# Concept

SQLWATCH can send data to Azure Log Analytics which can be used centralised storage for long term storage and data analysis.&#x20;

Each SQLWATCH instance can send data independently and does not require any central repository or central servers. Each server will require access to the Azure Log API over the internet.

![](https://560149426-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LamHUpIpVXoBUUDZZpO%2F-MB5Bn-GktLQX0mGDHrh%2F-MB5C5QzchnCDv0oQAzQ%2Fimage.png?alt=media\&token=4da03fd6-c231-41e4-9e3c-2d9a59e8d720)

{% hint style="info" %}
Although it is possible to set it up in a way that the central server is sending the data rather than individual instance, such configuration is out of the scope of this document.&#x20;
{% endhint %}

The main benefit is that we can offload the entire reporting to Azure where we can keep months worth of data and do all kinds of data analysis using Azure Workbooks.&#x20;

{% hint style="info" %}
Power BI also has the functionality to interface with the Azure Log Analytics. Although the default dashboard that comes with SQLWATCH connects to a SQL Server, it can be modified to connect to Azure Log Analytics.
{% endhint %}

{% hint style="success" %}
Alerts can also be set in Azure Log to monitor missing data and alert us when a server stopped sending data or when the thresholds are out of bounds.
{% endhint %}

## Screenshots

![](https://560149426-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LamHUpIpVXoBUUDZZpO%2F-MB51hRbHgu5lnjMZFZN%2F-MB5410aU9yT9z12OMaZ%2Fimage.png?alt=media\&token=9fb302a5-af08-4456-98e0-6c83e2dd2d04)
