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articles/azure-monitor/best-practices-logs.md

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## Reliability
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[Reliability](/azure/well-architected/resiliency/overview) refers to the ability of a system to recover from failures and continue to function. Instead of trying to prevent failures altogether in the cloud, the goal is to minimize the effects of a single failing component. Use the following information to minimize failure of your Log Analytics workspaces and to protect the data they collect.
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[Reliability](/azure/well-architected/resiliency/overview) refers to the ability of a system to recover from failures and continue to function. The goal is to minimize the effects of a single failing component. Use the following information to minimize failure of your Log Analytics workspaces and to protect the data they collect.
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This video provides an overview of reliability and resilience options available for Log Analytics workspaces:
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> [!VIDEO https://www.youtube.com/embed/CYspm1Yevx8?cc_load_policy=1&cc_lang_pref=auto]
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[!INCLUDE [waf-logs-reliability](includes/waf-logs-reliability.md)]
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articles/azure-monitor/logs/create-custom-table-auxiliary.md

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This article explains how to create a custom table with the Auxiliary plan in your Log Analytics workspace and set up a data collection rule that sends data to this table.
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Here's a video that explains some of the uses and benefits of the Auxiliary table plan:
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> [!VIDEO https://www.youtube.com/embed/GbD2Q3K_6Vo?cc_load_policy=1&cc_lang_pref=auto]
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> [!IMPORTANT]
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> See [public preview limitations](#public-preview-limitations) for supported regions and limitations related to Auxiliary tables and data collection rules.
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articles/azure-monitor/logs/data-platform-logs.md

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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.
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This video provides an overview of how table plans enable multi-tier logging in Azure Monitor Logs:
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> [!VIDEO https://www.youtube.com/embed/sn5-c8wYJcw?cc_load_policy=1&cc_lang_pref=auto]
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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](../logs/data-retention-configure.md). For information about how to select or modify a table plan, see [Select a table plan](logs-table-plans.md).
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:::image type="content" source="media/data-platform-logs/azure-monitor-logs-data-plans.png" lightbox="media/data-platform-logs/azure-monitor-logs-data-plans.png" alt-text="Diagram that presents an overview of the capabilities provided by the Analytics, Basic, and Auxiliary table plans.":::

articles/azure-monitor/logs/search-jobs.md

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Search jobs are asynchronous queries that fetch records into a new search table within your workspace for further analytics. The search job uses parallel processing and can run for hours across large datasets. This article describes how to create a search job and how to query its resulting data.
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This video explains when and how to use search jobs:
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> [!VIDEO https://www.youtube.com/embed/5iShgXRu1sU?cc_load_policy=1&cc_lang_pref=auto]
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## Permissions required
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| Action | Permissions required |

articles/azure-monitor/logs/summary-rules.md

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This article describes how summary rules work and how to define and view summary rules, and provides some examples of the use and benefits of summary rules.
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Here's a video that provides an overview of some of the benefits of summary rules:
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> [!VIDEO https://www.youtube.com/embed/uuZlOps42LE?cc_load_policy=1&cc_lang_pref=auto]
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## How summary rules work
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Summary rules perform batch processing directly in your Log Analytics workspace. The summary rule aggregates chunks of data, defined by bin size, based on a KQL query, and reingests the summarized results into a custom table with an [Analytics log plan](logs-table-plans.md) in your Log Analytics workspace.

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