Azure Batch

note

This guide assumes you already have an Azure account with a valid Azure Subscription. For details, visit Azure Free Account. Ensure you have sufficient permissions to create resource groups, an Azure Storage account, and an Azure Batch account.

Azure concepts

Regions

Azure regions are specific geographic locations around the world where Microsoft has established data centers to host its cloud services. Each Azure region is a collection of data centers that provide users with high availability, fault tolerance, and low latency for cloud services. Each region offers a wide range of Azure services that can be chosen to optimize performance, ensure data residency compliance, and meet regulatory requirements. Azure regions also enable redundancy and disaster recovery options by allowing resources to be replicated across different regions, enhancing the resilience of applications and data.

Resource groups

An Azure resource group is a logical container that holds related Azure resources such as virtual machines, storage accounts, databases, and more. A resource group serves as a management boundary to organize, deploy, monitor, and manage the resources within it as a single entity. Resources in a resource group share the same lifecycle, meaning they can be deployed, updated, and deleted together. This also enables easier access control, monitoring, and cost management, making resource groups a foundational element in organizing and managing cloud infrastructure in Azure.

Accounts

Azure uses accounts for each service. For example, an Azure Storage account will house a collection of blob containers, file shares, queues, and tables. An Azure subscription can have multiple Azure Storage and Azure Batch accounts - however, a Platform compute environment can only use one of each. Multiple Platform compute environments can be created to use separate credentials, Azure Storage accounts, and Azure Batch accounts.

Service principals

An Azure service principal is an identity created specifically for applications, hosted services, or automated tools to access Azure resources. It acts like a user identity with a defined set of permissions, enabling resources authenticated through the service principal to perform actions within the Azure account. Seqera can utilize an Azure service principal to authenticate and access Azure Batch for job execution and Azure Storage for data management.

Create Azure resources

Resource group

Create a resource group to link your Azure Batch and Azure Storage account:

note

A resource group can be created while creating an Azure Storage account or Azure Batch account.

1. Log in to your Azure account, go to the Create Resource group page, and select Create new resource group.
2. Enter a name for the resource group, such as seqeracompute.
3. Choose the preferred region.
4. Select Review and Create to proceed.
5. Select Create.

Storage account

After creating a resource group, set up an Azure Storage account:

1. Log in to your Azure account, go to the Create storage account page, and select Create a storage account.
   note

   If you haven't created a resource group, you can do so now.

2. Enter a name for the storage account, such as seqeracomputestorage.
3. Choose the preferred region. This must be the same region as the Batch account.
4. Platform supports all performance or redundancy settings — select the most appropriate settings for your use case.
5. Select Next: Advanced.
6. Enable storage account key access.
7. Select Next: Networking.
   • Enable public access from all networks. You can enable public access from selected virtual networks and IP addresses, but you will be unable to use Forge to create compute resources. Disabling public access is not supported.
8. Select Data protection.
   • Configure appropriate settings. All settings are supported by the platform.
9. Select Encryption.
   • Only Microsoft-managed keys (MMK) are supported.
10. In tags, add any required tags for the storage account.
11. Select Review and Create.
12. Select Create to create the Azure Storage account.
    • You will need at least one Blob Storage container to act as a working directory for Nextflow.
13. Go to your new storage account and select + Container to create a new Blob Storage container. A new container dialog will open. Enter a suitable name, such as seqeracomputestorage-container.
14. Go to the Access Keys section of your new storage account (seqeracomputestorage in this example).
15. Store the access keys for your Azure Storage account, to be used when you create a Seqera compute environment.

caution

Blob container storage credentials are associated with the Batch pool configuration. Avoid changing these credentials in your Seqera instance after you have created the compute environment.

Batch account

After you have created a resource group and Storage account, create a Batch account:

1. Log in to your Azure account and select Create a batch account on this page.
2. Select the existing resource group or create a new one.
3. Enter a name for the Batch account, such as seqeracomputebatch.
4. Choose the preferred region. This must be the same region as the Storage account.
5. Select Advanced.
6. For Pool allocation mode, select Batch service.
7. For Authentication mode, select Shared Key.
8. Select Networking. Ensure networking access is sufficient for Platform and any additional required resources.
9. Add any Tags to the Batch account, if needed.
10. Select Review and Create.
11. Select Create.
12. Go to your new Batch account, then select Access Keys.
13. Store the access keys for your Azure Batch account, to be used when you create a Seqera compute environment.
    caution

    A newly-created Azure Batch account may not be entitled to create virtual machines without making a service request to Azure. See Azure Batch service quotas and limits for more information.

