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Copy file name to clipboardExpand all lines: articles/load-balancer/concepts.md
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ms.service: load-balancer
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ms.topic: conceptual
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ms.workload: infrastructure-services
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ms.date: 11/29/2021
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ms.date: 05/08/2023
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ms.author: mbender
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ms.custom: template-concept
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---
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Azure Load Balancer is Azure's most performant Load Balancer all while keeping latency ultra-low. To learn more about Azure Load Balancer, visit [Azure Load Balancer overview](load-balancer-overview.md) or Azure Load balancer [components](components.md).
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Azure Load Balancer leverages a tuple-based hashing as the load-balancing algorithm.
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Azure Load Balancer uses a tuple-based hashing as the load-balancing algorithm.
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## Load balancing algorithm
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By creating a load balancer rule, you can distribute inbound traffic flows from a load balancer's frontend to its backend pools. Azure Load Balancer uses a five-tuple hashing algorithm for the distribution of inbound flows (not bytes). Load balancer rewrites the headers of TCP/UDP headers flows when directing traffic to the backend pool instances (load balancer does not rewrite HTTP/HTTPS headers). When the load balancer's health probe indicates a healthy back-end endpoint, backend instances will be available to receive new traffic flows.
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By creating a load balancer rule, you can distribute inbound traffic flows from a load balancer's frontend to its backend pools. Azure Load Balancer uses a five-tuple hashing algorithm for the distribution of inbound flows (not bytes). Load balancer rewrites the headers of TCP/UDP headers flows when directing traffic to the backend pool instances (load balancer doesn't rewrite HTTP/HTTPS headers). When the load balancer's health probe indicates a healthy back-end endpoint, backend instances are available to receive new traffic flows.
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By default, Azure Load Balancer uses a five-tuple hash.
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The fivetuple includes:
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The five-tuple includes:
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-**Source IP address**
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-**Source port**
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-**Destination IP address**
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-**Destination port**
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-**IP protocol number to map flows to available servers**
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You can also leverage session affinity [distribution mode](distribution-mode-concepts.md) which uses twotuple or threetuple based load balancing.
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You can also use session affinity [distribution mode](distribution-mode-concepts.md) which uses two-tuple or three-tuple based load balancing.
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Azure Load Balancer supports any TCP/UDP application scenario and doesn't close or originate flows. Load balancer also doesn't interact with the payload of any flow. Application payloads are transparent to the load balancer. Any UDP or TCP application can be supported.
Copy file name to clipboardExpand all lines: articles/load-balancer/load-balancer-insights.md
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ms.service: load-balancer
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ms.topic: conceptual
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ms.workload: infrastructure-services
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ms.date: 10/27/2020
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ms.date: 05/08/2023
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ms.author: mbender
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ms.custom: template-concept, engagement-fy23
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You can navigate through the available tabs each of which contain visuals relevant to a specific aspect of your Load Balancer. Explicit guidance for each is available in the dashboard at the bottom of each tab.
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The dashboard tabs currently available are:
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* Overview
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* Frontend and Backend Availability
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* Data Throughput
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* Metric Definitions
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### Overview tab
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The Overview tab contains a searchable grid with the overall Data Path Availability and Health Probe Status for each of the Frontend IPs attached to your Load Balancer. These metrics indicate whether the Frontend IP is responsive and the compute instances in your Backend Pool are individually responsive to inbound connections.
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You can also view the overall data throughput for each Frontend IP on this page to get a sense of whether you're producing and receive expected traffic levels. The guidance at the bottom of the page directs you to the appropriate tab should you see any irregular values.
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### Frontend and Backend Availability tab
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The Frontend and Backend Availability tabs show the Data Path Throughput and Health Probe Status metrics presented in a few useful views. The first graph shows the aggregate value so you can determine whether there's an issue. The rest of the graphs show these metrics split by various dimensions so that you can troubleshoot and identify the sources of any inbound availability issues.
