While Microservices architecture leverages crucial advantages like Scaling Up or improved fault tolerance, it also introduces increased communication, debugging and testing complexity.
Microservices Observability is crucial for understanding how apps are functioning, identifying and preventing performance bottlenecks in advance. In many use cases, Distributed Systems process inputs and produce some kind of output.
It turns out that your system may become slower depending on the nature of the input data.
How can you detect what kind of data produces bottlenecks?
How can you prevent system failures by predicting performance disasters?
Let’s discuss this topic and see how some basic Data Science techniques can help you to better understand your system weaknesses end to end.
Whether you are interested in Microservices Architecture from the very big picture, or you’re curious about data mining and data visualisation applied to software engineering performance analysis, this meetup will be interesting for you.
No coding experience is required!
About Fernando Contreras
Fernando is a software engineer at D-EDGE Hospitality Solutions. He enjoys working on challenging projects where performance is key to business success. He graduated with a Computer Science bachelor’s followed by a Master’s degree in Software Engineering but has followed a self-taught and online learning path in Data Science and Machine Learning. He’s very enthusiastic about knowledge sharing and this is why he also has a blog where he writes tech articles about new technologies and programming best practices:
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