Select your cookie preferences

We use essential cookies and similar tools that are necessary to provide our site and services. We use performance cookies to collect anonymous statistics, so we can understand how customers use our site and make improvements. Essential cookies cannot be deactivated, but you can choose “Customize” or “Decline” to decline performance cookies.

If you agree, AWS and approved third parties will also use cookies to provide useful site features, remember your preferences, and display relevant content, including relevant advertising. To accept or decline all non-essential cookies, choose “Accept” or “Decline.” To make more detailed choices, choose “Customize.”

Tutorial: Create a scheduling policy

Focus mode
Tutorial: Create a scheduling policy - AWS Batch

Before you can create a job queue with a scheduling policy, you must create a scheduling policy. When you create a fair-share scheduling policy, you associate one or more share identifiers or share identifier prefixes with weights for the queue and optionally assign a decay period and compute reservation to the policy.

To create a scheduling policy
  1. Open the AWS Batch console at https://console.aws.amazon.com/batch/.

  2. From the navigation bar, select the Region to use.

  3. In the navigation pane, choose Scheduling policies, Create.

  4. For Name, enter a unique name for your scheduling policy. Up to 128 letters (uppercase and lowercase), numbers, hyphens, and underscores are allowed.

  5. (Optional) For Share decay seconds, enter an integer value for the fair-share scheduling policy's share decay time. A longer share decay time will use considerably more compute resource usage over a longer time when scheduling jobs. This can allow jobs using a share identifier to temporarily use more compute resources than the weight for that share identifier would allow if that share identifier had not recently been using compute resources.

  6. (Optional) For Compute reservation, enter an integer value for the fair-share scheduling policy's compute reservation. The compute reservation will hold some vCPUs in reserve to be used for share identifiers that are not currently active.

    The reserved ratio is (computeReservation/100)^ActiveFairShares where ActiveFairShares is the number of active share identifiers.

    For example, a computeReservation value of 50 indicates that AWS Batch should reserve 50% of the maximum available VCPU if there is only one share identifier, 25% if there are two share identifiers, and 12.5% if there are three share identifiers. A computeReservation value of 25 indicates that AWS Batch should reserve 25% of the maximum available VCPU if there is only one share identifier, 6.25% if there are two share identifiers, and 1.56% if there are three share identifiers.

  7. In the Share attributes section, you can specify the share identifier and weight for each share identifier to associate with the fair-share scheduling policy.

    1. Choose Add share identifier.

    2. For Share identifier, specify the share identifier. If the string ends with '*', this becomes a share identifier prefix used to match share identifiers for jobs. All of the share identifiers and share identifier prefixes in a scheduling policy must be unique and cannot overlap. For example, you can't have share identifiers prefix 'UserA*' and share identifier 'UserA1' in the same fair-share scheduling policy.

    3. For Weight factor, specify the relative weight for the share identifier. The default value is 1.0. A lower value has a higher priority for compute resources. If a share identifier prefix is used, jobs with share identifiers that start with the prefix will share the weight factor. This effectively increases the weight factor for those jobs, lowering their individual priority but maintaining the same weight factor for the share identifier prefix.

  8. (Optional) In the Tags section, you can specify the key and value for each tag to associate with the scheduling policy. For more information, see Tag your AWS Batch resources.

  9. Choose Submit to finish and create your scheduling policy.

PrivacySite termsCookie preferences
© 2025, Amazon Web Services, Inc. or its affiliates. All rights reserved.