This is a reminder for me or a task if anyone wants :P

Basically, The last two questions aren't really regex's questions.

To do:

• Move said questions to correct place.
• Add new regex questions (Python related!)?
• Maybe add a new ## Regex section, as it is a valuable skill

Right now, the validation error message is in the Example Usage box, which is what SSDT does

There's support for validation for input boxes, so it would be nicer for the error message to show up with the associated input box like this:
![image](https://user-images.githubusercontent

The https://github.com/nccgroup/ScoutSuite/blob/master/ScoutSuite/providers/gcp/rules/findings/iam-lack-of-service-account-key-rotation.json finding should only flag USER_MANAGED keys (https://cloud.google.com/iam/docs/reference/rest/v1/projects.serviceAccounts.keys), as SYSTEM_MANAGED keys are "managed and rotated by Google"

Describe the bug
CKV_GCP_14 requires a backup configuration, but it does not take into consideration read replicas.
A read replica cannot have backup enabled in GCP.

To Reproduce
Steps to reproduce the behavior:

1. Create a google_sql_database_instance with master_instance_name and replica_configuration
2. Chekov will pop up error CKV_GCP_14

Expected behavior
Read replicas

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

Summary

The Event Hubs client library is instrumented using the .NET EventSource mechanism for logging. When instrumenting or diagnosing issues with applications that consume the library, it is often helpful to have access to the Event Hubs logs.

Though EventSource instrumentation is

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?