Testing Data-driven Microservices

#artificialintelligence 

Testing always opens a lot of questions, which cases to test? what are the edge cases? Which testing platform to use..etc. But when it comes to testing microservices, the level of complexity is raised up a notch. As they often cater to massive batches of data that are very varied in their nature. Besides, microservices architecture requires the data to be passed around between components (MQ, DataBase…), which can cause erosion and damages that are hard to detect -- i.e.: when the data streams into MQ between microservices and gets rounded, or casting error occurs which causes "silent" issues.

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