This PR sunset the Google LS executor

Signed-off-by: Paolo Di Tommaso <[email protected]>

Author: pditommaso

docs/executor.md

@@ -144,33 +144,6 @@ Resource requests and other job characteristics can be controlled via the follow
 
 See the {ref}`Google Cloud Batch <google-batch>` page for further configuration details.
 
-(google-lifesciences-executor)=
-
-## Google Life Sciences
-
-:::{versionadded} 20.01.0
-:::
-
-[Google Cloud Life Sciences](https://cloud.google.com/life-sciences) is a managed computing service that allows the execution of containerized workloads in the Google Cloud Platform infrastructure.
-
-Nextflow provides built-in support for the Life Sciences API, which allows the seamless deployment of a Nextflow pipeline in the cloud, offloading the process executions as pipelines.
-
-The pipeline processes must specify the Docker image to use by defining the `container` directive, either in the pipeline script or the `nextflow.config` file. Additionally, the pipeline work directory must be located in a Google Storage bucket.
-
-To enable this executor, set `process.executor = 'google-lifesciences'` in the `nextflow.config` file.
-
-Resource requests and other job characteristics can be controlled via the following process directives:
-
-- {ref}`process-accelerator`
-- {ref}`process-cpus`
-- {ref}`process-disk`
-- {ref}`process-machineType`
-- {ref}`process-memory`
-- {ref}`process-resourcelabels`
-- {ref}`process-time`
-
-See the {ref}`Google Life Sciences <google-lifesciences>` page for further configuration details.
-
 (htcondor-executor)=
 
 ## HTCondor

docs/google.md

@@ -4,7 +4,7 @@
 
 ## Credentials
 
-Credentials for submitting requests to the Google Cloud Batch and Cloud LifeSciences API are picked up from your environment using [Application Default Credentials](https://github.com/googleapis/google-auth-library-java#google-auth-library-oauth2-http). Application Default Credentials are designed to use the credentials most natural to the environment in which a tool runs.
+Credentials for submitting requests to the Google Cloud Batch API are picked up from your environment using [Application Default Credentials](https://github.com/googleapis/google-auth-library-java#google-auth-library-oauth2-http). Application Default Credentials are designed to use the credentials most natural to the environment in which a tool runs.
 
 The most common case will be to pick up your end-user Google credentials from your workstation. You can create these by running the command:
 
@@ -250,160 +250,23 @@ Currently, the following Nextflow directives are supported by the Google Batch e
 - {ref}`process-memory`
 - {ref}`process-time`
 
