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Run Azure Batch workloads on cost-effective low-priority VMs | Microsoft Docs |
Learn how to provision low-priority VMs to reduce the cost of Azure Batch workloads. |
batch |
mscurrell |
timlt |
dc6ba151-1718-468a-b455-2da549225ab2 |
batch |
multiple |
article |
na |
09/28/2017 |
markscu |
Azure Batch offers low-priority virtual machines (VMs) to reduce the cost of Batch workloads. Low-priority VMs make new types of Batch workloads possible by providing a large amount of compute power that is also economical.
Low-priority VMs take advantage of surplus capacity in Azure. When you specify low-priority VMs in your pools, Azure Batch can automatically use this surplus when available.
The tradeoff for using low-priority VMs is that those VMs may be preempted when no surplus capacity is available in Azure. For this reason, low-priority VMs are most suitable for certain types of workloads. Use low-priority VMs for batch and asynchronous processing workloads where the job completion time is flexible and the work is distributed across many VMs.
Low-priority VMs are offered at a significantly reduced price compared with dedicated VMs. For pricing details, see Batch Pricing.
Important
Low-priority VMs are currently available only for workloads running in Batch.
Given the characteristics of low-priority VMs, what workloads can and cannot use them? In general, batch processing workloads are a good fit, as jobs are broken into many parallel tasks or there are many jobs that are scaled out and distributed across many VMs.
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To maximize use of surplus capacity in Azure, suitable jobs can scale out.
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Occasionally VMs may not be available or are preempted, which results in reduced capacity for jobs and may lead to task interruption and reruns. Jobs must therefore be flexible in the time they can take to run.
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Jobs with longer tasks may be impacted more if interrupted. If long-running tasks implement checkpointing to save progress as they execute, then the impact of interruption is reduced. Tasks with shorter execution times tend to work best with low-priority VMs, because the impact of interruption is far less.
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Long-running MPI jobs that utilize multiple VMs are not well suited to use low-priority VMs, because one preempted VM can lead to the whole job having to run again.
Some examples of batch processing use cases well suited to use low-priority VMs are:
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Development and testing: In particular, if large-scale solutions are being developed, significant savings can be realized. All types of testing can benefit, but large-scale load testing and regression testing are great uses.
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Supplementing on-demand capacity: Low-priority VMs can be used to supplement regular dedicated VMs - when available, jobs can scale and therefore complete quicker for lower cost; when not available, the baseline of dedicated VMs remains available.
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Flexible job execution time: If there is flexibility in the time jobs have to complete, then potential drops in capacity can be tolerated; however, with the addition of low-priority VMs jobs frequently run faster and for a lower cost.
Batch pools can be configured to use low-priority VMs in a few ways, depending on the flexibility in job execution time:
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Low-priority VMs can solely be used in a pool. In this case, Batch recovers any preempted capacity when available. This configuration is the cheapest way to execute jobs, as only low-priority VMs are used.
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Low-priority VMs can be used in conjunction with a fixed baseline of dedicated VMs. The fixed number of dedicated VMs ensures there is always some capacity to keep a job progressing.
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There can be dynamic mix of dedicated and low-priority VMs, so that the cheaper low-priority VMs are solely used when available, but the full-priced dedicated VMs are scaled up when required. This configuration keeps a minimum amount of capacity available to keep the jobs progressing.
Azure Batch provides several capabilities that make it easy to consume and benefit from low-priority VMs:
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Batch pools can contain both dedicated VMs and low-priority VMs. The number of each type of VM can be specified when a pool is created, or changed at any time for an existing pool, using the explicit resize operation or using auto-scale. Job and task submission can remain unchanged, regardless of the VM types in the pool. You can also configure a pool to completely use low-priority VMs to run jobs as cheaply as possible, but spin up dedicated VMs if the capacity drops below a minimum threshold, to keep jobs running.
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Batch pools automatically seek the target number of low-priority VMs. If VMs are preempted, then Batch attempts to replace the lost capacity and return to the target.
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When tasks are interrupted, Batch detects and automatically requeues tasks to run again.
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Low-priority VMs have a separate vCPU quota, differs from the one for dedicated VMs. The quota for low-priority VMs is higher than the quota for dedicated VMs, because low-priority VMs cost less. For more information, see Batch service quotas and limits.
