What are the best practices for using Prometheus with Python?
An example of an AI chatbot conversation about Prometheus best practices in Python applications.
What are the best practices for using Prometheus with Python?
When using Prometheus with Python, it's essential to follow best practices like using the official client library, structuring your metrics properly, and ensuring efficient data collection.
Can you explain how to structure metrics properly?
Sure! Structure your metrics by using meaningful names, labels for dimensions, and avoid high cardinality to ensure efficient querying.
What is high cardinality and why should I avoid it?
High cardinality refers to metrics with a large number of unique label values. It can lead to performance issues and increased storage costs.
How can I efficiently collect metrics in a Python application?
You can efficiently collect metrics by using asynchronous libraries, batching your metrics, and scraping them at appropriate intervals.
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