Yeah, okay, so on the each day basis we process around 10 to 15 TB of data. So that data basically what we have, what we do is like we first, first pipeline level is like we spoil the data to and push that data to Amazon Kinesis. Now we are transforming this pipeline to the Kafka level. So what, what will happen like the source will directly, directly put that data, post that data to our Kafka topic. So what will happen, we are removing this Polar side and the Kinesis side and instead of that Kafka will be there. Kafka is like a streaming server. So like a source will directly put the data to the Kafka topic and we will analyze that and we will transform that data for our own storage and transform the data basically to our format. So that's how we have introduced Kafka for our real-time data streaming and the data processing. Okay. Apart from that coming to the scalability of the Kafka and scalability of the data processing systems, the way our Kafka cluster is designed, it can be scalable. So consider the, there is like 10, 10 machines running in the Kafka clusters. So whenever it required the huge amount to be, amount of data to be coming, we can easily scale our Kafka cluster based on the given, given parameter, how much machines or what kind of machines we need, we can easily scale that up. Okay. It totally depends if we have created an auto scalable cluster or not. So it totally depends on that. So coming to the processing, the processing of data, data scale, scale data processing. So basically as we are running the Apache Beam, Apache Beam for our executors, okay. So it's a solo executor basically based on the Kafka group ID and all. So we can easily scale the replicas of it. Basically consider that from a single topic and Apache Beam, 10 executors are running. Okay. So if we need more executors, we can easily scale that up based on the amount of data has been put in for that particular kind of a data in the Kafka topic. So that's how we introduced Kafka and the scalability of processing and the scale of our data. So, yeah. 