A Batch pool can contain both dedicated and low-priority VMs (also referred to as compute nodes). You can set the target number of compute nodes for both dedicated and low-priority VMs. The target number of nodes specifies the number of VMs you want to have in the pool.
For example, to create a pool using Azure cloud service VMs with a target of 5 dedicated VMs and 20 low-priority VMs:
CloudPool pool = batchClient.PoolOperations.CreatePool(
poolId: "cspool",
targetDedicatedComputeNodes: 5,
targetLowPriorityComputeNodes: 20,
virtualMachineSize: "Standard_D2_v2",
cloudServiceConfiguration: new CloudServiceConfiguration(osFamily: "4") // WS 2012 R2
);
To create a pool using Azure virtual machines (in this case Linux VMs) with a target of 5 dedicated VMs and 20 low-priority VMs:
ImageReference imageRef = new ImageReference(
publisher: "Canonical",
offer: "UbuntuServer",
sku: "16.04.0-LTS",
version: "latest");
// Create the pool
VirtualMachineConfiguration virtualMachineConfiguration =
new VirtualMachineConfiguration("batch.node.ubuntu 16.04", imageRef);
pool = batchClient.PoolOperations.CreatePool(
poolId: "vmpool",
targetDedicatedComputeNodes: 5,
targetLowPriorityComputeNodes: 20,
virtualMachineSize: "Standard\_D2\_v2",
virtualMachineConfiguration: virtualMachineConfiguration);
You can get the current number of nodes for both dedicated and low-priority VMs:
int? numDedicated = pool1.CurrentDedicatedComputeNodes;
int? numLowPri = pool1.CurrentLowPriorityComputeNodes;
Pool nodes have a property to indicate if the node is a dedicated or low-priority VM:
bool? isNodeDedicated = poolNode.IsDedicated;
When one or more nodes in a pool are preempted, a list nodes operation on the pool still returns those nodes. The current number of low-priority nodes remains unchanged, but those nodes have their state set to the Preempted state. Batch attempts to find replacement VMs and, if successful, the nodes go through Creating and then Starting states before becoming available for task execution, just like new nodes.
As with pools solely consisting of dedicated VMs, it is possible to scale a pool containing low-priority VMs by calling the Resize method or by using autoscale.
The pool resize operation takes a second optional parameter that updates the value of targetLowPriorityNodes:
pool.Resize(targetDedicatedComputeNodes: 0, targetLowPriorityComputeNodes: 25);
The pool autoscale formula supports low-priority VMs as follows:
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You can get or set the value of the service-defined variable $TargetLowPriorityNodes.
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You can get the value of the service-defined variable $CurrentLowPriorityNodes.
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You can get the value of the service-defined variable $PreemptedNodeCount. This variable returns the number of nodes in the preempted state and allows you to scale up or down the number of dedicated nodes, depending on the number of preempted nodes that are unavailable.
Jobs and tasks require little additional configuration for low-priority nodes; the only support is as follows:
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The JobManagerTask property of a job has a new property, AllowLowPriorityNode. When this property is true, the job manager task can be scheduled on either a dedicated or low-priority node. If this property is false, the job manager task is scheduled to a dedicated node only.
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An environment variable is available to a task application so that it can determine whether it is running on a low-priority or dedicated node. The environment variable is AZ_BATCH_NODE_IS_DEDICATED.
VMs may occasionally be preempted; when preemption happens, Batch does the following:
- The preempted VMs have their state updated to Preempted.
- If tasks were running on the preempted node VMs, then those tasks are requeued and run again.
- The VM is effectively deleted, leading to loss of any data stored locally on the VM.
- The pool continually attempts to reach the target number of low-priority nodes available. When replacement capacity is found, the nodes keep their IDs, but are reinitialized, going through Creating and Starting states before they are available for task scheduling.
- Preemption counts are available as a metric in the Azure portal.
New metrics are available in the Azure portal for low-priority nodes. These metrics are:
- Low-Priority Node Count
- Low-Priority Core Count
- Preempted Node Count
To view metrics in the Azure portal:
- Navigate to your Batch account in the portal, and view the settings for your Batch account.
- Select Metrics from the Monitoring section.
- Select the metrics you desire from the Available Metrics list.
- Read the Batch feature overview for developers, essential information for anyone preparing to use Batch. The article contains more detailed information about Batch service resources like pools, nodes, jobs, and tasks, and the many API features that you can use while building your Batch application.
- Learn about the Batch APIs and tools available for building Batch solutions.