<p>There is a python app for machine lerning that developer have running in docker. Azure container instance in particular. They are using micromamba:0.15.3 and inside dockerfile they also install nginx for web server.
Docker file at the end will run: <code>CMD [&quot;./start.sh&quot;]</code></p>
<p>and script inside:</p>
<pre><code>service nginx start 
streamlit run app.py --theme.base &quot;dark&quot; --server.address localhost --server.port 5000  --server.enableCORS=false
</code></pre>
<p>Also I saw that they use anaconda locally to run web app. This also runs streamlit</p>
<p>Now I would get rid of nginx part in dockerfile since will be moving to k8s and will be using nginx ingress controller + ingres as vhost which will be pointin to the running python service</p>
<p>Which is the Docker image that I should use for this? what the difference between using conda, miniconda or python official image? Don´t  I just need python image  where you can add streamlit, like <a href="https://www.section.io/engineering-education/how-to-deploy-streamlit-app-with-docker/" rel="nofollow noreferrer">here</a>?</p>
<p><a href="https://hub.docker.com/r/mambaorg/micromamba" rel="nofollow noreferrer">https://hub.docker.com/r/mambaorg/micromamba</a></p>
<p><a href="https://hub.docker.com/_/python" rel="nofollow noreferrer">https://hub.docker.com/_/python</a></p>

Chanafot
<p>You are right, you can create a simple Dockerized App derived from an official Python Image, Create a virtual environment and install a requirements.txt file in the build stage into the environment for streamlit and other dependencies. Anaconda and Miniconda just wrap the management of python virtual environments. If there is an environment.yml instead of requirements.txt you can use <code>conda create -f environment.yml</code> to create the environment in your Docker Container.</p>
