release: Terraform Provider 0.30.2 #155
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Speakeasy Lint Results: 0 errors, 34 warnings, 1766 hintsClick to expand lint outputLint completed at: Mon Feb 2 11:37:43 UTC 2026 |
Terraform Plan:Click to expand terraform planTerraform used the selected providers to generate the following execution
plan. Resource actions are indicated with the following symbols:
+ create
Terraform will perform the following actions:
# seqera_orgs.test_org will be created
+ resource "seqera_orgs" "test_org" {
+ description = "testing org for the terraform provider"
+ full_name = "seqera_test_shahbaz_tf_provider"
+ location = (known after apply)
+ member_id = (known after apply)
+ member_role = (known after apply)
+ name = "seqera_test_shahbaz_tf_provider"
+ org_id = (known after apply)
+ website = (known after apply)
}
# seqera_teams.my_teams will be created
+ resource "seqera_teams" "my_teams" {
+ avatar_url = (known after apply)
+ description = "Team created by Terraform"
+ members_count = (known after apply)
+ name = "terraform-test-team"
+ org_id = (known after apply)
+ team_id = (known after apply)
}
# seqera_workspace.my_workspace will be created
+ resource "seqera_workspace" "my_workspace" {
+ date_created = (known after apply)
+ description = "A test workspace created with Terraform"
+ full_name = "Test Workspace for Terraform Provider"
+ id = (known after apply)
+ last_updated = (known after apply)
+ name = "test-workspace-tf"
+ org_id = (known after apply)
+ visibility = "PRIVATE"
}
# module.aws_batch.seqera_action.my_action will be created
+ resource "seqera_action" "my_action" {
+ action_id = (known after apply)
+ config = (known after apply)
+ hook_id = (known after apply)
+ hook_url = (known after apply)
+ id = (known after apply)
+ launch = {
+ compute_env_id = (known after apply)
+ config_profiles = []
+ config_text = ""
+ entry_name = (known after apply)
+ head_job_cpus = (known after apply)
+ head_job_memory_mb = (known after apply)
+ id = (known after apply)
+ launch_container = (known after apply)
+ main_script = (known after apply)
+ optimization_id = (known after apply)
+ optimization_targets = (known after apply)
+ params_text = (known after apply)
+ pipeline = "https://github.com/nf-core/sarek"
+ post_run_script = <<-EOT
#!/bin/bash
echo "Workflow execution completed!"
# Add any cleanup commands here
EOT
+ pre_run_script = <<-EOT
#!/bin/bash
echo "Starting workflow execution..."
# Add any setup commands here
EOT
+ pull_latest = true
+ resume = true
+ resume_launch_id = (known after apply)
+ revision = "master"
+ run_name = (known after apply)
+ schema_name = (known after apply)
+ session_id = (known after apply)
+ stub_run = (known after apply)
+ tower_config = (known after apply)
+ user_secrets = (known after apply)
+ work_dir = "s3://shahbaz-test"
+ workspace_id = (known after apply)
+ workspace_secrets = (known after apply)
}
+ message = (known after apply)
+ name = "terraform-hello-world-action"
+ source = "tower"
+ status = (known after apply)
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_aws_compute_env.aws_batch_compute_env_dedicated will be created
+ resource "seqera_aws_compute_env" "aws_batch_compute_env_dedicated" {
+ compute_env_id = (known after apply)
+ config = {
+ cli_path = (known after apply)
+ compute_job_role = (known after apply)
+ compute_queue = (known after apply)
+ dragen_instance_type = (known after apply)
+ dragen_queue = (known after apply)
+ enable_fusion = (known after apply)
+ enable_wave = (known after apply)
+ environment = (known after apply)
+ execution_role = (known after apply)
+ forge = {
+ alloc_strategy = "BEST_FIT_PROGRESSIVE"
+ allow_buckets = (known after apply)
+ arm64_enabled = false
+ bid_percentage = (known after apply)
+ dispose_on_deletion = true
+ dragen_ami_id = (known after apply)
+ dragen_enabled = (known after apply)
+ dragen_instance_type = (known after apply)
