Hello guy’s, today’s we conduct short interview with SMACK about its architecture and there uses. Let’s start with of some introduction.
Interviewer: How would you describe your self ?
SMACK: I am SMACK (Spark, Mesos, Akka, Cassandra and Kafka) and belongs to all open source technologies. Mesosphere and Cisco collaboration bundles these technologies together and create a product called Infinity. Which is used to solved pipeline data challenges where the speed of response is matters like fraud detection system.
Interviewer: Why SMACK ?
Now day’s modern data-processing challenges are :
- Data is getting bigger or more accurately, the number of data source is increasing.
- Today, many modern business models data from one hour ago is practically obsolete.
- Data analysis becomes to slow to get any return on investment info.
- One modern requirement is to have horizontal scaling with low cost.
- We live in a age where data freshness matters many times more than the amount or size of data.
There are many challenges we are facing, SMACK exist because one technology doesn’t make an architecture. SMACK is a pipelined architecture model for data processing.
Interviewer: Lambda Architecture is data processing architecture and have advantage of both batch and stream processing methods, So, how SMACK different ?
SMACK: Yes, Lambda Architecture have these features, but most of the lambdas solutions cannot meet two needs at the same time :
- Handles a massive data stream in real time.
- Handles multiple and different data models from multiple data source.
For these. Apache Spark is responsible for real time analysis for both historical and recent and from massive information torrent and all such information and analysis results are persisted in Apache Cassandra. So, in the case of failure we can recover the real time data from any point of time. With lambda Architecture it’s not always possible.
Interviewer: SMACK can you briefly describe about you technologies ?
SMACK: Yes sure, as we discussed it is basically used for Pipeline data architecture for online data stream processing. There are lots of books and articles are available on each and every technology but we are using every technology for some specific purpose like:
- Apache Spark: Processing Engine.
- Akka: The Model.
- Apache Kafka: The Broker.
- Apache Cassandra: The Storage.
- Apache Mesos: The Container.
See, all are Apache projects with the exception of Akka.
Interviewer: Is, SMACK is only solution ?
SMACK: No, You can replace individual components as per you requirements like Yarn could be used as the cluster scheduler instead of Mesos and Apache Flink would be suitable batch and stream processing alternatives to Akka. There are many alternatives to SMACK.
Interviewer: Could you discuss one of your case study with us ?
SMACK: Yes, But not know. I need to go with my technologies for some hangout, that we will discuss further in our next interview.
Interviewer: Can I take one picture of you ?
SMACK: Yes sure, cheeezzzz …..