to achieve them by fine-tuning Kafka. While the solution will be deployed locally using Docker Compose, minimal adjustments will be needed to adapt it to a lightweight K3s or AWS ECS deployment or even a more robust production setup.

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During the recent attempts to find a cheaper alternative to big cloud players such as AWS or Azure, I found several options to deploy somewhat simple apps to provisioned VMs and have some sort of Load Balancing, HTTPS and other essentials things. Of course, this varies by your use case, and here I will be focusing on the “backend” part of your application that in most cases could be a single service, or a docker container running it.

A second blog post about AI Chatbots. I did not expect this, but anyway, you probably encountered a complex problem that your favorite AI chat can’t solve. Whether it be Gemini, ChatGPT or anything else, you probably thought about entering the same query into another chat, to see if its response is somewhat better. Not to mention, some of the AI models require monthly subscriptions, making this somewhat expensive. In this blog post, I am going to provide my current setup for querying multiple models, with a minimal but satisfactory UI at a very good price.

You might be familiar with the “Technology Camel” model proposed by Elizabeth Ghaffari and Barbara McNurlin, a modification of the traditional Technology Adoption Life Cycle (TALC) which visualizes the adoption of new technologies as a two-humped camel graph.1 While this image does not explain every wrong attitude towards AI chatbots, it serves as an ever-lasting truth to basically any new technology. There will simply always by a percentage of people who are not willing to dive into the all stuff new tech brings.