AZ-104 Exam EP 50: Log Analytics

Introduction

This tutorial provides a comprehensive overview of Log Analytics as part of the AZ-104 Azure Administrator exam preparation. Log Analytics is a vital tool in Azure for monitoring and analyzing data from various resources. This guide will help you understand its features, how to connect data sources, and how to query logs effectively.

Step 1: Understand Log Analytics

• Log Analytics is a service within Azure Monitor that collects and analyzes log data.
• It allows you to gain insights into the performance and health of your applications and infrastructure.
• Key benefits include:
  • Centralized log management
  • Efficient querying capabilities
  • Visualizations and dashboards for better insights

Step 2: Connect Data Sources

• Connecting data sources to Log Analytics is crucial for gathering relevant data.
• Follow these sub-steps to connect sources:
  1. Navigate to the Azure portal.
  2. Select your Log Analytics workspace.
  3. Click on "Connected Sources" in the menu.
  4. Choose the type of data source you want to connect (e.g., virtual machines, Azure resources).
  5. Follow the prompts to complete the connection setup.

Step 3: Configure Data Sources

• Once your data sources are connected, configure them to ensure the right data is collected.
• Steps to configure data sources include:
  1. Go to the “Data Sources” section within your Log Analytics workspace.
  2. Select the specific data source you want to configure.
  3. Adjust settings such as data retention policies and logs to collect.

Step 4: Query Log Analytics

• Querying log data is a powerful feature of Log Analytics.
• Use the Kusto Query Language (KQL) to write queries that analyze your data.
• Basic querying steps:
  1. Go to the "Logs" section in your Log Analytics workspace.
  2. Use sample queries or write your own using KQL.
  3. Execute the query to retrieve results.

Step 5: Learn Query Language Syntax

• Familiarize yourself with KQL syntax to maximize your querying capabilities.
• Key components of KQL include:
  • Tables: Represent your data.
  • Operators: Used to filter and manipulate data (e.g., where, summarize).
  • Functions: Perform calculations and transformations on data.
• Example of a simple KQL query:

  AzureActivity
  | where ActivityStatus == "Succeeded"
  | summarize Count = count() by ResourceGroup
  

Conclusion

Log Analytics is a powerful tool for Azure administrators looking to monitor and analyze their resources effectively. By understanding how to connect data sources, configure settings, and write queries using KQL, you can leverage this tool to gain valuable insights into your Azure environment. As a next step, practice querying log data and explore creating dashboards to visualize your findings for improved decision-making.