+ ebs_auto_scale = false
+ ebs_block_size = (known after apply)
+ ebs_boot_size = (known after apply)
+ ec2_key_pair = (known after apply)
+ ecs_config = (known after apply)
+ efs_create = (known after apply)
+ efs_id = (known after apply)
+ efs_mount = (known after apply)
+ fargate_head_enabled = (known after apply)
+ fsx_mount = (known after apply)
+ fsx_name = (known after apply)
+ fsx_size = (known after apply)
+ gpu_enabled = false
+ image_id = (known after apply)
+ instance_types = [
+ "m5.large",
+ "m5.xlarge",
+ "m5.2xlarge",
]
+ max_cpus = 1000
+ min_cpus = 0
+ security_groups = (known after apply)
+ subnets = (known after apply)
+ type = "EC2"
+ vpc_id = (known after apply)
}
+ fusion_snapshots = (known after apply)
+ head_job_cpus = 2
+ head_job_memory_mb = 4096
+ head_job_role = (known after apply)
+ head_queue = (known after apply)
+ log_group = (known after apply)
+ lustre_id = (known after apply)
+ nextflow_config = (known after apply)
+ nvme_storage_enabled = (known after apply)
+ post_run_script = (known after apply)
+ pre_run_script = (known after apply)
+ region = "us-east-1"
+ storage_type = (known after apply)
+ volumes = (known after apply)
+ work_dir = "s3://shahbaz-test"
}
+ credentials_id = (known after apply)
+ date_created = (known after apply)
+ deleted = (known after apply)
+ id = (known after apply)
+ last_updated = (known after apply)
+ last_used = (known after apply)
+ name = "aws-batch-dedicated"
+ org_id = (known after apply)
+ platform = "aws-batch"
+ status = (known after apply)
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_aws_credential.aws_credential will be created
+ resource "seqera_aws_credential" "aws_credential" {
+ access_key = (sensitive value)
+ assume_role_arn = "arn:aws:iam::128997144437:role/TowerDevelopmentRole"
+ credentials_id = (known after apply)
+ id = (known after apply)
+ name = "test_aws_credential"
+ provider_type = "aws"
+ secret_key = (sensitive value)
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_compute_env.aws_batch_compute_env will be created
+ resource "seqera_compute_env" "aws_batch_compute_env" {
+ compute_env = {
+ compute_env_id = (known after apply)
+ config = {
+ aws_batch = {
+ cli_path = (known after apply)
+ compute_job_role = (known after apply)
+ compute_queue = (known after apply)
+ dragen_instance_type = (known after apply)
+ dragen_queue = (known after apply)
+ enable_fusion = (known after apply)
+ enable_wave = (known after apply)
+ environment = (known after apply)
+ execution_role = (known after apply)
+ forge = {
+ alloc_strategy = "BEST_FIT_PROGRESSIVE"
+ allow_buckets = (known after apply)
+ arm64_enabled = false
+ bid_percentage = (known after apply)
+ dispose_on_deletion = true
+ dragen_ami_id = (known after apply)
+ dragen_enabled = (known after apply)
+ dragen_instance_type = (known after apply)
+ ebs_auto_scale = false
+ ebs_block_size = (known after apply)
+ ebs_boot_size = (known after apply)
+ ec2_key_pair = (known after apply)
+ ecs_config = (known after apply)
+ efs_create = (known after apply)
+ efs_id = (known after apply)
+ efs_mount = (known after apply)
+ fargate_head_enabled = (known after apply)
+ fsx_mount = (known after apply)
+ fsx_name = (known after apply)
+ fsx_size = (known after apply)
+ gpu_enabled = false
+ image_id = (known after apply)
+ instance_types = [
+ "m5.large",
+ "m5.xlarge",
+ "m5.2xlarge",
]
+ max_cpus = 1000
+ min_cpus = 0
+ security_groups = (known after apply)
+ subnets = (known after apply)
+ type = "EC2"
+ vpc_id = (known after apply)
}
+ fusion_snapshots = (known after apply)
+ head_job_cpus = 2
+ head_job_memory_mb = 4096
+ head_job_role = (known after apply)
+ head_queue = (known after apply)
+ log_group = (known after apply)
+ lustre_id = (known after apply)
+ nextflow_config = (known after apply)
+ nvme_storage_enabled = (known after apply)
+ post_run_script = <<-EOT
#!/bin/bash
echo "Workflow execution completed!"
