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azure sdks for python and custom urllib3 connection pools: a deep dive

the azure sdks for python, built on top of `requests`, leverage `urllib3` for underlying http communication. while the sdks provide robust default handling, scenarios like highly customized network configurations, sophisticated retry strategies beyond the sdk's built-in capabilities, or integration with specific proxy servers might necessitate using a custom `urllib3` connection pool. this tutorial will guide you through this process, explaining the rationale, steps, and potential pitfalls.

*why use a custom connection pool?*

the default `urllib3` connection pool within the azure sdks is generally sufficient. however, you might need a custom pool in these situations:

*advanced retry logic:* the sdk provides retry mechanisms, but a custom pool allows fine-grained control over retry conditions, exponential backoff strategies, and jitter.
*custom proxy configuration:* the sdk supports proxy settings, but a custom pool enables more complex scenarios like authentication with proxies or handling proxy failures differently.
*specific network configurations:* you might need to configure tls settings, timeouts, or connection limits differently than the sdk's defaults.
*monitoring and logging:* a custom pool allows integration with your logging and monitoring infrastructure to track connection activity.
*circuit breakers:* implement sophisticated failure detection and circuit-breaking mechanisms to prevent cascading failures.


*implementing a custom urllib3 connection pool*

we'll focus on the azure blob storage sdk as an example. the principles apply similarly to other azure sdks. the key is to provide a custom `transport` object to the client.

*1. setting up the environment:*

ensure you have the necessary packages installed:



*2. creating a custom transport:*

this is the core of the solution. we'll create a class that inherits from `requests.adapters.httpadap ...

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