How to Install and Uninstall python311-azure-monitor-ingestion Package on openSuSE Tumbleweed
Last updated: November 08,2024
1. Install "python311-azure-monitor-ingestion" package
This is a short guide on how to install python311-azure-monitor-ingestion on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python311-azure-monitor-ingestion
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2. Uninstall "python311-azure-monitor-ingestion" package
This guide let you learn how to uninstall python311-azure-monitor-ingestion on openSuSE Tumbleweed:
$
sudo zypper remove
python311-azure-monitor-ingestion
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3. Information about the python311-azure-monitor-ingestion package on openSuSE Tumbleweed
Information for package python311-azure-monitor-ingestion:
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Repository : openSUSE-Tumbleweed-Oss
Name : python311-azure-monitor-ingestion
Version : 1.0.3-1.4
Arch : noarch
Vendor : openSUSE
Installed Size : 304.0 KiB
Installed : No
Status : not installed
Source package : python-azure-monitor-ingestion-1.0.3-1.4.src
Upstream URL : https://github.com/Azure/azure-sdk-for-python
Summary : Microsoft Azure Monitor Ingestion Client Library for Python
Description :
The Azure Monitor Ingestion client library is used to send custom logs to Azure Monitor.
This library allows you to send data from virtually any source to supported built-in tables
or to custom tables that you create in Log Analytics workspace. You can even extend the schema
of built-in tables with custom columns.
----------------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python311-azure-monitor-ingestion
Version : 1.0.3-1.4
Arch : noarch
Vendor : openSUSE
Installed Size : 304.0 KiB
Installed : No
Status : not installed
Source package : python-azure-monitor-ingestion-1.0.3-1.4.src
Upstream URL : https://github.com/Azure/azure-sdk-for-python
Summary : Microsoft Azure Monitor Ingestion Client Library for Python
Description :
The Azure Monitor Ingestion client library is used to send custom logs to Azure Monitor.
This library allows you to send data from virtually any source to supported built-in tables
or to custom tables that you create in Log Analytics workspace. You can even extend the schema
of built-in tables with custom columns.