-(google-lifesciences)=
-
-## Cloud Life Sciences
-
-:::{versionadded} 20.01.0-edge
-:::
-
-:::{note}
-In versions of Nextflow prior to `21.04.0`, the following variables must be defined in your system environment:
-
-```bash
-export NXF_VER=20.01.0
-export NXF_MODE=google
-```
-:::
-
-[Cloud Life Sciences](https://cloud.google.com/life-sciences/) is a managed computing service that allows the execution of containerized workloads in the Google Cloud Platform infrastructure.
-
-Nextflow provides built-in support for Cloud Life Sciences, allowing the seamless deployment of Nextflow pipelines in the cloud, in which tasks are offloaded to the Cloud Life Sciences service.
-
-Read the {ref}`Google Life Sciences executor <google-lifesciences-executor>` page to learn about the `google-lifesciences` executor in Nextflow.
-
-:::{warning}
-This API works well for coarse-grained workloads (i.e. long-running jobs). It's not suggested the use this feature for pipelines spawning many short lived tasks.
-:::
-
-(google-lifesciences-config)=
-
-### Configuration
-
-Make sure to have defined in your environment the `GOOGLE_APPLICATION_CREDENTIALS` variable. See the section [Credentials](#credentials) for details.
-
-:::{tip}
-Make sure to enable the Cloud Life Sciences API beforehand. To learn how to enable it follow [this link](https://cloud.google.com/life-sciences/docs/quickstart).
-:::
-
-Create a `nextflow.config` file in the project root directory. The config must specify the following parameters:
-
-- Google Life Sciences as Nextflow executor
-- The Docker container image(s) for pipeline tasks
-- The Google Cloud project ID
-- The Google Cloud region or zone where the Compute Engine VMs will be executed.
-  You need to specify one or the other, *not* both. Multiple regions or zones can be specified as a comma-separated list, e.g. `google.zone = 'us-central1-f,us-central-1-b'`.
-
-Example:
-
-```groovy
-process {
-    executor = 'google-lifesciences'
-    container = 'your/container:latest'
-}
-
-google {
-    project = 'your-project-id'
-    zone = 'europe-west1-b'
-}
-```
-
-Notes:
-- A container image must be specified to execute processes. You can use a different Docker image for each process using one or more {ref}`config-process-selectors`.
-- Make sure to specify the project ID, not the project name.
-- Make sure to specify a location where Google Life Sciences is available. Refer to the [Google Cloud documentation](https://cloud.google.com/life-sciences/docs/concepts/locations) for details.
-
-Read the {ref}`Google configuration<config-google>` section to learn more about advanced configuration options.
-
-### Process definition
-
-Processes can be defined as usual and by default the `cpus` and `memory` directives are used to instantiate a custom machine type with the specified compute resources. If `memory` is not specified, 1GB of memory is allocated per cpu. A persistent disk will be created with size corresponding to the `disk` directive. If `disk` is not specified, the instance default is chosen to ensure reasonable I/O performance.
-
-The process `machineType` directive may optionally be used to specify a predefined Google Compute Platform [machine type](https://cloud.google.com/compute/docs/machine-types) If specified, this value overrides the `cpus` and `memory` directives. If the `cpus` and `memory` directives are used, the values must comply with the allowed custom machine type [specifications](https://cloud.google.com/compute/docs/instances/creating-instance-with-custom-machine-type#specifications) . Extended memory is not directly supported, however high memory or cpu predefined instances may be utilized using the `machineType` directive
-
-Examples:
-
-```nextflow
-process custom_resources_task {
-    cpus 8
-    memory '40 GB'
-    disk '200 GB'
-
-    script:
-    """
-    your_command --here
-    """
-}
-
-process predefined_resources_task {
-    machineType 'n1-highmem-8'
-
-    script:
-    """
-    your_command --here
-    """
-}
-```
-
-### Pipeline execution
-
-The pipeline can be launched either in a local computer or a cloud instance. Pipeline input data can be stored either locally or in a Google Storage bucket.
-
-The pipeline execution must specify a Google Storage bucket where the workflow's intermediate results are stored using the `-work-dir` command line options. For example:
-
-```bash
-nextflow run <script or project name> -work-dir gs://my-bucket/some/path
-```
-
-:::{tip}
-Any input data *not* stored in a Google Storage bucket will be automatically transferred to the pipeline work bucket. Use this feature with caution, being careful to avoid unnecessary data transfers.
-:::
-
-### Preemptible instances
-
-Preemptible instances are supported adding the following setting in the Nextflow config file:
-
-```groovy
-google {
-    lifeSciences.preemptible = true
-}
-```
-
-Since this type of virtual machines can be retired by the provider before the job completion, it is advisable to add the following retry strategy to your config file to instruct Nextflow to automatically re-execute a job if the virtual machine was terminated preemptively:
-
-```groovy
-process {
-    errorStrategy = { task.exitStatus==14 ? 'retry' : 'terminate' }
-    maxRetries = 5
-}
-```
-
-:::{note}
-Preemptible instances have a [runtime limit](https://cloud.google.com/compute/docs/instances/preemptible) of 24 hours.
-:::
-
-:::{tip}
-For an exhaustive list of error codes, refer to the official Google Life Sciences [documentation](https://cloud.google.com/life-sciences/docs/troubleshooting#error_codes).
-:::
-
 ### Hybrid execution
 
-Nextflow allows the use of multiple executors in the same workflow. This feature enables the deployment of hybrid workloads, in which some jobs are executed in the local computer or local computing cluster, and some jobs are offloaded to Google Cloud (either Google Batch or Google Life Sciences).
+Nextflow allows the use of multiple executors in the same workflow. This feature enables the deployment of hybrid workloads, in which some jobs are executed in the local computer or local computing cluster, and some jobs are offloaded to Google Cloud.
 