14. Select the + Quotas tab of the Azure Batch account to check and increase existing quotas if necessary.
15. Select + Request quota increase and add the quantity of resources you require. Here is a brief guideline:
    • Active jobs and schedules: Each Nextflow process will require an active Azure Batch job per pipeline while running, so increase this number to a high level. See here to learn more about jobs in Azure Batch.
    • Pools: Each platform compute environment requires at least one Azure Batch pool. Batch Forge creates two pools by default (one for the head job and one for compute tasks). Each pool is composed of multiple machines of one virtual machine size.
    note

    To use separate pools for head and compute nodes, see this FAQ entry.

    • Batch accounts per region per subscription: Set this to the number of Azure Batch accounts per region per subscription. Only one is required.
    • Total Dedicated vCPUs per VM series: See the Azure documentation for virtual machine sizes to help determine the machine size you need. We recommend the latest version of the ED series available in your region as a cost-effective and appropriately-sized machine for running Nextflow. However, you will need to select alternative machine series that have additional requirements, such as those with additional GPUs or faster storage. Increase the quota by the number of required concurrent CPUs. In Azure, machines are charged per cpu minute so there is no additional cost for a higher number.

Credentials

There are two types of Azure credentials available: access keys and Entra service principals.

Access keys are simple to use but have several limitations:

• Access keys are long-lived.
• Access keys provide full access to the Azure Storage and Azure Batch accounts.
• Azure allows only two access keys per account, making them a single point of failure.
• Access keys do not support VNet/subnet configuration.

Entra service principals are accounts which can be granted access to Azure Batch and Azure Storage resources:

• Service principals enable role-based access control with more precise permissions.
• Service principals map to a many-to-many relationship with Azure Batch and Azure Storage accounts.
• Some Azure Batch features, such as VNet/subnet configuration, are only available when using Microsoft Entra.

Both credential types support Batch Forge and Manual compute environment modes.

note

The two Azure credential types use different authentication methods. You can add more than one credential to a workspace, but Platform compute environments use only one credential at any given time. While separate credentials can be used by separate compute environments concurrently, they are not cross-compatible — access granted by one credential will not be shared with the other.

Access keys

To create an access key:

1. Navigate to the Azure Portal and sign in.
2. Locate the Azure Batch account and select Keys under Account management. The Primary and Secondary keys are listed here. Copy one of the keys and save it in a secure location for later use.
3. Locate the Azure Storage account and, under the Security and Networking section, select Access keys. Key1 and Key2 options are listed here. Copy one of them and save it in a secure location for later use.
4. In your Platform workspace Credentials tab, select the Add credentials button and complete the following fields:
   • Enter a Name for the credentials
   • Provider: Azure
   • Select the Shared key tab
   • Add the Batch account and Blob Storage account names and access keys to the relevant fields.
5. Delete the copied keys from their temporary location after they have been added to a credential in Platform.

Entra service principal and managed identity

To use Entra for authentication, you must create a service principal and managed identity. Seqera uses the service principal to authenticate to Azure Batch and Azure Storage. It submits a Nextflow task as the head process to run Nextflow, which authenticates to Azure Batch and Storage using the managed identity attached to the node pool.

Therefore, you must create both an Entra service principal and a managed identity:

1. Add the service principal details as credentials in Seqera Platform.
2. Assign the managed identity to each Azure Batch node pool with the relevant permissions.
3. When using Batch Forge, provide the managed identity resource ID for each managed identity. Seqera Platform assigns the identity to each pool during creation.

note

Entra service principal credentials support both Batch Forge and Manual compute environments. Some features, such as VNet/subnet configuration and managed identities, require Entra credentials. When using Entra credentials, a managed identity is recommended for best security practices, but is not mandatory.

Service principal

See Create a service principal for more details.

