Merge Queue Batches

Mergify’s batch merging feature is a powerful tool that enhances productivity and efficiency in your development workflow. Instead of merging pull requests one by one, which can be time-consuming, especially for larger projects, batch merging allows you to combine and merge multiple pull requests at once.

The batch merging process works by setting a batch_size option on your merge queue. This option determines the number of pull requests that Mergify will check at the same time using your CI. If the CI validation passes, Mergify merges all the pull requests in the batch and closes the batch pull request it created to test.

If a failure occurs, Mergify identifies the problematic pull request(s) automatically and removes them from the queue, allowing the rest of the queue to be processed as usual (see Handling Batch Failures).

This feature is especially useful for large-scale projects with many pull requests to merge, as it can significantly reduce the time required to merge them all.

Batch merging works by utilizing the batch_size option in your Mergify queue configuration. This option tells Mergify how many pull requests it should try to combine and validate at once. The batch_size can be adjusted according to the needs of your project, with a higher number indicating a larger batch size.

For example, if you set batch_size to 3, Mergify will create a batch pull request that includes the changes from the next three pull requests in the queue. This batch pull request is then validated by your CI system. If all checks pass, then the three pull requests included in the batch are deemed ready to be merged.

queue_rules:
  - name: default
    batch_size: 3
    ...

This batch merging process allows multiple pull requests to be validated and merged more efficiently than if they were handled individually.

Configuring batch merging involves adjusting your Mergify configuration file to set the batch_size option according to your project’s needs.

1. Open your Mergify configuration file.

2. Under queue_rules, set the batch_size option to the number of pull requests you want to be tested together in a batch.

queue_rules:
  - name: default
    batch_size: 3
    ...

In the above example, batches of up to 3 pull requests will be created and tested together.

You can configure the delay that Mergify will use to wait for the batch to be filled up using the batch_max_wait_time option.

queue_rules:
  - name: default
    batch_size: 5
    batch_max_wait_time: 5 min
    ...

With the configuration above, Mergify waits up to 5 minutes for 5 PR to enter the queue before creating a batch. This allows you to pick the right trade-off between latency and minimal CI usage.

When batch_size is greater than 1, Mergify has to decide which pull requests go into a batch together. It does not simply take the next few pull requests in the queue. Instead, it groups pull requests that touch similar parts of your codebase, so each batch is a cohesive set of related changes. This makes batch failures cheaper to resolve: when a batch fails and has to be split, related changes stay together and unrelated pull requests aren’t dragged into someone else’s failure.

This is the default merge queue behavior (serial mode). Parallel mode groups pull requests strictly by scope instead. See Queue Modes.

Grouping applies these rules in order of precedence: it never overrides priority or queue order, it always keeps a stack together, and only then does similarity fill whatever batch slots remain. The sections below follow that order.

Grouping never overrides priority or queue order. Mergify seeds each batch with the pull request that is next to merge: the highest priority, and the oldest among equal priorities. Similarity only ever breaks ties between pull requests of equal priority: a lower-priority pull request is never pulled ahead of a higher-priority one just because it is similar. Higher-priority pull requests always fill the batch first; lower priorities are only considered once the batch still has room.

Stacks are the next firm rule, applied before similarity is considered. When a pull request depends on earlier ones still in the queue (a stack), Mergify keeps the whole stack in one batch: whenever a pull request joins a batch, its queued predecessors join with it, whether or not they share its scopes or changed directories.

This is why stack relationships take precedence over scope and directory similarity. A predecessor joins the batch because the dependency requires it, not because it ranked highly. The only limit is batch_size: if the stack doesn’t fit, the dependent pull request waits for a later batch rather than being tested without the changes it builds on.

Priority and stacks decide what a batch must contain. Similarity decides the rest: which of the remaining equal-priority pull requests fill the slots that are still free (up to batch_size). Mergify adds them one at a time, ranking every waiting candidate by three criteria applied in order, each one only breaking the ties the previous one leaves open:

1. Scopes. The pull requests that share the most scopes with the batch are the strongest match and are grouped together.

2. Changed directories. When scopes don’t separate two candidates, Mergify compares the directories each pull request changes and prefers the one touching the same areas of the repository. On very large monorepos it automatically compares broader areas (parent directories) rather than every individual folder, so grouping stays effective whatever the repository size.

3. Queue time. If two pull requests are still tied, the one that has been waiting longest joins the batch first, keeping first-in, first-out order.

Scopes always take precedence over directories; the changed directories only decide the grouping when scopes leave it open. In practice this depends on your configuration: if you have configured scopes, pull requests are grouped by scope and the directory signal stays out of the way. If you have not, every pull request reports no scope, so that signal is a tie for all of them and grouping falls back entirely to the directories they change.

Because of this, a pull request further down the queue may join an earlier batch when it is similar to what is already there, while a closer but unrelated pull request waits for the next batch:

Here the queue order is PR #1, #2, #3, #4. PR #3 changes the same area as PR #1 (api/), so it joins PR #1 in the first batch even though PR #2 was queued earlier. PR #2 and PR #4, which touch unrelated areas, fall into the next batch.

By default, Mergify creates temporary branches and batch PRs for testing batches. However, the original PRs are the ones merged, not these temporary branches. This ensures the integrity and traceability of the original pull requests.

