You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: articles/active-directory/devices/plan-device-deployment.md
+4-2Lines changed: 4 additions & 2 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -6,7 +6,7 @@ services: active-directory
6
6
ms.service: active-directory
7
7
ms.subservice: devices
8
8
ms.topic: how-to
9
-
ms.date: 02/15/2022
9
+
ms.date: 09/30/2022
10
10
11
11
ms.author: gasinh
12
12
author: gargi-sinha
@@ -55,7 +55,7 @@ Consider your organizational needs while you determine the strategy for this dep
55
55
56
56
### Engage the right stakeholders
57
57
58
-
When technology projects fail, they typically do because of mismatched expectations on impact, outcomes, and responsibilities. To avoid these pitfalls, [ensure that you're engaging the right stakeholders](../fundamentals/active-directory-deployment-plans.md) and that stakeholder roles in the project are well understood.
58
+
When technology projects fail, they typically do because of mismatched expectations on impact, outcomes, and responsibilities. To avoid these pitfalls, [ensure that you're engaging the right stakeholders,](../fundamentals/active-directory-deployment-plans.md) and that stakeholder roles in the project are well understood.
59
59
60
60
For this plan, add the following stakeholders to your list:
61
61
@@ -103,6 +103,7 @@ iOS and Android devices may only be Azure AD registered. The following table pre
103
103
|**Client operating systems**||||
104
104
| Windows 11 or Windows 10 devices ||||
105
105
| Windows down-level devices (Windows 8.1 or Windows 7) ||||
106
+
| Linux Desktop - Ubuntu 20.04/22.04 ||||
106
107
|**Sign in options**||||
107
108
| End-user local credentials ||||
108
109
| Password ||||
@@ -135,6 +136,7 @@ BYOD and corporate owned mobile device are registered by users installing the Co
Copy file name to clipboardExpand all lines: articles/aks/cluster-autoscaler.md
+6-14Lines changed: 6 additions & 14 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -3,7 +3,7 @@ title: Use the cluster autoscaler in Azure Kubernetes Service (AKS)
3
3
description: Learn how to use the cluster autoscaler to automatically scale your cluster to meet application demands in an Azure Kubernetes Service (AKS) cluster.
4
4
services: container-service
5
5
ms.topic: article
6
-
ms.date: 07/18/2019
6
+
ms.date: 10/03/2022
7
7
8
8
---
9
9
@@ -225,7 +225,7 @@ To configure logs to be pushed from the cluster autoscaler into Log Analytics, f
225
225
1. Select the "Logs" section on your cluster via the Azure portal.
226
226
1. Input the following example query into Log Analytics:
227
227
228
-
```
228
+
```kusto
229
229
AzureDiagnostics
230
230
| where Category == "cluster-autoscaler"
231
231
```
@@ -236,7 +236,7 @@ You should see logs similar to the following example as long as there are logs t
236
236
237
237
The cluster autoscaler will also write out health status to a `configmap` named `cluster-autoscaler-status`. To retrieve these logs, execute the following `kubectl` command. A health status will be reported for each node pool configured with the cluster autoscaler.
238
238
239
-
```
239
+
```bash
240
240
kubectl get configmap -n kube-system cluster-autoscaler-status -o yaml
241
241
```
242
242
@@ -281,31 +281,23 @@ Kubernetes supports [horizontal pod autoscaling][kubernetes-hpa] to adjust the n
281
281
282
282
This article showed you how to automatically scale the number of AKS nodes. You can also use the horizontal pod autoscaler to automatically adjust the number of pods that run your application. For steps on using the horizontal pod autoscaler, see [Scale applications in AKS][aks-scale-apps].
283
283
284
+
To further help improve cluster resource utilization and free up CPU and memory for other pods, see [Vertical Pod Autoscaler][vertical-pod-autoscaler].
