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Merge pull request #227760 from pritamso/Broken-link-fix-bwren
Broken link fix
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articles/azure-monitor/faq.yml

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| [Standard Metrics](app/standard-metrics.md) (accuracy currently affected by sampling) | :warning: | :warning: | :warning: | :white_check_mark: |
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| [Fixed-Rate Sampling](app/sampling.md) | :warning: | :warning: | :warning: | :white_check_mark: |
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| [Offline Storage & Automatic Retries](app/opentelemetry-enable.md#offline-storage-and-automatic-retries)| :warning: | :warning: | :warning: | :white_check_mark: |
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| [Exception Reporting](/app/asp-net-exceptions.md) | :warning: | :warning: | :warning: | :white_check_mark: |
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| [Exception Reporting](app/asp-net-exceptions.md) | :warning: | :warning: | :warning: | :white_check_mark: |
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| [Logs Collection](app/asp-net-trace-logs.md) | :x: | :x: | :x: | :white_check_mark: |
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| [Azure Active Directory (AAD) authentication](app/azure-ad-authentication.md) | :x: | :x: | :x: | :white_check_mark: |
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| [Auto-populate cloud role name/role instance on Azure](/app/correlation.md#role-names) | :x: | :x: | :x: | :white_check_mark: |
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| [Auto-populate cloud role name/role instance on Azure](app/correlation.md#role-names) | :x: | :x: | :x: | :white_check_mark: |
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| [Live Metrics](app/live-stream.md) | :x: | :x: | :x: | :white_check_mark: |
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| Autopopulation of User ID, Authenticated User ID, and User IP | :x: | :x: | :x: | :white_check_mark: |
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| Manually override/set Operation Name, User ID or Authenticated User ID | :x: | :x: | :x: | :white_check_mark: |

articles/azure-monitor/logs/query-optimization.md

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Query behaviors that can reduce parallelism include:
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- Use of serialization and window functions, such as the [serialize operator](/azure/kusto/query/serializeoperator), [next()](/azure/kusto/query/nextfunction), [prev()](/azure/kusto/query/prevfunction), and the [row](/azure/kusto/query/rowcumsumfunction) functions. Time series and user analytics functions can be used in some of these cases. Inefficient serialization might also happen if the following operators aren't used at the end of the query: [range](/azure/kusto/query/rangeoperator), [sort](/azure/kusto/query/sortoperator), [order](/azure/kusto/query/orderoperator), [top](/azure/kusto/query/topoperator), [top-hitters](/azure/kusto/query/tophittersoperator), and [getschema](/azure/kusto/query/getschemaoperator).
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- Use of serialization and window functions, such as the [serialize operator](/azure/kusto/query/serializeoperator), [next()](/azure/kusto/query/nextfunction), [prev()](/azure/kusto/query/prevfunction), and the [row](/azure/kusto/query/rowcumsumfunction) functions. Time series and user analytics functions can be used in some of these cases. Inefficient serialization might also happen if the following operators aren't used at the end of the query: [range](/azure/kusto/query/rangeoperator), [sort](/azure/data-explorer/kusto/query/sort-operator), [order](/azure/kusto/query/orderoperator), [top](/azure/kusto/query/topoperator), [top-hitters](/azure/kusto/query/tophittersoperator), and [getschema](/azure/kusto/query/getschemaoperator).
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- Use of the [dcount()](/azure/kusto/query/dcount-aggfunction) aggregation function forces the system to have a central copy of the distinct values. When the scale of data is high, consider using the `dcount` function optional parameters to reduce accuracy.
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- In many cases, the [join](/azure/kusto/query/joinoperator?pivots=azuremonitor) operator lowers overall parallelism. Examine `shuffle join` as an alternative when performance is problematic.
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- In resource-scope queries, the pre-execution Kubernetes role-based access control (RBAC) or Azure RBAC checks might linger in situations where there's a large number of Azure role assignments. This situation might lead to longer checks that would result in lower parallelism. For example, a query might be executed on a subscription where there are thousands of resources and each resource has many role assignments on the resource level, not on the subscription or resource group.

articles/azure-monitor/whats-new.md

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Application-Insights|[Application Insights for Azure VMs and Virtual Machine Scale Sets](app/azure-vm-vmss-apps.md)|Easily monitor your IIS-hosted .NET Framework and .NET Core applications running on Azure VMs and Virtual Machine Scale Sets using a new App Insights Extension.|
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Application-Insights|[Sampling in Application Insights](app/sampling.md)|We've added embedded links to assist with looking up type definitions. (Dependency, Event, Exception, PageView, Request, Trace)|
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Application-Insights|[Configuration options: Azure Monitor Application Insights for Java](app/java-standalone-config.md)|Instructions are now available on how to set the http proxy using an environment variable, which overrides the JSON configuration. We've also provided a sample to configure connection string at runtime.|
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Application-Insights|[Application Insights for Java 2.x](app/deprecated-java-2x.md)|The Java 2.x retirement notice is available at https://azure.microsoft.com/updates/application-insights-java-2x-retirement.|
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Application-Insights|[Application Insights for Java 2.x](app/deprecated-java-2x.md)|The Java 2.x retirement notice is available at https://azure.microsoft.com/updates/application-insights-java-2x-retirement .|
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Autoscale|[Diagnostic settings in Autoscale](autoscale/autoscale-diagnostics.md)|Updated and expanded content|
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Autoscale|[Overview of common autoscale patterns](autoscale/autoscale-common-scale-patterns.md)|Clarification of weekend profiles|
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Autoscale|[Autoscale with multiple profiles](autoscale/autoscale-multiprofile.md)|Added clarifications for profile end times|

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