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contributions/executable-tutorial/samkh-miladsf/README.md

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+# Assignment Proposal
+
+## Title
+Monitoring ML Model Predictions with Prometheus
+
+## Names and KTH ID
+
+  - Sam Khosravi ([email protected])
+  - Milad Farahani ([email protected])
+
+## Deadline
+- Task 3
+
+## Category
+- Executable tutorial
+
+## Description
+
+In this tutorial we will set up a python script that logs a ML models predictions. 
+This is integrated with Prometheus which will mointor them. 
+The goal is to learn how to integrate Prometheus with a Python application, which is then will be able to monitor the model to understand if it for example will work well when put into production.
+
+ **Relevance**
+
+Monitoring ML model prediction with Prometheus is highly relevant to DevOps because it introduces automation and observability to the machine learning lifecycle. 
+In DevOps, ensuring that systems are continously monitored for performance and reliability is crucial and this extends to machine learning models in production. 
+By integrating Prometheus to track metrics like prediction accuracy or latency, teams can proactively identify issues to reduce downtime and improve model reliability.