However, there might be scenarios where you want to merge the temporary branches instead. One advantage of this is maintaining the same SHA1, which might be important for some workflows and for traceability.

Also, if you are deploying after a merge, this can also make sure that you trigger only a single deployment once a batch of pull request is fully tested and passes the CI.

There are two ways to merge the batch PR directly:

Set merge_method: fast-forward on your queue rule. When batching is enabled, Mergify creates the batch PR as usual, runs CI on it, and then fast-forwards the base branch to the batch PR’s head commit instead of merging the original PRs individually.

queue_rules:
  - name: default
    batch_size: 10
    merge_method: fast-forward

See Merge Strategies: Fast-Forward for a detailed explanation of how fast-forward works in both inplace and batch-PR modes.

Set merge_method: merge-batch on your queue rule. This merge method requires batch_size to be greater than 1. Mergify creates the batch PR as usual, runs CI on it, and then merges the batch PR into the base branch using the GitHub Pull Request merge API with a merge commit. The merge commit message lists all the pull requests included in the batch.

queue_rules:
  - name: default
    batch_size: 10
    merge_method: merge-batch

Unlike fast-forward, merge-batch uses the standard GitHub merge API, so it works with branch protection settings that require pull request merges — no bypass configuration is needed.

See Merge Strategies: Merge Batch for more details.

When a batch fails, or when the checks time out with the option checks_timeout on, Mergify does not remove all its pull requests from the queue. Instead, it takes additional steps to identify the problematic pull request and remove it from the queue.

This is how it works:

1. Splitting the batch: If a batch fails, all subsequent batches are deemed to fail as well, are canceled and put back into the queue. The system splits the failed batch to isolate the problematic pull request. The size of these new batches is determined by the max_parallel_checks parameter. By default, the batch is split into two; however, if max_parallel_checks is set to a value greater than 1, it dictates the number of batches the failed batch should be divided into.

2. Testing the new batches: After splitting, the first new batch is immediately retested, while others are queued. If max_parallel_checks is greater than 1, the system will also test subsequent batch split at the same time. This continues until the split is done.

3. Handling the result: If the first batch split succeeds, it is merged and the next split is scheduled for testing. If the batch fails, Mergify splits this batch, going back to step 1.

4. Pin-pointing the failed batch: If a batch contains only one pull request and still fails, it is deemed to be the culprit and is removed from the queue.

Note that this system is completely automatic and there is no need to intervene. The number of maximum splits can be controlled by batch_max_failure_resolution_attempts.

Let’s assume that we have a batch of 6 pull requests: [PR1 + PR2 + PR3 + PR4 + PR5 + PR6]. During the initial testing, Mergify first tests the batch with all 6 pull requests together.

As the batch fails, this could be due to any of the PRs or a specific combination of them. Mergify learned that the combination [PR1 + PR2 + PR3 + PR4 + PR5 + PR6] does not work; it now needs to test parts of this combination.

With max_parallel_checks set to 3, the system will aim to split the batch into 3 parts:

• First part: [PR1 + PR2]
• Second part: [PR1 + PR2 + PR3 + PR4]
• Third part: [PR1 + PR2 + PR3 + PR4 + PR5]

The system will immediately retest the different parts since the number of splits matches the number of parallel checks allowed.

If the first part [PR1 + PR2] passes, the system will merge it.

If the first part [PR1 + PR2] fails, the system will split it again and test each PR individually, applying the algorithm again.

If there’s a consecutive failure in the subsequent parts, the system will continue to split and isolate the problematic PR(s) and retest until the split contains a single pull request.

Mergify runs checks directly on the original pull request, instead of creating temporary batch PRs, only when all of the following are true:

• queue_rules[*].batch_size = 1

• merge_queue.max_parallel_checks = 1

• No two-step CI is configured (no separate merge_conditions beyond queue_conditions)

Optionally set update_bot_account to avoid in-place updates blocked by GitHub for security reasons (for example, PRs from forks that modify workflows, or PRs opened by other bots).

Flaky tests cause intermittent batch failures that block the queue. With skip_intermediate_results: true, Mergify stops requiring every intermediate batch to pass: if any passing batch contains a pull request’s changes, an earlier failing batch for that pull request is treated as transient and the pull request still merges.

merge_queue:
  skip_intermediate_results: true

This is safe because a real bug would also fail the larger batch that contains the same code; only flaky failures get bypassed. Enable it when your CI has some flakiness and you want to maximize throughput. Consider disabling it when you need every intermediate state validated for compliance, or while debugging CI and want to see all failures.

While using batch merging and parallel checks together can significantly speed up your merge queue processing, it’s crucial to consider the following points for an optimal setup:

Batches require the branch protection setting Require branches to be up to date before merging to be disabled. If your team requires a linear history, you can set the queue option merge_method: rebase.

For details on why and how to resolve this, see GitHub Rulesets Compatibility: Require Branches to Be Up to Date.

Remember that changes to PRs or the queue can disrupt the batch process. If a PR is updated or changed in a way that it no longer meets the queue_rules, it will be removed from the queue, and the order of checks will be updated. In such cases, the process resets, and the remaining PRs are rechecked in their new order.