# Add any cleanup commands here
EOT
+ pre_run_script = <<-EOT
#!/bin/bash
echo "Starting workflow execution..."
# Add any setup commands here
EOT
+ region = "us-east-1"
+ storage_type = (known after apply)
+ volumes = (known after apply)
+ work_dir = "s3://shahbaz-test"
}
}
+ credentials_id = (known after apply)
+ date_created = (known after apply)
+ deleted = (known after apply)
+ description = "AWS Batch compute environment for bioinformatics workflows"
+ labels = (known after apply)
+ last_updated = (known after apply)
+ last_used = (known after apply)
+ managed_identity_id = (known after apply)
+ message = (known after apply)
+ name = "aws-batch-compute-env"
+ org_id = (known after apply)
+ platform = "aws-batch"
+ primary = (known after apply)
+ resources = (known after apply)
+ status = (known after apply)
+ workspace_id = (known after apply)
}
+ compute_env_id = (known after apply)
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_data_link.my_datalink will be created
+ resource "seqera_data_link" "my_datalink" {
+ credentials = (known after apply)
+ credentials_id = (known after apply)
+ data_link_id = (known after apply)
+ description = "data link created by Terraform"
+ hidden = (known after apply)
+ message = (known after apply)
+ name = "terraform-datalink"
+ provider_type = "aws"
+ public_accessible = false
+ region = (known after apply)
+ resource_ref = "s3://shahbaz-test"
+ status = (known after apply)
+ type = "bucket"
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_datasets.my_datasets will be created
+ resource "seqera_datasets" "my_datasets" {
+ description = "Terraform created dataset"
+ id = (known after apply)
+ last_updated = (known after apply)
+ media_type = (known after apply)
+ name = "terraform-dataset"
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_labels.my_labels will be created
+ resource "seqera_labels" "my_labels" {
+ is_default = false
+ label_id = (known after apply)
+ name = "terraform-test-label"
+ resource = true
+ value = "terraform-label-value"
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_pipeline.hello_world_minimal will be created
+ resource "seqera_pipeline" "hello_world_minimal" {
+ description = "Hello world pipeline generated by terraform"
+ icon = (known after apply)
+ launch = {
+ compute_env_id = (known after apply)
+ config_profiles = []
+ head_job_cpus = 6
+ pipeline = "https://github.com/nextflow-io/hello"
+ pull_latest = true
+ resume = false
+ revision = "master"
+ work_dir = "s3://shahbaz-test"
}
+ name = "terraform-hello-world"
+ pipeline_id = (known after apply)
+ repository = (known after apply)
+ user_first_name = (known after apply)
+ user_id = (known after apply)
+ user_name = (known after apply)
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_pipeline_secret.my_pipelinesecret will be created
+ resource "seqera_pipeline_secret" "my_pipelinesecret" {
+ date_created = (known after apply)
+ id = (known after apply)
+ last_updated = (known after apply)
+ last_used = (known after apply)
+ name = "test_terraform_secret"
+ secret_id = (known after apply)
+ value = (sensitive value)
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_primary_compute_env.my_primarycomputeenv will be created
+ resource "seqera_primary_compute_env" "my_primarycomputeenv" {
+ compute_env_id = (known after apply)
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_studios.my_datastudios will be created
+ resource "seqera_studios" "my_datastudios" {
+ compute_env_id = (known after apply)
+ configuration = {
+ conda_environment = (known after apply)
+ cpu = 2
+ environment = (known after apply)
+ gpu = 0
+ lifespan_hours = (known after apply)
+ memory = 8192
+ mount_data = (known after apply)
}
+ data_studio_tool_url = "public.cr.seqera.io/platform/data-studio-jupyter:4.2.5-0.8"
