Okay, first I will explain you with the APIs, okay. Basically, the integration of API with your with your with our data pipelines and our data and our system is like, whenever there is an API endpoint that we need to source the data from, okay, what we need to do is like we need to hit that API, that API might be giving you a response with 500 articles or 500 records, you need to process that data to a particular service that might be Kafka, that might be that might be PubSub at the Google services or maybe any other queuing mechanism that you are using. Once that we pull the data, let's say, data of newspapers, you're gonna hit Times of India, their API for a particular article in a day, and they're providing 500 articles for 15 seconds. Okay, so what you want to do for each 15 seconds, you're gonna hit that API, collect that 1500 articles, put it to somewhere to process that data, let's say you put that 500 articles in a Kafka, from there, once the once the data is in a Kafka, you have already the you got the data already in your system, okay, that you need to process that how you need to process that other part. But from there, okay, once that you have in a Kafka, from there a consumer will go consumer in the sense that Apache Beam, Apache Beam pipeline, data pipeline will work, each and every article will be get consumed. And that will get transformed and transformed and pushed to your database. In our case, it's Elasticsearch, then we after transformation, after adding some kind of enhancement to the data, we push the data to Elasticsearch. From there, then API services are already running, we circulate that data to a different client based on the query. That's how we integrate the data coming from an API to the Kafka. Or instead of Kafka, you can for sure use Kinesis for Amazon Kinesis. Okay, let's come into the IoT devices. So here in case of IoT devices, most of the time the thing is like, you don't pull the data automatically, you don't pull the data. Okay, you need that IoT device to push that data to the Kafka. There can be 1000s of IoT devices, and that will be pushing 1000s of devices will be pushing their data to your Kafka. From there, the pipeline will remain the same. So based on the data, type of data, type of IoT devices, let's say, IoT cars, IoT bikes, and IoT scooty will be having different kind of data, okay, or that you will be creating a different kind of a topic in a Kafka. Okay, based on the topics, you will be processing your executors will be processing your data based on the requirements. So that is how IoT data can be integrated in the Kafka or the data systems that we have.
