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Copy file name to clipboardExpand all lines: articles/batch/batch-automatic-scaling.md
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Error:
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```
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## Get autoscale run history using pool autoscale events
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You can also check automatic scaling history by querying [PoolAutoScaleEvent](batch-pool-autoscale-event.md). This event is emitted by Batch Service to record each occurrence of autoscale formula evaluation and execution, which can be helpful to troubleshoot potential issues.
This C# example adjusts the pool size based on the number of tasks. This formula also takes into account the [MaxTasksPerComputeNode](/dotnet/api/microsoft.azure.batch.cloudpool.maxtaskspercomputenode) value that has been set for the pool. This approach is useful in situations where [parallel task execution](batch-parallel-node-tasks.md) has been enabled on your pool.
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This C# example adjusts the pool size based on the number of tasks. This formula also takes into account the [TaskSlotsPerNode](/dotnet/api/microsoft.azure.batch.cloudpool.taskslotspernode) value that has been set for the pool. This approach is useful in situations where [parallel task execution](batch-parallel-node-tasks.md) has been enabled on your pool.
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```csharp
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// Determine whether 70 percent of the samples have been recorded in the past
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},
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"taskFactory": {
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"type": "taskPerFile",
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"source": {
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"source": {
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"fileGroup": "ffmpeg-input"
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},
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"repeatTask": {
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The Batch CLI extension provides commands to upload files from client to a specified file group and download files from the specified file group to a client.
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```azurecli
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az batch file upload --local-path c:\source_videos\*.mp4
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az batch file upload --local-path c:\source_videos\*.mp4
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--file-group ffmpeg-input
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az batch file download --file-group ffmpeg-output --local-path
Copy file name to clipboardExpand all lines: articles/batch/batch-diagnostics.md
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---
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# Batch metrics, alerts, and logs for diagnostic evaluation and monitoring
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This article explains how to monitor a Batch account using features of [Azure Monitor](../azure-monitor/overview.md). Azure Monitor collects [metrics](../azure-monitor/platform/data-platform-metrics.md) and [diagnostic logs](../azure-monitor/platform/platform-logs-overview.md) for resources in your Batch account. Collect and consume this data in a variety of ways to monitor your Batch account and diagnose issues. You can also configure [metric alerts](../azure-monitor/platform/alerts-overview.md) so you receive notifications when a metric reaches a specified value.
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## Batch metrics
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Alerts that trigger on a single data point is not recommended, as metrics are subject to out-of-order delivery, data loss, and/or duplication. When creating your alerts, you can use thresholds to account for these inconsistencies.
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For example, you might want to configure a metric alert when your low priority core count falls to a certain level, so you can adjust the composition of your pools. For best results, set a period of 10 or more minutes, where alerts trigger if the average low priority core count falls below the threshold value for the entire period. This allows for more time for metrics to aggregate so that you get more accurate results.
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For example, you might want to configure a metric alert when your low priority core count falls to a certain level, so you can adjust the composition of your pools. For best results, set a period of 10 or more minutes, where alerts trigger if the average low priority core count falls below the threshold value for the entire period. This allows for more time for metrics to aggregate so that you get more accurate results.
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To configure a metric alert in the Azure portal:
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Alternately, you can:
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- Stream Batch diagnostic log events to an [Azure Event Hub](../event-hubs/event-hubs-about.md). Event Hubs can ingest millions of events per second, which you can then transform and store using any real-time analytics provider.
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- Stream Batch diagnostic log events to an [Azure Event Hub](../event-hubs/event-hubs-about.md). Event Hubs can ingest millions of events per second, which you can then transform and store using any real-time analytics provider.
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- Send diagnostic logs to [Azure Monitor logs](../azure-monitor/log-query/log-query-overview.md), where you can analyze them or export them for analysis in Power BI or Excel.
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> [!NOTE]
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> You may incur additional costs to store or process diagnostic log data with Azure services.
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> You may incur additional costs to store or process diagnostic log data with Azure services.
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### Enable collection of Batch diagnostic logs
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Copy file name to clipboardExpand all lines: articles/batch/batch-mpi.md
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## Requirements for multi-instance tasks
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Multi-instance tasks require a pool with **inter-node communication enabled**, and with **concurrent task execution disabled**. To disable concurrent task execution, set the [CloudPool.MaxTasksPerComputeNode](/dotnet/api/microsoft.azure.batch.cloudpool) property to 1.