To create an Entra service principal:

1. In the Azure Portal, navigate to Microsoft Entra ID. Under App registrations, select New registration.
2. Provide a name for the application. The application will automatically have a service principal associated with it.
3. Assign roles to the service principal:
   1. Go to the Azure Storage account. Under Access Control (IAM), select Add role assignment.
   2. Select the Storage Blob Data Contributor role.
   3. Select Members, then Select Members. Search for your newly created service principal and assign the role.
   4. Repeat the same process for the Azure Batch account, using the Azure Batch Data Contributor role. This role is sufficient for pool creation and is narrower than the general Azure Batch Account Contributor role (which additionally grants Batch-account create/delete and shared-key regeneration — neither needed by Forge).
   5. If you create a managed identity (recommended), also assign the Managed Identity Operator role to the service principal on each managed identity. Without this role, Seqera cannot attach the managed identity to a Batch pool.
   6. If you plan to deploy Batch pools into a private VNet (by specifying a Subnet ID when creating the compute environment), also assign the Network Contributor role (or a custom role granting Microsoft.Network/virtualNetworks/subnets/join/action) to the service principal on the VNet. Only the service principal needs VNet permissions (the head and pool managed identities do not).
4. Platform will need credentials to authenticate as the service principal:
   1. Navigate back to the app registration. On the Overview page, save the Application (client) ID value for use in Platform.
   2. Select Certificates & secrets, then New client secret. A new secret is created containing a value and secret ID. Save both values securely for use in Platform.
5. In your Platform workspace Credentials tab, select the Add credentials button and complete the following fields:
   • Enter a Name for the credentials
   • Provider: Azure
   • Select the Entra tab
   • Complete the remaining fields: Batch account name, Blob Storage account name, Tenant ID (Directory (tenant) ID in Azure), Client ID (Application (client) ID in Azure), Client secret (Client secret value in Azure).
6. Delete the ID and secret values from their temporary location after they have been added to a credential in Platform.

Managed identity

info

To use managed identities, Seqera requires Nextflow version 24.06.0-edge or later.

Nextflow can authenticate to Azure services using a managed identity. This method offers enhanced security compared to access keys, but it must run on Azure infrastructure and requires Entra service principal credentials. Pool creation with a managed identity attached uses the Azure Batch management plane, which only accepts Entra (AAD) tokens, so shared-key credentials cannot create pools with managed identities.

When you use a compute environment with a managed identity attached to the Azure Batch pool, Nextflow uses this managed identity for authentication. Seqera still uses the Entra service principal to submit the initial Nextflow task; that task then proceeds with the managed identity for subsequent authentication.

1. In Azure, create a user-assigned managed identity. See Manage user-assigned managed identities for detailed steps. Take note of both the client ID and the resource ID of the managed identity when you create it.

2. Assign the following roles to the managed identity:

   • Storage Blob Data Contributor on the Azure Storage account, so the pool VMs can read inputs and write outputs.
   • AcrPull on any Azure Container Registry the pipeline pulls images from. Without this role, container pulls fail when the pool VM authenticates via the managed identity.

   See Required role assignments for more information.

3. Associate the user-assigned managed identity with the Azure Batch pool. See Set up managed identity in your Batch pool for more information.

   note

   When you use separate head and worker pools, you can assign a different managed identity to each pool. Typically, the head managed identity needs broader Batch and storage permissions, while the worker managed identity only needs storage and AcrPull access.

4. When you set up the Seqera compute environment, provide the managed identity details in the specified fields. The form has four managed identity fields — a client ID and a resource ID for both the head pool and the worker pool:

   • Resource IDs are the full ARM paths of the managed identities (e.g., /subscriptions/{subscriptionId}/resourceGroups/{resourceGroup}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}). Seqera passes these to Azure Batch at pool-create time to attach the managed identity to the head pool and worker pool VMs respectively. Resource IDs are required when using Batch Forge.
   • Client IDs are passed to Nextflow, Fusion, and AzCopy on the pool VMs. The Azure Instance Metadata Service uses the client ID to mint a token for the correct managed identity. A VM can have multiple managed identities attached, so the consumer must specify which one to use.

   You can use the same managed identity for both head and worker pools by entering the same values in both pairs of fields, but separate identities are recommended so that worker RBAC can stay narrower than head RBAC.

   The four fields work for both single-pool and dual-pool topologies:

   • Single-pool (head pool only): both managed identities are attached to the same VMs. The client IDs disambiguate which managed identity each consumer authenticates as.
   • Dual-pool (separate head and worker pools): each pool has only its own managed identity attached, so disambiguation is implicit at the VM level. The client IDs are still required so that consumers know which managed identity is theirs.

When you submit a pipeline to this compute environment, Nextflow authenticates using the managed identity associated with the Azure Batch node it runs on, rather than relying on access keys.

caution

If a managed identity is misconfigured (for example, invalid client ID or missing RBAC roles), the pipeline fails with an explicit error. Seqera will not silently fall back to access key authentication.