 To enable this feature, use one or more {ref}`config-process-selectors` in your Nextflow configuration file to apply the Google Cloud executor to the subset of processes that you want to offload. For example:
 
 ```groovy
 process {
     withLabel: bigTask {
-        executor = 'google-batch' // or 'google-lifesciences'
+        executor = 'google-batch'
         container = 'my/image:tag'
     }
 }
 
 google {
     project = 'your-project-id'
     location = 'us-central1' // for Google Batch
-    // zone = 'us-central1-a' // for Google Life Sciences
 }
 ```
 
@@ -427,16 +290,3 @@ Nextflow will automatically manage the transfer of input and output files betwee
 
 - Currently, it's not possible to specify a disk type different from the default one assigned by the service depending on the chosen instance type.
 
-### Troubleshooting
-
-- Make sure to enable the Compute Engine API, Life Sciences API and Cloud Storage API in the [APIs & Services Dashboard](https://console.cloud.google.com/apis/dashboard) page.
-
-- Make sure to have enough compute resources to run your pipeline in your project [Quotas](https://console.cloud.google.com/iam-admin/quotas) (i.e. Compute Engine CPUs, Compute Engine Persistent Disk, Compute Engine In-use IP addresses, etc).
-
-- Make sure your security credentials allow you to access any Google Storage bucket where input data and temporary files are stored.
-
-- When a job fails, you can check the `google/` directory in the task work directory (in the bucket storage), which contains useful information about the job execution. To enable the creation of this directory, set `google.lifeSciences.debug = true` in the Nextflow config.
-
-- You can enable the optional SSH daemon in the job VM by setting `google.lifeSciences.sshDaemon = true` in the Nextflow config.
-
-- Make sure you are choosing a `location` where the [Cloud Life Sciences API is available](https://cloud.google.com/life-sciences/docs/concepts/locations), and a `region` or `zone` where the [Compute Engine API is available](https://cloud.google.com/compute/docs/regions-zones/).

docs/reference/config.md

@@ -816,7 +816,7 @@ The following settings are available:
 
 ## `google`
 
-The `google` scope allows you to configure the interactions with Google Cloud, including Google Cloud Batch, Google Life Sciences, and Google Cloud Storage.
+The `google` scope allows you to configure the interactions with Google Cloud, including Google Cloud Batch and Google Cloud Storage.
 
 Read the {ref}`google-page` page for more information.
 
@@ -956,52 +956,6 @@ The following settings are available for Cloud Life Sciences:
 `google.zone`
 : The Google Cloud zone where jobs are executed. Multiple zones can be provided as a comma-separated list. Cannot be used with the `google.region` option. See the [Google Cloud documentation](https://cloud.google.com/compute/docs/regions-zones/) for a list of available regions and zones.
 
-`google.lifeSciences.bootDiskSize`
-: Set the size of the virtual machine boot disk e.g `50.GB` (default: none).
-
-`google.lifeSciences.copyImage`
-: The container image run to copy input and output files. It must include the `gsutil` tool (default: `google/cloud-sdk:alpine`).
-
-`google.lifeSciences.cpuPlatform`
-: Set the minimum CPU Platform e.g. `'Intel Skylake'`. See [Specifying a minimum CPU Platform for VM instances](https://cloud.google.com/compute/docs/instances/specify-min-cpu-platform#specifications) (default: none).
-
-`google.lifeSciences.debug`
-: When `true` copies the `/google` debug directory in that task bucket directory (default: `false`).
-
-`google.lifeSciences.keepAliveOnFailure`
-: :::{versionadded} 21.06.0-edge
-  :::
-: When `true` and a task complete with an unexpected exit status the associated compute node is kept up for 1 hour. This options implies `sshDaemon=true` (default: `false`).
-
-`google.lifeSciences.network`
-: :::{versionadded} 21.03.0-edge
-  :::
-: Set network name to attach the VM's network interface to. The value will be prefixed with `global/networks/` unless it contains a `/`, in which case it is assumed to be a fully specified network resource URL. If unspecified, the global default network is used.
-
-`google.lifeSciences.preemptible`
-: When `true` enables the usage of *preemptible* virtual machines or `false` otherwise (default: `true`).
-
-`google.lifeSciences.serviceAccountEmail`
-: :::{versionadded} 20.05.0-edge
-  :::
-: Define the Google service account email to use for the pipeline execution. If not specified, the default Compute Engine service account for the project will be used.
-
-`google.lifeSciences.subnetwork`
-: :::{versionadded} 21.03.0-edge
-  :::
-: Define the name of the subnetwork to attach the instance to must be specified here, when the specified network is configured for custom subnet creation. The value is prefixed with `regions/subnetworks/` unless it contains a `/`, in which case it is assumed to be a fully specified subnetwork resource URL.
-
-`google.lifeSciences.sshDaemon`
-: When `true` runs SSH daemon in the VM carrying out the job to which it's possible to connect for debugging purposes (default: `false`).
-
-`google.lifeSciences.sshImage`
-: The container image used to run the SSH daemon (default: `gcr.io/cloud-genomics-pipelines/tools`).
-
-`google.lifeSciences.usePrivateAddress`
-: :::{versionadded} 20.03.0-edge
-  :::
-: When `true` the VM will NOT be provided with a public IP address, and only contain an internal IP. If this option is enabled, the associated job can only load docker images from Google Container Registry, and the job executable cannot use external services other than Google APIs (default: `false`).
-
 `google.storage.delayBetweenAttempts`
 : :::{versionadded} 21.06.0-edge
   :::