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Multi-instance tasks require a pool with **inter-node communication enabled**, and with **concurrent task execution disabled**. To disable concurrent task execution, set the [CloudPool.TaskSlotsPerNode](/dotnet/api/microsoft.azure.batch.cloudpool) property to 1.
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> [!NOTE]
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> Batch [limits](batch-quota-limit.md#pool-size-limits) the size of a pool that has inter-node communication enabled.
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// Multi-instance tasks require inter-node communication, and those nodes
> If you try to run a multi-instance task in a pool with internode communication disabled, or with a *maxTasksPerNode* value greater than 1, the task is never scheduled--it remains indefinitely in the "active" state.
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> If you try to run a multi-instance task in a pool with internode communication disabled, or with a *taskSlotsPerNode* value greater than 1, the task is never scheduled--it remains indefinitely in the "active" state.
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### Use a StartTask to install MPI
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*[Sizes for virtual machines in Azure](../virtual-machines/windows/sizes.md?toc=%2fazure%2fvirtual-machines%2fwindows%2ftoc.json) (Windows)
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> [!NOTE]
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> To take advantage of RDMA on [Linux compute nodes](batch-linux-nodes.md), you must use **Intel MPI** on the nodes.
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> To take advantage of RDMA on [Linux compute nodes](batch-linux-nodes.md), you must use **Intel MPI** on the nodes.
Copy file name to clipboardExpand all lines: articles/batch/batch-nodejs-get-started.md
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# Get started with Batch SDK for Node.js
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Learn the basics of building a Batch client in Node.js using [Azure Batch Node.js SDK](/javascript/api/overview/azure/batch). We take a step by step approach of understanding a scenario for a batch application and then setting it up using a Node.js client.
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Learn the basics of building a Batch client in Node.js using [Azure Batch Node.js SDK](/javascript/api/overview/azure/batch). We take a step by step approach of understanding a scenario for a batch application and then setting it up using a Node.js client.
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## Prerequisites
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This article assumes that you have a working knowledge of Node.js and familiarity with Linux. It also assumes that you have an Azure account setup with access rights to create Batch and Storage services.
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{
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if(error.statusCode==404)
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{
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console.log("Pool not found yet returned 404...");
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console.log("Pool not found yet returned 404...");
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}
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else
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These tasks would run in parallel and deployed across multiple nodes, orchestrated by the Azure Batch service.
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> [!Tip]
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> You can use the [maxTasksPerNode](https://azure.github.io/azure-sdk-for-node/azure-batch/latest/Pool.html#add) property to specify maximum number of tasks that can run concurrently on a single node.
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> You can use the [taskSlotsPerNode](https://azure.github.io/azure-sdk-for-node/azure-batch/latest/Pool.html#add) property to specify maximum number of tasks that can run concurrently on a single node.
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```nodejs
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// storing container names in an array
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var container_list = ["con1","con2","con3","con4"]
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container_list.forEach(function(val,index){
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container_list.forEach(function(val,index){
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var container_name = val;
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var taskID = container_name + "_process";
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var task_config = {id:taskID,displayName:'process csv in ' + container_name,commandLine:'python processcsv.py --container ' + container_name,resourceFiles:[{'blobSource':'<blob SAS URI>','filePath':'processcsv.py'}]}
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var task = batch_client.task.add(poolid,task_config,function(error,result){
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{
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```
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The code adds multiple tasks to the pool. And each of the tasks is executed on a node in the pool of VMs created. If the number of tasks exceeds the number of VMs in a pool or the maxTasksPerNode property, the tasks wait until a node is made available. This orchestration is handled by Azure Batch automatically.
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The code adds multiple tasks to the pool. And each of the tasks is executed on a node in the pool of VMs created. If the number of tasks exceeds the number of VMs in a pool or the taskSlotsPerNode property, the tasks wait until a node is made available. This orchestration is handled by Azure Batch automatically.
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The portal has detailed views on the tasks and job statuses. You can also use the list and get functions in the Azure Node SDK. Details are provided in the documentation [link](https://azure.github.io/azure-sdk-for-node/azure-batch/latest/Job.html).
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