Data Analysis with Python

Part 4 – Adding scalability with Apache Kafka and IBM Streams Designer

Note

Note: This section is optional. It demonstrates how to re-implement parts of the data pipeline with cloud-based streaming services to achieve greater scalability

Implementing the entire data pipeline in a single Notebook gave us high productivity during development and testing. We can experiment with the code and test the changes very rapidly with a very small footprint. Also, performances have been reasonable because we have been working with a relatively small amount of data. However, it is quite obvious that we wouldn't use this architecture in production and the next question we need to ask ourselves is where are the bottlenecks that would prevent the application from ...