Add Seqera compute environment

There are two ways to create an Azure Batch compute environment in Seqera Platform:

• Batch Forge: Automatically creates Azure Batch resources.
• Manual: For using existing Azure Batch resources.

tip

For an end-to-end walkthrough of Azure Batch topologies (separate head and worker pools, Entra authentication, and private networking), see Set up advanced Azure Batch compute environments.

VM size considerations

Azure Batch requires you to select an appropriate VM size for your compute environment. There are a number of considerations when selecting VM sizes — See Sizes for virtual machines in Azure for more information.

1. Family: The first letter of the VM size name indicates the machine family. For example, Standard_E16d_v5 is a member of the E family.
   • A: Economical machines, low power machines.
   • B: Burstable machines which use credits for cost allocation.
   • D: General purpose machines suitable for most applications.
   • DC: D machines with additional confidential compute capabilities.
   • E: The same as D but with more memory. These are generally the best machines for bioinformatics workloads.
   • EC: The same as E but with additional confidential compute capabilities.
   • F: Compute optimized machines which come with a faster CPU compared to D-series machines.
   • M: Memory optimized machines which come with extremely large and fast memory layers, typically more than is needed for bioinformatics workloads.
   • L: Storage optimized machines which come with large locally attached NVMe storage drives. Note that these need to be configured before you can use them with Azure Batch.
   • N: Accelerated computing machines which come with FPGAs, GPUs, or custom ASICs.
   • H: High performance machines which come with the fastest processors and memory.

In general, we recommend using the E family of machines for bioinformatics workloads since these are cost-effective, widely available, and sufficiently fast.

1. vCPUs: The machine's number of vCPUs. This is the main factor in determining the speed of the machine.

2. features: Additional machine features. For example, some machines come with a local SSD.

   • d: A local temp disk. Azure Batch uses this disk for task working directories, and Batch Forge pools can also use it for container data.
   • s: The VM supports a premium storage account.
   • a: AMD CPUs instead of Intel.
   • p: ARM-based CPUs, such as Azure Cobalt.
   • l: Reduced memory with a large cost reduction.

3. Version: The version of the VM size. This is the generation of the machine. Typically, more recent is better but availability can vary between regions.

In the Azure Portal on the page for your Azure Batch account, request an appropriate quota for your desired VM size. See Azure Batch service quotas and limits for more information.

note

When a VM size has a local temp disk (/mnt) of at least 128 GB that is at least as large as the boot disk, Batch Forge pools store Docker and containerd data on the temp disk instead of the OS disk. The temp disk is faster than the default OS disk, which keeps container creation within the Batch node agent's 5-minute limit on busy nodes. Many d sizes from v4 and v5 qualify, such as Standard_E16d_v5. NVMe-only v6 sizes don't.

Container images share the temp disk with task working directories. Allow for both when you choose a VM size. Existing compute environments keep container data on the OS disk. To use the temp disk, create the compute environment again.

Batch Forge

caution

Batch Forge automatically creates resources that you may be charged for in your Azure account. See Cloud costs for guidelines to manage cloud resources effectively and prevent unexpected costs.

Create a Batch Forge Azure Batch compute environment:

1. In a workspace, select Compute Environments > New Environment.

2. Enter a descriptive name, such as Azure Batch (east-us).

3. Select Azure Batch as the target platform.

4. Choose existing Azure credentials or add a new credential.

   note

   Both access keys and Entra service principal credentials are supported for Batch Forge. Some features, such as VNet/subnet configuration, require Entra credentials.

5. Add the Batch account and Blob Storage account names and access keys.

6. Select a Region, such as eastus.

7. In the Work directory field, enter the Azure blob container created previously. For example, az://seqeracomputestorage-container/work.

   note

   When you specify a Blob Storage bucket as your work directory, this bucket is used for the Nextflow cloud cache by default. You can specify an alternative cache location with the Nextflow config file field on the pipeline launch form.

8. Select Enable Wave containers to facilitate access to private container repositories and provision containers in your pipelines using the Wave containers service. See Wave containers for more information.

9. Select Enable Fusion v2 to allow access to your Azure Blob Storage data via the Fusion v2 virtual distributed file system. This speeds up most data operations. The Fusion v2 file system requires Wave containers to be enabled. See Fusion file system for configuration details.

   Use Fusion v2

   note

   The compute recommendations below are based on internal benchmarking performed by Seqera. Benchmark runs of nf-core/rnaseq used profile test_full, consisting of an input dataset with 16 FASTQ files and a total size of approximately 123.5 GB.

