Azure Monitor Logs overview

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Azure Monitor Logs is a centralized software as a service (SaaS) platform for collecting, analyzing, and acting on telemetry data generated by Azure and non-Azure resources and applications.

You can collect logs, manage log data and costs, and consume different types of data in one Log Analytics workspace, the primary Azure Monitor Logs resource. This means you never have to move data or manage other storage, and you can retain different data types for as long or as little as you need.

This article provides an overview of how Azure Monitor Logs works and explains how it addresses the needs and skills of different personas in an organization.

Note

Azure Monitor Logs is one half of the data platform that supports Azure Monitor. The other is Azure Monitor Metrics, which stores numeric data in a time-series database.

How Azure Monitor Logs works

Azure Monitor Logs provides you with the tools to:

  • Collect any data by using Azure Monitor data collection methods. Transform data based on your needs to optimize costs, remove personal data, and so on, and route data to tables in your Log Analytics workspace.
  • Manage and optimize log data and costs by configuring your Log Analytics workspace and log tables, including table schemas, table plans, data retention, data aggregation, who has access to which data, and log-related costs.
  • Retrieve data in near-real time by using Kusto Query language (KQL), or KQL-based tools and features that don't require KQL knowledge, such as Simple mode in the Log Analytics user interface, prebuilt curated monitoring experiences called Insights, and predefined queries.
  • Use data flexibly for a range of use cases, including data analysis, troubleshooting, alerting, dashboards and reports, custom applications, and other Azure or non-Azure services.

A diagram that shows how Azure Monitor and Azure Monitor Logs provide an end-to-end solution for collecting, managing, retrieving, and working with log data.

Data collection, routing, and transformation

Azure Monitor's data collection capabilities let you collect data from all of your applications and resources running in Azure, other clouds, and on-premises. A powerful ingestion pipeline enables filtering, transforming, and routing data to destination tables in your Log Analytics workspace to optimize costs, analytics capabilities, and query performance.

A diagram that shows data being collected from data sources and transformed and sent to tables in a Log Analytics workspace.

For more information on data collection and transformation, see Azure Monitor data sources and data collection methods and Data collection transformations in Azure Monitor.

Log Analytics workspace

A Log Analytics workspace is a data store that holds tables into which you collect data.

To address the data storage and consumption needs of various personas who use a Log Analytics workspace, you can:

A screenshot of a Log Analytics workspace in the Azure portal.

You can also configure network isolation, replicate your workspace across regions, and design a workspace architecture based on your business needs.

Table plans

You can use one Log Analytics workspace to store any type of log required for any purpose. For example:

  • High-volume, verbose data that requires cheap long-term storage for audit and compliance
  • App and resource data for troubleshooting by developers
  • Key event and performance data for scaling and alerting to ensure ongoing operational excellence and security
  • Aggregated long-term data trends for advanced analytics and machine learning

Table plans let you manage data costs based on how often you use the data in a table and the type of analysis you need the data for.

The diagram and table below compare the Analytics, Basic, and Auxiliary table plans. For information about interactive and long-term retention, see Manage data retention in a Log Analytics workspace. For information about how to select or modify a table plan, see Select a table plan.

Diagram that presents an overview of the capabilities provided by the Analytics, Basic, and Auxiliary table plans.

Features Analytics Basic Auxiliary (Preview)
Best for High-value data used for continuous monitoring, real-time detection, and performance analytics. Medium-touch data needed for troubleshooting and incident response. Low-touch data, such as verbose logs, and data required for auditing and compliance.
Supported table types All table types Azure tables that support Basic logs and DCR-based custom tables DCR-based custom tables
Ingestion cost Standard Reduced Minimal
Query price included ✅ ❌ ❌
Optimized query performance ✅ ✅ ❌ Slower queries.
Good for auditing. Not optimized for real-time analysis.
Query capabilities Full query capabilities. Full Kusto Query Language (KQL) on a single table, which you can extend with data from an Analytics table using lookup. Full KQL on a single table, which you can extend with data from an Analytics table using lookup.
Alerts ✅ ❌ ❌
Insights ✅ ❌ ❌
Dashboards ✅ ✅ Cost per query for dashboard refreshes not included. Possible, but slow to refresh, cost per query for dashboard refreshes not included.
Data export ✅ ✅ ❌
Search jobs ✅ ✅ ✅
Restore ✅ ✅ ❌
Interactive retention 30 days (90 days for Microsoft Sentinel and Application Insights).
Can be extended to up to two years at a prorated monthly long-term retention charge.		 30 days 30 days
Total retention Up to 12 years Up to 12 years Up to 12 years*
*Public preview limitation: Auxiliary plan total retention is currently fixed at 365 days.

Note

The Auxiliary table plan is currently not available in Microsoft Azure operated by 21Vianet.

Kusto Query Language (KQL) and Log Analytics

You retrieve data from a Log Analytics workspace using a Kusto Query Language (KQL) query, which is a read-only request to process data and return results. KQL is a powerful tool that can analyze millions of records quickly. Use KQL to explore your logs, transform and aggregate data, discover patterns, identify anomalies and outliers, and more.

Log Analytics is a tool in the Azure portal for running log queries and analyzing their results. A set of controls lets you explore and analyze the retrieved data using the most popular Azure Monitor Logs functionality in an intuitive, spreadsheet-like experience.

If you're familiar with KQL, you can use Log Analytics KQL mode to edit and create queries, which you can then use in Azure Monitor features such as alerts and workbooks, or share with other users.

For more information about Log Analytics, see Overview of Log Analytics in Azure Monitor.

Built-in insights and custom dashboards, workbooks, and reports

Many of Azure Monitor's ready-to-use, curated Insights experiences store data in Azure Monitor Logs, and present this data in an intuitive way so you can monitor the performance and availability of your cloud and hybrid applications and their supporting components.

A screenshot that shows the built-in Container Insights monitoring experience in Azure Monitor.

You can also create your own visualizations and reports using workbooks, dashboards, and Power BI.

Use cases

This table describes some of the ways that you can use the data you collect in Azure Monitor Logs to derive operational and business value.

Capability Description
Analyze Use Log Analytics in the Azure portal to write log queries and interactively analyze log data by using a powerful analysis engine.
Alert Configure a log search alert rule or metric alert for logs to send a notification or take automated action when a particular condition occurs.
Visualize Pin query results rendered as tables or charts to an Azure dashboard.
Create a workbook to combine with multiple sets of data in an interactive report.
Export the results of a query to Power BI to use different visualizations and share with people outside Azure.
Export the results of a query to Grafana to use its dashboarding and combine with other data sources.
Get insights Insights provide a customized monitoring experience for particular resources and services.
Retrieve Access log query results from:
Import Upload logs from a custom app via the REST API or client library for .NET, Go, Java, JavaScript, or Python.
Export Configure automated export of log data to an Azure Storage account or Azure Event Hubs.
Build a workflow to retrieve log data and copy it to an external location by using Azure Logic Apps.
Retain data for auditing and compliance Send data directly to a table with the extend retention of data in any table to keep data for auditing and compliance to up to 12 years.

Working with Microsoft Defender for Cloud

Microsoft Defender for Cloud perform Security monitoring in Azure.

These services store their data in Azure Monitor Logs so that it can be analyzed with other log data collected by Azure Monitor.

Learn more

Service More information
Microsoft Defender for Cloud

Next steps