docs/reference/process.md

@@ -520,7 +520,7 @@ process runThisWithDocker {
 ```
 
 :::{warning}
-This feature is not supported by the {ref}`k8s-executor` and {ref}`google-lifesciences-executor` executors.
+This feature is not supported by the {ref}`k8s-executor` executor.
 :::
 
 (process-cpus)=
@@ -682,7 +682,6 @@ The following executors are available:
 | `awsbatch`            | [AWS Batch](https://aws.amazon.com/batch/) service                                          |
 | `azurebatch`          | [Azure Batch](https://azure.microsoft.com/en-us/services/batch/) service                    |
 | `condor`              | [HTCondor](https://research.cs.wisc.edu/htcondor/) job scheduler                            |
-| `google-lifesciences` | [Google Genomics Pipelines](https://cloud.google.com/life-sciences) service                 |
 | `k8s`                 | [Kubernetes](https://kubernetes.io/) cluster                                                |
 | `local`               | The computer where `Nextflow` is launched                                                   |
 | `lsf`                 | [Platform LSF](http://en.wikipedia.org/wiki/Platform_LSF) job scheduler                     |
@@ -821,7 +820,7 @@ See also: [resourceLabels](#resourcelabels)
 :::{versionadded} 19.07.0
 :::
 
-The `machineType` can be used to specify a predefined Google Compute Platform [machine type](https://cloud.google.com/compute/docs/machine-types) when running using the {ref}`Google Batch <google-batch-executor>` or {ref}`Google Life Sciences <google-lifesciences-executor>` executor, or when using the autopools feature of the {ref}`Azure Batch executor<azurebatch-executor>`.
+The `machineType` can be used to specify a predefined Google Compute Platform [machine type](https://cloud.google.com/compute/docs/machine-types) when running using the {ref}`Google Batch <google-batch-executor>`, or when using the autopools feature of the {ref}`Azure Batch executor<azurebatch-executor>`.
 
 This directive is optional and if specified overrides the cpus and memory directives:
 
@@ -1379,7 +1378,6 @@ Resource labels are currently supported by the following executors:
 - {ref}`awsbatch-executor`
 - {ref}`azurebatch-executor`
 - {ref}`google-batch-executor`
-- {ref}`google-lifesciences-executor`
 - {ref}`k8s-executor`
 
 :::{versionadded} 23.09.0-edge

plugins/nf-google/build.gradle

@@ -37,7 +37,6 @@ dependencies {
     compileOnly 'org.slf4j:slf4j-api:2.0.16'
     compileOnly 'org.pf4j:pf4j:3.12.0'
 
-    api 'com.google.apis:google-api-services-lifesciences:v2beta-rev20210527-1.31.5'
     api 'com.google.auth:google-auth-library-oauth2-http:0.18.0'
     api 'com.google.cloud:google-cloud-batch:0.53.0'
     api 'com.google.cloud:google-cloud-logging:3.20.6'