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docs/_sources/source/compute_backends.rst

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compute_config/azure_containers.md
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compute_config/kubernetes.md
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compute_config/knative.md
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compute_config/singularity.md
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**Standalone Backends:**
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docs/_sources/source/compute_config/aws_lambda.md

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| aws_lambda | remote_invoker | False | no | Activate the remote invoker feature that uses one cloud function to spawn all the actual `map()` activations |
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| aws_lambda | architecture | x86_64 | no | Runtime architecture. One of **x86_64** or **arm64** |
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| aws_lambda | ephemeral_storage | 512 | no | Ephemeral storage (`/tmp`) size in MB (must be between 512 MB and 10240 MB) |
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| aws_lambda | user_tags | {} | no | List of {name: ..., value: ...} pairs for Lambda instance user tags |
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| aws_lambda | env_vars | {} | no | List of {name: ..., value: ...} pairs for Lambda instance environment variables |
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| aws_lambda | namespace | | no | Virtual namespace. This can be useful to virtually group Lithops function workers. The functions deployed by lithops will be prefixed by this namespace. For example you can set it to differentiate between `prod`, `dev` and `stage` environments. |
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| aws_lambda | runtime_include_function | False | no | If set to true, Lithops will automatically build a new runtime, including the function's code, instead of transferring it through the storage backend at invocation time. This is useful when the function's code size is large (in the order of 10s of MB) and the code does not change frequently |
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```bash
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lithops logs poll
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```
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```

docs/_sources/source/compute_config/kubernetes.md

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|k8s | runtime_cpu | 1 |no | CPU limit. Default 1vCPU |
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|k8s | runtime_memory | 512 |no | Memory limit in MB. Default 512MB |
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|k8s | runtime_timeout | 600 |no | Runtime timeout in seconds. Default 600 seconds |
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|k8s | master_timeout | 600 |no | Master pod timeout in seconds. Default 600 seconds |
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## Test Lithops
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# Singularity
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Lithops with *Singularity* as a serverless compute backend is **ideal for High-Performance Computing (HPC) environments** where Docker might be restricted due to security concerns or administrative privileges. Singularity's ability to run containers without requiring root access makes it a suitable choice for such environments.
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**Note:** This backend requires a RabbitMQ server for communication and coordination between Lithops components.
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## Configuration
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### Configure RabbiMQ
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```yaml
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lithops:
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backend: singularity
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monitoring: rabbitmq
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rabbitmq:
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amqp_url: amqp://<username>:<password>@<rabbitmq_host>:<rabbitmq_port>/<vhost>
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```
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Replace `<username>`, `<password>`, `<rabbitmq_host>`, `<rabbitmq_port>`, and `<vhost>` with your RabbitMQ credentials.
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### Configure Singularity backend
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```yaml
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singularity:
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worker_processes: <WORKER_PROCESSES>
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runtime: <RUNTIME_NAME>
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sif_path: <CUSTOM_PATH>
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```
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## Summary of Configuration Keys for Singularity
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| Group | Key | Default | Mandatory | Additional info |
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|-------------|----------------------|---------|-----------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| singularity | worker_processes | 1 | no | Number of functions sent in each RabbitMQ package. Ideally, set to a multiple of the node's CPU count. |
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| singularity | runtime | | yes | Name of the Singularity runtime image (`.sif`) file containing the Lithops runtime environment. |
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| singularity | sif_path | /tmp | no | Directory path where the Singularity runtime image `.sif` will be stored. |
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## Deploying the Runtime Image
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Since Lithops doesn't directly manage Singularity instances on your cluster, you need to ensure the runtime image is available on **each** node:
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1. **Transfer:** Manually copy the built `.sif` runtime image to each node in your cluster.
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2. **Start:** Start a new Singularity instance on each node using the `.sif` file. Then run the instance and add the RabbitMQ server details to the environment variables.
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```bash
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singularity instance start --fakeroot /path/to/sif/your-singularity-runtime.sif <INSTANCE_NAME>
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singularity run instance://<INSTANCE_NAME> --env AMQP_URL=amqp://<username>:<password>@<rabbitmq_host>:<rabbitmq_port>/<vhost>
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```
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Depending on your cluster setup, you might need to adjust permissions of the `.sif` file or the [singularity flags](https://docs.sylabs.io/guides/latest/user-guide/cli/singularity_exec.html#singularity-exec) to ensure that the user running the Lithops worker can access and execute it.
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## Test Lithops
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Once you have your compute and storage backends configured, you can run a hello world function with:
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```bash
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lithops hello -b singularity
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```
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## Viewing the execution logs
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You can view the function executions logs in your local machine using the *lithops client*:
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```bash
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lithops logs poll
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```