   Azure virtual machines include fast SSDs and require no additional storage configuration for Fusion. For optimal performance, use VMs with sufficient local storage to support Fusion's streaming data throughput.

   1. Use Seqera Platform version 23.1 or later.
   2. Use an Azure Blob storage container as the work directory.
   3. Enable Wave containers and Fusion v2.
   4. Select the Batch Forge config mode.
   5. Specify suitable VM sizes under VMs type. A Standard_E16d_v5 VM or larger is recommended for production use.

   tip

   We recommend selecting machine types with a local temp storage disk of at least 200 GB and a random read speed of 1000 MBps or more for large and long-lived production pipelines. To work with files larger than 100 GB, increase temp storage accordingly (400 GB or more). On Batch Forge pools, container images also use this disk.

   The suffix d after the core number (e.g., Standard_E16*d*_v5) denotes a VM with a local temp disk. Select instances with Standard SSDs — Fusion does not support Azure network-attached storage (Premium SSDv2, Ultra Disk, etc.). Larger local storage increases Fusion's throughput and reduces the chance of overloading the machine. See Sizes for virtual machines in Azure for more information.

10. (Optional) Enter a Subnet ID to connect the Batch pool nodes to a private Azure VNet. Enter the full Azure ARM subnet resource ID in the following format:

    /subscriptions/{subscriptionId}/resourceGroups/{resourceGroup}/providers/Microsoft.Network/virtualNetworks/{vnetName}/subnets/{subnetName}

    note

    VNet/subnet configuration requires Entra credentials. This field is only available when Entra credentials are selected. If no subnet ID is provided, default networking is used. The service principal must have the Network Contributor role (or Microsoft.Network/virtualNetworks/subnets/join/action) on the VNet, otherwise pool creation fails.

11. Set the Config mode to Batch Forge.

12. Enter the default VMs type for compute tasks, depending on your quota limits set previously. The default is Standard_D4_v3.

    note

    See VM size considerations for how Batch Forge uses the temp disk of the VM size you select.

13. Enter the VMs count. If autoscaling is enabled (default), this is the maximum number of VMs the compute pool will scale up to. If autoscaling is disabled, this is the fixed number of virtual machines in the compute pool.

14. (Optional) Configure Head job resources to control the VM type and resources allocated to the Nextflow head job:

    • Head VM type: The VM size for the head node pool. If not specified, the same VM type as the compute pool is used.
    • Head job CPUs: The number of CPUs allocated to the Nextflow head job.
    • Head job memory: The amount of memory allocated to the Nextflow head job.

15. Enable Autoscale to scale the compute pool up and down automatically, based on the number of pipeline tasks. The number of VMs will vary from 0 to VMs count.

16. Enable Dispose resources for Seqera to automatically delete the Batch pools if the compute environment is deleted on the platform.

info

Batch Forge creates separate Azure Batch pools for the Nextflow head job and compute tasks by default (named tower-pool-{envId}-head and tower-pool-{envId}-worker). This prevents the head node from competing for resources with compute tasks and allows independent sizing of each pool.

1. Select or create Container registry credentials to authenticate a registry (used by the Wave containers service). It is recommended to use an Azure Container registry within the same region for maximum performance.

2. Apply Resource labels. This will populate the Metadata fields of the Azure Batch pools and jobs.

3. Expand Staging options to include:

   • Optional pre- or post-run Bash scripts that execute before or after the Nextflow pipeline execution in your environment.
   • Global Nextflow configuration settings for all pipeline runs launched with this compute environment. Values defined here are pre-filled in the Nextflow config file field in the pipeline launch form. These values can be overridden during pipeline launch.
   info

   Configuration settings in this field override the same values in the pipeline repository nextflow.config file. See Nextflow config file for more information on configuration priority.

4. Under Environment variables, add each variable with a Name, Value, and Target Environment:

   • Head job: Adds the variable to the Nextflow head job container, which evaluates nextflow.config and submits tasks to the compute backend. Use this target for variables that Nextflow or its plugins read, such as NXF_OPTS, NXF_JVM_ARGS, NXF_PLUGINS_DEFAULT, or proxy settings the head node uses to reach external services.
   • Compute job: Adds the variable to the worker containers that run individual pipeline tasks. Use this target for variables your pipeline tools read, such as OPENAI_API_KEY for a process that calls the OpenAI API, registry credentials needed inside the task container, or tool-specific settings like JAVA_HOME.
   • Head and Compute jobs: Adds the variable to both the head job and the compute jobs. Use this target for values needed in both places, such as an HTTP proxy used by both Nextflow and task tools, or a credential needed in both the head job and individual compute tasks.
   note

   For sensitive values such as API keys and tokens, use pipeline secrets instead of custom environment variables. Custom environment variables are stored in the compute environment configuration and cannot be edited after creation. To rotate a value, recreate the compute environment.