Copy file name to clipboardExpand all lines: articles/api-management/self-hosted-gateway-settings-reference.md
+3Lines changed: 3 additions & 0 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -23,6 +23,9 @@ This article provides a reference for required and optional settings that are us
23
23
|----|------|----------|-------------------|
24
24
| config.service.endpoint | Configuration endpoint in Azure API Management for the self-hosted gateway. Find this value in the Azure portal under **Gateways** > **Deployment**. | Yes | N/A |
25
25
| config.service.auth | Access token (authentication key) of the self-hosted gateway. Find this value in the Azure portal under **Gateways** > **Deployment**. | Yes | N/A |
26
+
| neighborhood.host | DNS name used to resolve all instances of a self-hosted gateway deployment for cross-instance synchronization. In Kubernetes, this can be achieved by using a headless Service. | No | N/A |
27
+
| neighborhood.heartbeat.port | UDP port used for instances of a self-hosted gateway deployment to send heartbeats to other instances. | No | 4291 |
28
+
| policy.rate-limit.sync.port | UDP port used for self-hosted gateway instances to synchronize rate limiting across multiple instances. | No | 4290 |
Copy file name to clipboardExpand all lines: articles/azure-monitor/alerts/itsmc-definition.md
+1-1Lines changed: 1 addition & 1 deletion
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -79,7 +79,7 @@ Action groups provide a modular and reusable way to trigger actions for your Azu
79
79
80
80
### Define a template
81
81
82
-
Certain work item types can use templates that you define in ServiceNow. When you use templates, you can define fields that will be automatically populated by using constant values defined in ServiceNow (not values from the payload). The templates are synced with Azure. You can define which template you want to use as a part of the definition of an action group. For information about how to create templates, see the [ServiceNow documentation](https://www.servicenow.com/community/now-platform-articles/servicenow-versions/ta-p/2312014).
82
+
Certain work item types can use templates that you define in ServiceNow. When you use templates, you can define fields that will be automatically populated by using constant values defined in ServiceNow (not values from the payload). The templates are synced with Azure. You can define which template you want to use as a part of the definition of an action group. For information about how to create templates, see the [ServiceNow documentation](https://docs.servicenow.com/en-US/bundle/tokyo-platform-administration/page/administer/form-administration/task/t_CreateATemplateUsingTheTmplForm.html).
Copy file name to clipboardExpand all lines: articles/azure-monitor/app/sampling.md
+21-21Lines changed: 21 additions & 21 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -11,7 +11,7 @@ ms.reviewer: mmcc
11
11
12
12
Sampling is a feature in [Azure Application Insights](./app-insights-overview.md). It's the recommended way to reduce telemetry traffic, data costs, and storage costs, while preserving a statistically correct analysis of application data. Sampling also helps you avoid Application Insights throttling your telemetry. The sampling filter selects items that are related, so that you can navigate between items when you're doing diagnostic investigations.
13
13
14
-
When metric counts are presented in the portal, they're re-normalized to take into account sampling. Doing so minimizes any effect on the statistics.
14
+
When metric counts are presented in the portal, they're renormalized to take into account sampling. Doing so minimizes any effect on the statistics.
15
15
16
16
## Brief summary
17
17
@@ -39,6 +39,26 @@ The following table summarizes the sampling types available for each SDK and typ
39
39
> [!NOTE]
40
40
> The information on most of this page applies to the current versions of the Application Insights SDKs. For information on older versions of the SDKs, [see the section below](#older-sdk-versions).
41
41
42
+
## When to use sampling
43
+
44
+
In general, for most small and medium size applications you don't need sampling. The most useful diagnostic information and most accurate statistics are obtained by collecting data on all your user activities.
45
+
46
+
The main advantages of sampling are:
47
+
48
+
* Application Insights service drops ("throttles") data points when your app sends a very high rate of telemetry in a short time interval. Sampling reduces the likelihood that your application will see throttling occur.
49
+
* To keep within the [quota](../logs/daily-cap.md) of data points for your pricing tier.
50
+
* To reduce network traffic from the collection of telemetry.
51
+
52
+
## How sampling works
53
+
54
+
The sampling algorithm decides which telemetry items to drop, and which ones to keep. This is true whether sampling is done by the SDK or in the Application Insights service. The sampling decision is based on several rules that aim to preserve all interrelated data points intact, maintaining a diagnostic experience in Application Insights that is actionable and reliable even with a reduced data set. For example, if your app has a failed request included in a sample, the additional telemetry items (such as exception and traces logged for this request) will be retained. Sampling either keeps or drops them all together. As a result, when you look at the request details in Application Insights, you can always see the request along with its associated telemetry items.
