How to fix Error: Error creating Batch Job Queue: ClientException in Terraform

TerraformINTERMEDIATEHIGH

AWS Batch ClientException errors when creating job queues typically indicate compute environment issues, IAM permissions, or VPC configuration problems. This guide covers the most common causes and step-by-step fixes.

What this error means

When creating an AWS Batch job queue through Terraform, a ClientException error means AWS Batch encountered a problem that prevents the job queue from being created. This is usually a validation error rather than a transient failure. The error occurs because the service detects an issue with your compute environment, IAM permissions, VPC configuration, or resource state. Unlike other errors, ClientException doesn't indicate a networking problem—it indicates that your configuration or AWS account state is invalid for creating the job queue.

How to fix "Error: Error creating Batch Job Queue: ClientException"

1Verify the compute environment exists and is in a valid state

First, check that your compute environment is created and ready. AWS Batch requires the compute environment to exist before you can reference it in a job queue.

hcl

resource "aws_batch_compute_environment" "example" {
  compute_environment_name = "my-compute-env"
  type                     = "MANAGED"
  state                    = "ENABLED"
  service_role            = aws_iam_role.batch_service_role.arn

  compute_resources {
    type           = "EC2"
    min_vcpus      = 0
    max_vcpus      = 256
    desired_vcpus  = 0
    instance_types = ["optimal"]
    subnets        = [aws_subnet.example.id]
    security_groups = [aws_security_group.example.id]
    instance_role  = aws_iam_instance_profile.batch_instance_role.arn
  }
}

In the AWS Console, navigate to Batch > Compute environments and verify your compute environment shows a status of VALID or DISABLED (not INVALID or UPDATE_FAILED). If it shows INVALID, you need to fix the compute environment configuration first before creating the job queue.

2Add an explicit dependency from job queue to compute environment

Terraform sometimes attempts to create resources in parallel. Add an explicit dependency to ensure the compute environment is fully created and initialized before the job queue is created.

hcl

resource "aws_batch_job_queue" "example" {
  name                 = "my-job-queue"
  state                = "ENABLED"
  priority             = 1
  compute_environments = [aws_batch_compute_environment.example.arn]

  # CRITICAL: Add this dependency
  depends_on = [aws_batch_compute_environment.example]
}

The depends_on directive forces Terraform to wait until the compute environment resource is completely created before attempting to create the job queue. This prevents race conditions that can trigger the ClientException.

3Verify IAM service role has required Batch permissions

The IAM service role attached to your compute environment must have the AWSBatchServiceRole policy attached. This policy grants Batch permission to create and manage EC2 instances and other resources.

hcl

data "aws_iam_policy_document" "batch_service_policy" {
  statement {
    actions = [
      "batch:*",
      "ec2:CreateNetworkInterface",
      "ec2:DescribeNetworkInterfaces",
      "ec2:DescribeVpcs",
      "ec2:DescribeSubnets",
      "ec2:DescribeSecurityGroups",
      "ec2:DescribeImages",
      "ec2:DescribeInstances",
      "ec2:RunInstances",
      "ec2:TerminateInstances",
      "iam:PassRole"
    ]
    resources = ["*"]
  }
}

resource "aws_iam_role" "batch_service_role" {
  name = "batch-service-role"

  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [
      {
        Action = "sts:AssumeRole"
        Effect = "Allow"
        Principal = {
          Service = "batch.amazonaws.com"
        }
      }
    ]
  })
}

resource "aws_iam_role_policy" "batch_service_policy" {
  name   = "batch-service-policy"
  role   = aws_iam_role.batch_service_role.id
  policy = data.aws_iam_policy_document.batch_service_policy.json
}

Ensure the role is properly attached to your compute environment in the service_role parameter.

4Check VPC and subnet configuration in compute environment

VPC issues in the compute environment prevent job queue creation. Verify that your subnets and security groups are properly configured.

hcl

resource "aws_batch_compute_environment" "example" {
  # ... other config ...

  compute_resources {
    # ... other config ...

    # Ensure subnets exist and have available IP addresses
    subnets = [
      aws_subnet.private_a.id,
      aws_subnet.private_b.id
    ]

    # Security group must allow outbound HTTPS (port 443) for ECR image pulls
    security_groups = [aws_security_group.batch_sg.id]

    instance_role = aws_iam_instance_profile.batch_instance_role.arn
  }
}

resource "aws_security_group" "batch_sg" {
  name        = "batch-sg"
  description = "Security group for Batch compute environment"
  vpc_id      = aws_vpc.example.id

  egress {
    from_port   = 443
    to_port     = 443
    protocol    = "tcp"
    cidr_blocks = ["0.0.0.0/0"]
    description = "Allow HTTPS to ECR and AWS services"
  }

  egress {
    from_port   = 80
    to_port     = 80
    protocol    = "tcp"
    cidr_blocks = ["0.0.0.0/0"]
    description = "Allow HTTP"
  }
}

Verify that your subnets have available IP addresses and that security groups allow necessary outbound traffic.

5Ensure job queue has required attributes (state and priority)

The job queue must explicitly include the state and priority attributes. Missing these triggers a ClientException.

hcl

resource "aws_batch_job_queue" "example" {
  name                 = "my-job-queue"
  state                = "ENABLED"    # REQUIRED: ENABLED or DISABLED
  priority             = 1            # REQUIRED: Integer priority value
  compute_environments = [
    aws_batch_compute_environment.example.arn
  ]
}

The priority field determines the order in which Batch evaluates job queues when scheduling jobs. Higher priority values are evaluated first.

6Add a delay if compute environment initialization takes time

In rare cases where compute environment initialization takes longer than expected, add a time-based dependency.

hcl

resource "time_sleep" "wait_for_compute_env" {
  depends_on      = [aws_batch_compute_environment.example]
  create_duration = "30s"
}

resource "aws_batch_job_queue" "example" {
  name                 = "my-job-queue"
  state                = "ENABLED"
  priority             = 1
  compute_environments = [aws_batch_compute_environment.example.arn]

  depends_on = [time_sleep.wait_for_compute_env]
}

This introduces a 30-second delay after the compute environment is created, allowing AWS Batch to fully initialize it before the job queue is created. Remove this if the basic dependency fix works.

How to fix Error: Error creating Batch Job Queue: ClientException in Terraform

What this error means

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How to fix "Error: Error creating Batch Job Queue: ClientException"

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