5. Configure any advanced options you need:

   • Use Max wallclock time to set the maximum duration a job can run. The default is 7 days. Accepts human-readable duration syntax (e.g., 7d, 12h, 1d6h30m). The maximum allowed by Azure Batch is 180 days. Existing compute environments without this setting use Nextflow's default of 30 days.

   • Job cleanup toggles control how Nextflow process jobs are managed on completion. Active jobs consume the quota of your Azure Batch account. Three independent toggles are available:

     Toggle	Default	Description
     Delete jobs on completion	Off	Permanently deletes all jobs and their tasks from Azure Batch when the workflow finishes.
     Delete tasks on completion	On	Deletes individual tasks from jobs when they complete successfully. Failed tasks are preserved for debugging.
     Terminate jobs on completion	On	Sets jobs to terminate when all their tasks complete. Jobs remain in "completed" state but are no longer active.

     Existing compute environments retain their current cleanup behavior.

   • Use Token duration to control the duration of the SAS token generated by Nextflow. This must be as long as the longest period of time the pipeline will run.

6. Select Add to finalize the compute environment setup. It will take a few seconds for all the resources to be created before the compute environment is ready to launch pipelines.

info

See Launch pipelines to start executing workflows in your Azure Batch compute environment.

Manual

You can configure Seqera Platform to use a pre-existing Azure Batch pool. This allows the use of more advanced Azure Batch features, such as custom VM images and private networking. See Azure Batch security best practices for more information.

caution

Your Seqera compute environment uses resources that you may be charged for in your Azure account. See Cloud costs for guidelines to manage cloud resources effectively and prevent unexpected costs.

Create a Nextflow-compatible Azure Batch pool

If not described below, use the default settings:

1. Account: You must have an existing Azure Batch account. Ideally, you should already have tested whether you can run an Azure Batch task within this account. Any type of account is compatible.

2. Quota: You must check you have sufficient quota for the number of pools, jobs, and vCPUs per series. See Azure Batch service quotas and limits for more information.

3. On the Azure Batch page of the Azure Portal, select Pools and then + Add.

4. Name: Enter a Pool ID and Display Name. This ID will be used by Seqera and Nextflow.

5. Identity: Select User assigned to use a managed identity for the pool. Select Add for the user-assigned managed identity and select the managed identity with the correct permissions to the Azure Storage and Batch accounts.

6. Operating System: You can use any Linux-based image here, but it is recommended to use it with a Microsoft Azure Batch-provided image. Note that there are two generations of Azure Virtual Machine images, and certain VM series are only available in one generation. See Azure Virtual Machine series for more information. For default settings, select the following:

   • Publisher: microsoft-dsvm
   • Offer: ubuntu-hpc
   • Sku: 2204
   • Security type: standard

7. OS disk storage account type: Certain VM series only support a specific Storage account type. See Azure managed disk types and Azure Virtual Machine series for more information. In general, a VM series with the suffix s supports a Premium LRS Storage account type. For example, a standard_e16ds_v5 supports Premium_LRS but a standard_e16d_v5 does not. Premium LRS offers the best performance.

8. OS disk size: The size of the OS disk in GB. This must be sufficient to hold every Docker container the VM will run, plus any logging or further files. If you are not using a machine with attached storage, you must increase this disk size to accommodate task files (see VM type below). If you are using a machine with attached storage, this setting can be left at the OS default size.

9. Container configuration: Container configuration must be turned on. Do this by switching it from None to Custom. The type is Docker compatible which should be the only available option. This will enable the VM to use Docker images and is sufficient. However, you can add further options:

   • Under Container image names you can add containers for the VM to grab at startup time. Add a list of fully qualified Docker URIs, such as quay.io/seqeralabs/nf-launcher:j17-23.04.2. - Under Container registries, you can add any container registries that require additional authentication. Select Container registries, then Add. Here, you can add a registry username, password, and registry server. If you attached the managed identity earlier, select this as an authentication method so you don't have to enter a username and password.

