Category: Azure Monitoring

Azure Centralized Monitoring is designed to collect telemetry data from diverse sources, process and analyze it on a scalable platform, and provide actionable insights to manage workloads efficiently. The architecture is divided into three core layers: Data Sources The Data Sources layer is where telemetry… [ Read More ]

Azure Log Analytics is a powerful tool within Azure Monitor that helps you collect, analyze, and act on log data from various Azure resources. With Log Analytics, you can query logs, monitor metrics, detect issues, and even automate responses based on log data. It is… [ Read More ]

To provide you with a detailed demonstration on Azure Alerts, let's walk through the process step by step. This will cover the creation, configuration, and monitoring of various types of alerts in Azure Monitor, including Metric Alerts, Log Alerts, Activity Log Alerts, and Service Health… [ Read More ]

Kusto Query Language (KQL) is a powerful query language used in Azure for querying large volumes of data across different services, particularly in Azure Monitor, Log Analytics, Azure Sentinel, and Application Insights. KQL is designed to be efficient, flexible, and optimized for fast data exploration,… [ Read More ]

Azure offers a variety of built-in log queries that can be accessed via Azure Monitor and Log Analytics. These queries are predefined to help users quickly gain insights from their Azure resources and services. Built-in queries typically focus on common use cases such as monitoring… [ Read More ]

Kusto Query Language (KQL) is used to query data in Azure, particularly within Azure Monitor, Azure Log Analytics, and Azure Sentinel. Understanding the KQL query structure is key to efficiently retrieving and analyzing data. Below are the fundamental elements of KQL query structure: Basic Structure… [ Read More ]

Log Analytics queries in Azure are written using a query language called Kusto Query Language (KQL). The structure of Log Analytics queries typically involves the following components: Data Sources (Tables) Azure Log Analytics stores data in various tables based on the data type, such as… [ Read More ]

Querying Log Analytics data in Azure is done using Kusto Query Language (KQL), a powerful and flexible query language designed to analyze large volumes of structured, semi-structured, and unstructured data. Here’s how you can query Log Analytics data and best practices for doing so: Accessing… [ Read More ]

A Log Analytics workspace in Azure is a central repository for collecting, storing, and analyzing log and performance data from various sources across your Azure environment. It is an essential component of Azure Monitor and enables you to perform detailed log queries and visualizations. Here… [ Read More ]

When using Log Analytics in Azure, there are several factors and best practices to consider to ensure efficient, cost-effective, and secure usage. Below are key things to keep in mind: Data Collection and Sources Data Sources: Decide which data sources you need to collect logs… [ Read More ]