[Technology][Application][Data] — Generating Synthetic Data for Streaming Applications

Recently I have been to an event which held in Gurgaon, hosted by Kafka. I covered crucial aspects of generating synthetic data for testing data streaming applications. This blogs summarizes the key discussions from the event, focusing on the challenges of using real production data and highlighting various tools and best practices for synthetic data generation for robust testing of the applications.

• Synthetic Data Generation: Techniques and tools for creating realistic test data without compromising privacy.
• Robust Application Testing: Strategies to enhance application reliability and performance under various conditions.
• Simulating System Failures using Chaos Monkey & Gatline.

Challenges of Using Real Production Data

1. Privacy and Security:

• Real data often contains sensitive and personal information.
• Exposing such data in a testing environment can violate privacy laws and result in security breaches.

2. Data Completeness:

• Real datasets may not include all scenarios needed for comprehensive testing.
• Specific edge cases and peak load situations are often hard to replicate with real data.

3. Lack of Control:

• Real data is unpredictable and doesn’t allow testers to…