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Azure is a cloud computing service created by Microsoft for building, testing, deploying, and managing applications and services through a global network of Microsoft-managed data centers.

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infracost
bobziuchkovski
bobziuchkovski commented Aug 16, 2021

Is your feature request related to a problem? Please describe.
Yes. We've inherited a terraform repo with a lot of legacy problems. We've introduced checkov to ensure new config going
forward meets our standards. We've also generated baseline files for all of the existing legacy terraform config, so that we only fail checks for new problems. However, we'd like to keep visibility on all

azure-sdk-for-net
jsquire
jsquire commented Aug 23, 2019

Summary

The Event Hubs client library aims to be mockable and fully support testability. To help illustrate usage of the new API for the testing scenarios, a set of samples mocking the various Event Hubs client types and illustrating use of the model factory is needed.

Scope of Work

  • Implement a sample or set of samples demonstrating a basic approach for mocking the high level cli
waylew-lexis
waylew-lexis commented Sep 9, 2021

Not sure if this is a feature request or a bug, but when using this resource against a windows vm that is using a secured custom version of the mssql server image, the resource will time out on the apply. The custom image we are using does work on the vm without using this resource, which makes me believe this an issue with the resource and not the image.

mrnonz
mrnonz commented Feb 15, 2019

Hi, I read example command here https://docs.microsoft.com/en-us/cli/azure/container?view=azure-cli-latest#examples

and I found wrong command on "Create a container in a container group that runs Windows, with 2 cores and 3.5Gb of memory." Section.

Here your command
az container create -g MyResourceGroup --name myapp --image myimage:latest --ip-address public --ports 8081 --protocol UDP

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brunocous
brunocous commented Sep 2, 2020

I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?

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