55
+
56
+
The sampling decision is based on the operation ID of the request, which means that all telemetry items belonging to a particular operation is either preserved or dropped. For the telemetry items that do not have an operation ID set (such as telemetry items reported from asynchronous threads with no HTTP context) sampling simply captures a percentage of telemetry items of each type.
57
+
58
+
When presenting telemetry back to you, the Application Insights service adjusts the metrics by the same sampling percentage that was used at the time of collection, to compensate for the missing data points. Hence, when looking at the telemetry in Application Insights, the users are seeing statistically correct approximations that are very close to the real numbers.
59
+
60
+
The accuracy of the approximation largely depends on the configured sampling percentage. Also, the accuracy increases for applications that handle a large volume of generally similar requests from lots of users. On the other hand, for applications that don't work with a significant load, sampling is not needed as these applications can usually send all their telemetry while staying within the quota, without causing data loss from throttling.
61
+
42
62
## Types of sampling
43
63
44
64
There are three different sampling methods:
@@ -407,16 +427,6 @@ Ingestion sampling doesn't operate while adaptive or fixed-rate sampling is in o
407
427
> [!WARNING]
408
428
> The value shown on the portal tile indicates the value that you set for ingestion sampling. It doesn't represent the actual sampling rate if any sort of SDK sampling (adaptive or fixed-rate sampling) is in operation.
409
429
410
-
## When to use sampling
411
-
412
-
In general, for most small and medium size applications you don't need sampling. The most useful diagnostic information and most accurate statistics are obtained by collecting data on all your user activities.
413
-
414
-
The main advantages of sampling are:
415
-
416
-
* Application Insights service drops ("throttles") data points when your app sends a very high rate of telemetry in a short time interval. Sampling reduces the likelihood that your application will see throttling occur.
417
-
* To keep within the [quota](../logs/daily-cap.md) of data points for your pricing tier.
418
-
* To reduce network traffic from the collection of telemetry.
419
-
420
430
### Which type of sampling should I use?
421
431
422
432
**Use ingestion sampling if:**
@@ -449,16 +459,6 @@ If you see that `RetainedPercentage` for any type is less than 100, then that ty
449
459
> [!IMPORTANT]
450
460
> Application Insights does not sample session, metrics (including custom metrics), or performance counter telemetry types in any of the sampling techniques. These types are always excluded from sampling as a reduction in precision can be highly undesirable for these telemetry types.
451
461
452
-
## How sampling works
453
-
454
-
The sampling algorithm decides which telemetry items to drop, and which ones to keep. This is true whether sampling is done by the SDK or in the Application Insights service. The sampling decision is based on several rules that aim to preserve all interrelated data points intact, maintaining a diagnostic experience in Application Insights that is actionable and reliable even with a reduced data set. For example, if your app has a failed request included in a sample, the additional telemetry items (such as exception and traces logged for this request) will be retained. Sampling either keeps or drops them all together. As a result, when you look at the request details in Application Insights, you can always see the request along with its associated telemetry items.
455
-
456
-
The sampling decision is based on the operation ID of the request, which means that all telemetry items belonging to a particular operation is either preserved or dropped. For the telemetry items that do not have an operation ID set (such as telemetry items reported from asynchronous threads with no HTTP context) sampling simply captures a percentage of telemetry items of each type.
457
-
458
-
When presenting telemetry back to you, the Application Insights service adjusts the metrics by the same sampling percentage that was used at the time of collection, to compensate for the missing data points. Hence, when looking at the telemetry in Application Insights, the users are seeing statistically correct approximations that are very close to the real numbers.
459
-
460
-
The accuracy of the approximation largely depends on the configured sampling percentage. Also, the accuracy increases for applications that handle a large volume of generally similar requests from lots of users. On the other hand, for applications that don't work with a significant load, sampling is not needed as these applications can usually send all their telemetry while staying within the quota, without causing data loss from throttling.
461
-
462
462
## Log query accuracy and high sample rates
463
463
464
464
As the application is scaled up, it may be processing dozens, hundreds, or thousands of work items per second. Logging an event for each of them is not resource nor cost effective. Application Insights uses sampling to adapt to growing telemetry volume in a flexible manner and to control resource usage and cost.
0 commit comments