10. VM size: This is the size of the VM. See Sizes for virtual machines in Azure for more information.

11. Scale: Azure Node pools can be fixed in size or autoscale based on a formula. Autoscaling is recommended to enable scaling your resources down to zero when not in use. Select Auto scale and change the AutoScale evaluation interval to 5 minutes - this is the minimum period between evaluations of the autoscale formula. For Formula, you can use any valid formula — See Create a formula to automatically scale compute nodes in a Batch pool for more information. This is the default autoscaling formula, with a maximum of 8 VMs:

    // Get pool lifetime since creation.
    lifespan = time() - time("2024-10-30T00:00:00.880011Z");
    interval = TimeInterval_Minute * 5;
    
    // Compute the target nodes based on pending tasks.
    // $PendingTasks == The sum of $ActiveTasks and $RunningTasks
    $samples = $PendingTasks.GetSamplePercent(interval);
    $tasks = $samples < 70 ? max(0, $PendingTasks.GetSample(1)) : max( $PendingTasks.GetSample(1), avg($PendingTasks.GetSample(interval)));
    $targetVMs = $tasks > 0 ? $tasks : max(0, $TargetDedicatedNodes/2);
    targetPoolSize = max(0, min($targetVMs, 8));
    
    // For first interval, deploy 1 node, for other intervals scale up/down as per tasks.
    $TargetDedicatedNodes = lifespan < interval ? 1 : targetPoolSize;
    $NodeDeallocationOption = taskcompletion;

12. Start task: This is the task that will run on each VM when it joins the pool. This can be used to install additional software on the VM. When using Batch Forge, this is used to install azcopy for staging files onto and off of the node. Select Enabled and add the following command line to install azcopy:

    bash -c "chmod +x azcopy && mkdir $AZ_BATCH_NODE_SHARED_DIR/bin/ && cp azcopy $AZ_BATCH_NODE_SHARED_DIR/bin/"

    Select Resource files then select Http url. For the URL, add https://nf-xpack.seqera.io/azcopy/linux_amd64_10.8.0/azcopy and for File path enter azcopy. Every other setting can be left default.

    note

    When not using Fusion, every node must have azcopy installed.

13. Task Slots: Set task slots to the machine's number of vCPUs. For example, select 4 for a Standard_D4_v3 VM size.

14. Task scheduling policy: This can be set to Pack or Spread. Pack will attempt to schedule tasks from the same job on the same VM, while Spread will attempt to distribute tasks evenly across VMs.

15. Virtual Network: If you are using a virtual network, you can select it here. Be sure to select the correct virtual network and subnet. The VMs require:

    • Access to container registries (such as quay.io and docker.io) to pull containers.
    • Access to Azure Storage to copy data using azcopy.
    • Access to any remote files required by the pipeline, such as AWS S3 storage.
    • Communication with the head node that runs Nextflow and Seqera to relay logs and information. Note that overly-restrictive networking may prevent pipelines from running successfully.

16. Mount configuration: Nextflow only supports Azure File Shares. Select Azure Files Share, then add:

    • Source: URL in format https://${accountName}.file.core.windows.net/${fileShareName}
    • Relative mount path: Path where the file share will be mounted on the VM
    • Storage account name and Storage account key (managed identity is not supported)

Leave the node pool to start and create a single Azure VM. Monitor the VM to ensure it starts correctly. If any errors occur, check and correct them - you may need to create a new Azure node pool if issues persist.

The following settings can be modified after creating a pool:

• Autoscale formula
• Start task
• Application packages
• Node communication
• Metadata

Create a manual Seqera Azure Batch compute environment

1. In a workspace, select Compute Environments, then Add compute environment.

2. Enter a descriptive name for this environment, such as Azure Batch (east-us).

3. For Provider, select Azure Batch.

4. Select your existing Azure credentials (access keys or Entra service principal) or select + to add new credentials.

   note

   Both access keys and Entra service principal credentials are supported. Some features, such as VNet/subnet configuration, require Entra credentials. To use Entra with a managed identity, see Managed identity below.

5. Select a Region, such as eastus (East US).

6. In the Work directory field, add the Azure blob container created previously. For example, az://seqeracomputestorage-container/work.

   note

   When you specify a Blob Storage bucket as your work directory, this bucket is used for the Nextflow cloud cache by default. You can specify an alternative cache location with the Nextflow config file field on the pipeline launch form.

7. Select Enable Wave containers to facilitate access to private container repositories and provision containers in your pipelines using the Wave containers service. See Wave containers for more information.