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A workflow for viewing these graphs is provided at the bottom of the page with common causes for various symptoms.
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### Data Throughput tab
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The Data Throughput tab allows you to review your inbound and outbound throughput to identify if your traffic patterns are as expected. It shows the inbound and outbound data throughput split by Frontend IP and Frontend Port so that you can identify if how the services you have running are performing individually.
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### Flow Distribution
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The Flow Distribution Tab helps you visualize and manage the number of flows your backend instances are receiving and producing. It shows the Flow Creation Rate and Flow Count for inbound and outbound traffic as well as the Network Traffic each VM and Virtual Machine Scale Set instance is receiving.
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These views can give you feedback on whether your Load Balancer configuration or traffic patterns are leading to imbalanced traffic. For example, if you have session affinity configured and a single client is making a disproportionate number of requests. It will also let you know if you're approaching the [per VM flow limit](../virtual-network/virtual-machine-network-throughput.md#flow-limits-and-active-connections-recommendations) for your machine size.
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### Connection Monitors
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The Connection Monitors tab shows you the round-trip latency on a global map for all of the [Connection Monitors](../network-watcher/connection-monitor.md) you've configured. These visuals provide useful information for services with strict latency requirements. To meet your requirements, you may need to add other regional deployments or move to a [cross-regional load balancing](./cross-region-overview.md) model
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### Metric Definitions
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The Metric Definitions tab contains all the information shown in the [Multi-dimensional Metrics article](./load-balancer-standard-diagnostics.md#multi-dimensional-metrics).
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## Next steps
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* Review the dashboard and provide feedback using the below link if there's anything that can be improved
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*[Review the metrics documentation to ensure you understand how each metric is calculated](./load-balancer-standard-diagnostics.md#multi-dimensional-metrics)
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*[Create Connection Monitors for your Load Balancer](../network-watcher/connection-monitor.md)
# Get Load Balancer usage metrics using the REST API
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# Get Load Balancer usage metrics using the Azure REST API
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Collect the number of bytes processed by a [Standard Load Balancer](./load-balancer-overview.md) for an interval of time using the [Azure REST API](/rest/api/azure/).
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Complete reference documentation and additional samples for the REST API are available in the [Azure Monitor REST reference](/rest/api/monitor).
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Complete reference documentation and more samples for the REST API are available in the [Azure Monitor REST reference](/rest/api/monitor).
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Using data path availability, you can fire alerts whenever a specific load-balancing rule becomes unavailable. You can configure this alert by setting an alert condition for the data path availability and splitting by all current values and future values for both frontend port and frontend IP address. Setting the alert logic to be less than or equal to 0 will cause this alert to be fired whenever any load-balancing rule becomes unresponsive. Set the aggregation granularity and frequency of evaluation according to your desired evaluation.
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With health probe status, you can alert when a given backend instance fails to respond to the health probe for a significant amount of time. Set up your alert condition to use the health probe status metric and split by backend IP address and backend port. This will ensure that you can alert separately for each individual backend instance’s ability to serve traffic on a specific port. Use the **Average** aggregation type and set the threshold value according to how frequently your backend instance is probed and your considered healthy threshold.
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With health probe status, you can alert when a given backend instance fails to respond to the health probe for a significant amount of time. Set up your alert condition to use the health probe status metric and split by backend IP address and backend port. This ensures that you can alert separately for each individual backend instance’s ability to serve traffic on a specific port. Use the **Average** aggregation type and set the threshold value according to how frequently your backend instance is probed and your considered healthy threshold.