+ description = "Data studio"
+ is_private = (known after apply)
+ name = "Terraform-Data-Studio"
+ session_id = (known after apply)
+ workspace_id = (known after apply)
}
# module.aws_batch.seqera_workflows.my_workflows will be created
+ resource "seqera_workflows" "my_workflows" {
+ compute_env_id = (known after apply)
+ pipeline = "nextflow-io/hello"
+ work_dir = "s3://shahbaz-test"
+ workflow = (known after apply)
+ workflow_id = (known after apply)
+ workspace_id = (known after apply)
}
# module.azure_batch.seqera_azure_credential.azure_credential will be created
+ resource "seqera_azure_credential" "azure_credential" {
+ batch_key = (sensitive value)
+ batch_name = "seqeralabs"
+ credentials_id = (known after apply)
+ id = (known after apply)
+ name = "azure_credential"
+ provider_type = "azure"
+ storage_key = (sensitive value)
+ storage_name = "seqeralabs"
+ workspace_id = (known after apply)
}
# module.azure_batch.seqera_compute_env.azure_batch_compute_env will be created
+ resource "seqera_compute_env" "azure_batch_compute_env" {
+ compute_env = {
+ compute_env_id = (known after apply)
+ config = {
+ azure_batch = {
+ auto_pool_mode = (known after apply)
+ delete_jobs_on_completion = (known after apply)
+ delete_pools_on_completion = (known after apply)
+ enable_fusion = (known after apply)
+ enable_wave = (known after apply)
+ environment = (known after apply)
+ forge = {
+ auto_scale = (known after apply)
+ container_reg_ids = (known after apply)
+ dispose_on_deletion = (known after apply)
+ vm_count = 1
+ vm_type = (known after apply)
}
+ head_pool = (known after apply)
+ managed_identity_client_id = (known after apply)
+ nextflow_config = (known after apply)
+ post_run_script = (known after apply)
+ pre_run_script = (known after apply)
+ region = "eastus"
+ token_duration = (known after apply)
+ work_dir = "az://terraform-provider"
}
}
+ credentials_id = (known after apply)
+ date_created = (known after apply)
+ deleted = (known after apply)
+ description = "azure Batch compute environment"
+ labels = (known after apply)
+ last_updated = (known after apply)
+ last_used = (known after apply)
+ managed_identity_id = (known after apply)
+ message = (known after apply)
+ name = "azure-batch-compute-env-terraform"
+ org_id = (known after apply)
+ platform = "azure-batch"
+ primary = (known after apply)
+ resources = (known after apply)
+ status = (known after apply)
+ workspace_id = (known after apply)
}
+ compute_env_id = (known after apply)
+ workspace_id = (known after apply)
}
# module.azure_batch.seqera_pipeline.hello_world_minimal will be created
+ resource "seqera_pipeline" "hello_world_minimal" {
+ description = "Hello world pipeline generated by terraform"
+ icon = (known after apply)
+ launch = {
+ compute_env_id = (known after apply)
+ config_profiles = []
+ head_job_cpus = 6
+ pipeline = "https://github.com/nextflow-io/hello"
+ pull_latest = true
+ resume = false
+ revision = "master"
+ work_dir = "az://terraform-provider"
}
+ name = "terraform-hello-world-azure"
+ pipeline_id = (known after apply)
+ repository = (known after apply)
+ user_first_name = (known after apply)
+ user_id = (known after apply)
+ user_name = (known after apply)
+ workspace_id = (known after apply)
}
# module.azure_batch.seqera_workflows.my_workflows will be created
+ resource "seqera_workflows" "my_workflows" {
+ compute_env_id = (known after apply)
+ pipeline = "nextflow-io/hello"
+ work_dir = "az://terraform-provider"
+ workflow = (known after apply)
+ workflow_id = (known after apply)
+ workspace_id = (known after apply)
}
Plan: 19 to add, 0 to change, 0 to destroy.Plan generated at: Mon Feb 2 11:37:53 UTC 2026 |
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The following preps the 0.30.2 release