8. Select Enable Fusion v2 to allow access to your Azure Blob Storage data via the Fusion v2 virtual distributed file system. This speeds up most data operations. The Fusion v2 file system requires Wave containers to be enabled. See Fusion file system for configuration details.

   Use Fusion v2

   note

   The compute recommendations below are based on internal benchmarking performed by Seqera. Benchmark runs of nf-core/rnaseq used profile test_full, consisting of an input dataset with 16 FASTQ files and a total size of approximately 123.5 GB.

   Azure virtual machines include fast SSDs and require no additional storage configuration for Fusion. For optimal performance, use VMs with sufficient local storage to support Fusion's streaming data throughput.

   1. Use Seqera Platform version 23.1 or later.
   2. Use an Azure Blob storage container as the work directory.
   3. Enable Wave containers and Fusion v2.
   4. Specify suitable VM sizes under VMs type. A Standard_E16d_v5 VM or larger is recommended for production use.

   tip

   We recommend selecting machine types with a local temp storage disk of at least 200 GB and a random read speed of 1000 MBps or more for large and long-lived production pipelines. To work with files larger than 100 GB, increase temp storage accordingly (400 GB or more).

   The suffix d after the core number (e.g., Standard_E16*d*_v5) denotes a VM with a local temp disk. Select instances with Standard SSDs — Fusion does not support Azure network-attached storage (Premium SSDv2, Ultra Disk, etc.). Larger local storage increases Fusion's throughput and reduces the chance of overloading the machine. See Sizes for virtual machines in Azure for more information.

9. Set the Config mode to Manual.

10. Enter the Compute Pool name. This is the name of the Azure Batch pool you created previously in the Azure Batch account.

    note

    Batch Forge creates separate head and worker pools by default. For manual environments, you can also use separate pools to run compute tasks on low-priority VMs. See Use separate Batch pools for head and compute nodes.

11. Enter a user-assigned Managed identity client ID, if one is attached to your Azure Batch pool. See Managed Identity below.

12. Apply Resource labels. This will populate the Metadata fields of the Azure Batch pool.

13. Expand Staging options to include:

    • Optional pre- or post-run Bash scripts that execute before or after the Nextflow pipeline execution in your environment.
    • Global Nextflow configuration settings for all pipeline runs launched with this compute environment. Values defined here are pre-filled in the Nextflow config file field in the pipeline launch form. These values can be overridden during pipeline launch.
    info

    Configuration settings in this field override the same values in the pipeline repository nextflow.config file. See Nextflow config file for more information on configuration priority.

14. Under Environment variables, add each variable with a Name, Value, and Target Environment:

    • Head job: Adds the variable to the Nextflow head job container, which evaluates nextflow.config and submits tasks to the compute backend. Use this target for variables that Nextflow or its plugins read, such as NXF_OPTS, NXF_JVM_ARGS, NXF_PLUGINS_DEFAULT, or proxy settings the head node uses to reach external services.
    • Compute job: Adds the variable to the worker containers that run individual pipeline tasks. Use this target for variables your pipeline tools read, such as OPENAI_API_KEY for a process that calls the OpenAI API, registry credentials needed inside the task container, or tool-specific settings like JAVA_HOME.
    • Head and Compute jobs: Adds the variable to both the head job and the compute jobs. Use this target for values needed in both places, such as an HTTP proxy used by both Nextflow and task tools, or a credential needed in both the head job and individual compute tasks.
    note

    For sensitive values such as API keys and tokens, use pipeline secrets instead of custom environment variables. Custom environment variables are stored in the compute environment configuration and cannot be edited after creation. To rotate a value, recreate the compute environment.

15. Configure any necessary advanced options:

    • Use Jobs cleanup policy to control how Nextflow process jobs are deleted on completion. Active jobs consume the quota of the Azure Batch account. By default, jobs are terminated by Nextflow and removed from the quota when all tasks successfully complete. If set to Always, all jobs are deleted by Nextflow after pipeline completion. If set to Never, jobs are never deleted. If set to On success, successful tasks are removed but failed tasks will be left for debugging purposes.
    • Use Token duration to control the duration of the SAS token generated by Nextflow. This must be as long as the longest period of time the pipeline will run.

16. Select Add to complete the compute environment setup. The creation of resources will take a few seconds, after which you can launch pipelines.

info

See Launch pipelines to start executing workflows in your Azure Batch compute environment.