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You can also alert on a backend pool level by not splitting by any dimensions and using the **Average** aggregation type. This allows you to set up alert rules such as alert when 50% of my backend pool members are unhealthy.
| Data path availability | Public and internal load balancer | Standard Load Balancer continuously exercises the data path from within a region to the load balancer front end, all the way to the SDN stack that supports your VM. As long as healthy instances remain, the measurement follows the same path as your application's load-balanced traffic. The data path that your customers use is also validated. The measurement is invisible to your application and does not interfere with other operations. | Average |
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| Data path availability | Public and internal load balancer | Standard Load Balancer continuously exercises the data path from within a region to the load balancer front end, all the way to the SDN stack that supports your VM. As long as healthy instances remain, the measurement follows the same path as your application's load-balanced traffic. The data path that your customer's use is also validated. The measurement is invisible to your application and doesn't interfere with other operations. | Average |
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| Health probe status | Public and internal load balancer | Standard Load Balancer uses a distributed health-probing service that monitors your application endpoint's health according to your configuration settings. This metric provides an aggregate or per-endpoint filtered view of each instance endpoint in the load balancer pool. You can see how Load Balancer views the health of your application, as indicated by your health probe configuration. | Average |
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| SYN (synchronize) count | Public and internal load balancer | Standard Load Balancer uses a distributed health-probing service that monitors your application endpoint's health according to your configuration settings. This metric provides an aggregate or per-endpoint filtered view of each instance endpoint in the load balancer pool. You can see how Load Balancer views the health of your application, as indicated by your health probe configuration. | Average |
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| SNAT connection count | Public load balancer | Standard Load Balancer reports the number of outbound flows that are masqueraded to the Public IP address front end. Source network address translation (SNAT) ports are an exhaustible resource. This metric can give an indication of how heavily your application is relying on SNAT for outbound originated flows. Counters for successful and failed outbound SNAT flows are reported and can be used to troubleshoot and understand the health of your outbound flows. | Sum |
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| Allocated SNAT ports | Public load balancer | Standard Load Balancer reports the number of SNAT ports allocated per backend instance. | Average |
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| Used SNAT ports | Public load balancer | Standard Load Balancer reports the number of SNAT ports that are utilized per backend instance. | Average |
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| Byte count | Public and internal load balancer | Standard Load Balancer reports the data processed per front end. You may notice that the bytes are not distributed equally across the backend instances. This is expected as Azure's Load Balancer algorithm is based on flows. | Sum |
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| Byte count | Public and internal load balancer | Standard Load Balancer reports the data processed per front end. You may notice that the bytes aren't distributed equally across the backend instances. This is expected as Azure's Load Balancer algorithm is based on flows. | Sum |
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| Packet count | Public and internal load balancer | Standard Load Balancer reports the packets processed per front end. | Sum |
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For more information, see a list of [all platform metrics supported in Azure Monitor for load balancer](../azure-monitor/essentials/metrics-supported.md#microsoftnetworkloadbalancers).
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For more information on what metric dimensions are, see [Multi-dimensional metrics](../azure-monitor/essentials/data-platform-metrics.md#multi-dimensional-metrics).
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Load Balancer has the following dimensions associated with its metrics.
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Load Balancer has the following **dimensions** associated with its metrics.
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| Dimension Name | Description |
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|**Dimension Name**|**Description**|
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| -------------- | ----------- |
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| Frontend IP | The frontend IP address of the relevant load balancing rule(s) |
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| Frontend Port | The frontend port of the relevant load balancing rule(s) |
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Diagnostics tables are currently unsupported by Azure Load Balancer.
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## Activity log
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The following table lists the operations related to Load Balancer that may be created in the Activity log.
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The following table lists the **operations** related to Load Balancer that may be created in the Activity log.
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| Operation | Description |
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|**Operation**|**Description**|
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| --- | --- |
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| Microsoft.Network/loadBalancers/read | Gets a load balancer definition |
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| Microsoft.Network/loadBalancers/write | Creates a load balancer or updates an existing load balancer |
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If an NSG blocks health probe requests from the AZURE_LOADBALANCER default tag, your VM health probe fails and the VM is marked unavailable. The load balancer stops sending new flows to that VM.
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## Scenarios with outbound rules
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### Outbound rules scenarios
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## Outbound rules scenarios
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* Configure outbound connections to a specific set of public IPs or prefix.
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