Highlights#
Tower 21.06.x brings the following changes:
- Add Support for AWS Host credentials and role-base permissions
- Add Support for AWS EFS storage
- Add ability to specify custom AWS cli path
- Add AWS regions eu-south-1 and af-south-1
- Add uploadChunkSize configuration parameter to abstract k8 provider (#1820)
- Limit compute env error message length
- Invalidate compute envs associated to deleted credentials
- Fix launch form pipelineParameters after navigating to pipeline input form (#1847)
- Fix error report for missing invalid/creds
- Fix GitHub action creation
- Fix Prevent GH delete action hook exception
- Display team id in team page
- Disable index.html caching in nginx.config
- Bump nextflow launcher 21.04.3
- Bump groovy 3.0.8
Updating Tower deployment from version 21.04.x to 21.06.x#
NOTE: If you are upgrading from a verion prior to 21.04.x
, update your installation to tower 21.04.0
, before installing this release.
License key#
As of version 21.02.x
, a license key must be provided to enable the Tower deployment feature. The license key should be specified using the configuration variable TOWER_LICENSE. If you don't have a license key, contact sales@seqera.io.
Compute environments#
The Tower compute environments to be made available to users must be specified in the Tower configuration.
The following ids options are available:
awsbatch-platform
: AWS Batch cloud compute servicegls-platform
: Google LifeSciences cloud compute serviceazbatch-platform
: Azure Batch cloud compute servicelsf-platform
: IBM LSF batch schedulerslurm-platform
: Slurm batch scheduleraltair-platform
: Altair PBS Pro batch scheduleruniva-platform
: (Univa/Sun) GridEnginek8s-platform
: Kubernetes compute platformeks-platform
: AWS EKS compute platformgke-platform
: Google GKE compute platform
Choose one or more of these platform ids and append to your current MICRONAUT_ENVIRONMENTS
variable, separating them via a comma ,
.
Database schema#
This Tower version requires a database schema update. Follow these steps to update your DB instance and the Tower installation.
Docker compose deployment#
1. Make a backup of the Tower database.
2. Update the docker-compose.yml
file with the following container images:
1 2 |
|
If you are using AWS Batch with a custom launcher job definition you need to update it to use the following container images (please refer the configuration section for details):
1 |
|
3. Restart the service using the command docker-compose restart
.
Kubernetes based deployment#
1. Make a backup of the Tower database.
2. Update the Tower container images in the Kubernetes manifest yaml files to:
1 2 |
|
If you are using AWS Batch with a custom launcher job definition you need to update it to use the following container image (please refer the configuration section for details):
1 |
|
Refer to the manifests included in the K8s instalation section for details.
3. Update the Tower cron service using the following:
1 |
|
Note
This task will automatically run the Tower database schema update tool.
4. Update the Tower backend and frontend services using the following command:
1 |
|
Custom deployment script#
1. Make a backup of the Tower database.
2. Pull or update the Tower container images references in your deployment script(s) to:
1 2 |
|
If you are using AWS Batch with a custom launcher job definition you need to update it to use the following container image (please refer the configuration section for details):
1 |
|
3. Update the Tower database schema by running the /migrate-db.sh
provided in the backend container.
Note
Make sure to include the identical environment as used in the normal backend execution.
4. Once the schema update completes, deploy Tower following your usual procedure.
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