detekt VS ApacheKafka

In protection rules, I added build workflow in Require status checks to pass before merging. This is to ensure that before merging code in master branch, build should run successfully. I also added Jacoco Code Coverage to make sure that enough unit tests are available in project and Detekt to make sure that code in project is readable. I added them in build configuration. Even if one of them gives error, build will fail. Whenever, someone push code in pull request, build action will run and check if build is running successfully or not.

Detekt

ext { // https://github.com/detekt/detekt/releases detektVersion = "1.17.0" } dependencies { classpath 'com.android.tools.build:gradle:7.0.0' classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:1.4.32" ## DETEKT DEPENDENCY classpath "io.gitlab.arturbosch.detekt:detekt-gradle- plugin:$detektVersion" }

I haven't looked through it completely, but have you considered adhering to detekt and ktlint as well?

Senden an Kafka (d. h. Senden der Daten an Apache Kafka)

Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a machine's temperature exceeds a certain threshold, a streaming platform can instantly trigger an alert and engineers do timely maintenance.

Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time.

*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...)

RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput.

Apache Kafka is a distributed streaming platform to share data between applications and services in real-time.

also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.