demo-scene VS kafka-lag-exporter

Hi HN!

I recently created a website that displays your votes on classically debated questions like 'tabs or spaces?'?

One of my favorite things about it is that if you leave the result progress bars up, and someone else votes, you can see the results change in real time.

I used the confluent-kafka-javascript(https://github.com/confluentinc/confluent-kafka-javascript) client which is currently in early access.

Votes are sent to a Kafka topic deployed in Confluent Cloud, and the code for the frontend is on Amplify while the code creating the route and Kafka clients is on EC2.

I put a version of the code here(https://github.com/confluentinc/demo-scene/tree/master/confl...) so you can follow along and deploy a similar project for yourself. I'm hoping it makes a fun way for you to learn this Kafka JavaScript client.

In the future, I'd like to implement features like allowing you to change your vote, or a board summarizing votes like "30% of developers who voted for X voted for Y".

Enjoy! Looking forward to your feedback.

Here’s a great place to dig into things: https://developer.confluent.io

Once you’ve decided on a language to focus on, it’s time to start filling those knowledge gaps. Don’t be discouraged by this step. We all have knowledge gaps, and filling them can be very rewarding. First, you’ll want to make sure you have a good understanding of Kafka basics. Fortunately, there are many resources to help you with this. A web search will turn up many great books and other resources. And, of course, Confluent Developer offers interactive courses ranging from introductory (Apache Kafka 101) to advanced (Kafka Internals), full documentation, and other content to help you get started.

Confluent Developer: Learn Apache Kafka through Confluent Developer tutorials, documentation, courses, blog posts, and examples.

Spend some time on https://developer.confluent.io , especially https://developer.confluent.io/get-started/java/ and look at https://github.com/confluentinc/examples . Those will give really practical examples for how to set up your configs and start consuming

FWIW you'll find a bunch of promo codes over at developer.confluent.io

Kafka streams is a Java library built on the producer/consumer APIs designed to create event-driven microservices on top of Kafka. In general, I recommend exploring https://developer.confluent.io to learn more

For example: https://github.com/confluentinc/demo-scene/tree/master/kafka-connect-zero-to-hero

should I be reading a different material for a first Kafka project and working with a different kind of setup? Now, I can't be unbiased on this one ;) One of the things we're doing with Confluent Developer is to try and create a resource for people to learn Kafka from the ground up, whether they ultimately decide to pursue it on Confluent or not. The fundamentals of Kafka that you'll be learning are going to be as applicable whether you're using Apache Kafka self-managed, or Confluent, or AWS' MSK, or whatever else. Personally I'd this stage I'd use whatever setup you find easiest and least friction to your learning journey. As u/louisvell mentioned, /u/stephanemaarek's courses on Udemy are also very popular, if you wanted a "second opinion" on how to approach learning Kafka.

- https://github.com/prometheus/jmx_exporter - https://github.com/lightbend/kafka-lag-exporter (Export Kafka Topics Lag Metrics) - https://github.com/danielqsj/kafka_exporter (Export Kafka Metrics) - https://github.com/obsidiandynamics/kafdrop (Topic Administration tool - create/edit/delete topics & view messages)

Kafka Lag Exporter is not part of the Apache Kafka project nor the Confluent Platform. It’s an open-source project under Apache-2.0 License to export Consumer Lag with reporters like Prometheus, Graphite, or InfluxDB. Kafka Lag Exporter enables to monitor Consumer Lag but it also allows to estimate the Time Lag. This metric shows how far a Consumer group is behind the last produced record in terms of time. It shows the actual latency of a consumer application. For more information about this estimation, you can read the chapter of the documentation Estimate Consumer Group Time Lag