docs/_sources/source/configuration.rst

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|| `Oracle Functions <compute_config/oracle_functions.html>`_ || `Oracle Object Storage <storage_config/oracle_oss.html>`_ |
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|| `Kubernetes <compute_config/Kubernetes.html>`_ || |
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|| `Knative <compute_config/knative.html>`_ || |
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|| `Singularity <compute_config/singularity.html>`_ || |
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|| `OpenWhisk <compute_config/openwhisk.html>`_ || |
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|| `Remote Host / Virtual Machine <compute_config/vm.html>`_ || |
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|| `IBM Virtual Private Cloud <compute_config/ibm_vpc.html>`_ || |

docs/_sources/source/execution_modes.rst

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fexec = lithops.ServerlessExecutor()
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- Available backends: `IBM Cloud Functions <compute_config/ibm_cf.md>`_, `IBM Code Engine <compute_config/code_engine.md>`_, `AWS Lambda <compute_config/aws_lambda.md>`_, `AWS Batch <compute_config/aws_batch.md>`_, `Google Cloud Functions <compute_config/gcp_functions.md>`_, `Google Cloud Run <compute_config/gcp_cloudrun.md>`_, `Azure Functions <compute_config/azure_functions.md>`_, `Azure Container APPs <compute_config/azure_containers.md>`_, `Aliyun Function Compute <compute_config/aliyun_functions.md>`_, `Oracle Functions <compute_config/oracle_functions.md>`_, `Kubernetes Jobs <compute_config/kubernetes.md>`_, `Knative <compute_config/knative.md>`_, `OpenWhisk <compute_config/openwhisk.md>`_
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- Available backends: `IBM Cloud Functions <compute_config/ibm_cf.md>`_, `IBM Code Engine <compute_config/code_engine.md>`_, `AWS Lambda <compute_config/aws_lambda.md>`_, `AWS Batch <compute_config/aws_batch.md>`_, `Google Cloud Functions <compute_config/gcp_functions.md>`_, `Google Cloud Run <compute_config/gcp_cloudrun.md>`_, `Azure Functions <compute_config/azure_functions.md>`_, `Azure Container APPs <compute_config/azure_containers.md>`_, `Aliyun Function Compute <compute_config/aliyun_functions.md>`_, `Oracle Functions <compute_config/oracle_functions.md>`_, `Kubernetes Jobs <compute_config/kubernetes.md>`_, `Knative <compute_config/knative.md>`_, `Singularity <compute_config/singularity.md>`_, `OpenWhisk <compute_config/openwhisk.md>`_
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Standalone mode

docs/_sources/source/supported_clouds.rst

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- `OpenStack Swift <https://docs.openstack.org/swift/latest/>`_
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* - `Knative <https://knative.dev/>`_
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- `Redis <https://redis.io/documentation>`_
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* - `OpenWhisk <https://openwhisk.apache.org/>`_
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* - `Singularity <https://docs.sylabs.io/guides/latest/user-guide/index.html>`_
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- `Ceph <https://docs.ceph.com/en/latest/>`_
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* -
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* - `OpenWhisk <https://openwhisk.apache.org/>`_
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- `MinIO <https://docs.min.io/minio/baremetal/>`_
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* -
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- `Infinispan <https://infinispan.org/documentation/>`_

docs/api_futures.html

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<li class="toctree-l2"><a class="reference internal" href="source/compute_config/singularity.html">Singularity</a></li>
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<li class="toctree-l2"><a class="reference internal" href="source/compute_config/vm.html">Virtual Machine</a></li>
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<li class="toctree-l2"><a class="reference internal" href="source/compute_config/ibm_vpc.html">IBM Virtual Private Cloud</a></li>
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docs/api_storage.html

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<li class="toctree-l2"><a class="reference internal" href="source/compute_config/singularity.html">Singularity</a></li>
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<li class="toctree-l2"><a class="reference internal" href="source/compute_config/vm.html">Virtual Machine</a></li>
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docs/genindex.html

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