Luna services requirements

There are several requirements for luna-services for lambda work.

General requirement is Luna-Configurator service, see service configuration for details.

It is also required luna_lambda enabled in ADDITIONAL_SERVICES_USAGE setting.

There are several lambda types, including standalone lambda which does not require any other service by default, but lambdas of any other types can have more requirements, see requirements for specific lambda from lambda types for specific requirements.

S3 storage requirements

The luna-lambda service requires s3 bucket for storing archives with lambda.

Note

It is not required to use amazon s3 service, the minio object storage also fits the requirements.

Read/write access is required for the specified bucket.

Warning

At present, there is no mechanism of s3 bucket garbage collection, but be careful removing lambdas data. The lambda update mechanism may use those data.

The s3 storage is determined by S3 setting of luna-lambda. See service configuration for configuration details.

Kubernetes cluster requirements

The luna-lambda service requires some access rights in kubernetes cluster whose provided by specified credentials.

At present, the service uses default namespace of kubernetes cluster, so it is required to grant creation/monitoring/deletion rights (including service/deployment/pod creation, deletion). It is recommended to ask kubernetes administrator to grant access for the above.

The simplest way to allow lambda creation and management is to execute next command for kubernetes:

kubectl create clusterrolebinding permissive-binding --clusterrole=cluster-admin --user=admin --user=kubelet --group=system:serviceaccounts

Warning

It is highly not recommended to use similar decisions in production. It is highly recommended that you negotiate with your Kubernetes cluster administrator and use the security policy for your Kubernetes cluster as required.

Note

At present, there is no possibility to allow lambda to use mount directories or replicate to different nodes. These possibilities might be added in future releases.

Docker registry requirements

The luna-lambda service requires docker registry for lambda image storage. The registry must be specified using LAMBDA_REGISTRY, see configurator requirements for details.

Those registry also must contain base lambda images provided by VL:

  • image named lpa-lambda-base for all lambdas without Luna SDK support

  • image name lpa-lambda-base-fsdk for lambdas with Luna SDK support (for example)

If those registry is insecure registry, it is also required to add it to LAMBDA_INSECURE_REGISTRIES setting.

The registry storage is determined by LAMBDA_REGISTRY setting of luna-lambda. See service configuration for configuration details.

Lambda - base image requirements

The luna-lambda service creates each lambda based on one of two base docker images: lpa-lambda-base or lpa-lambda-base-fsdk, but there is a possibility to create custom base image for lambda.

The lpa-lambda-base image intended for most lambdas and provides basic functionality for lambda.

The lpa-lambda-base-fsdk image in addition to base image functionality provides functionality for FSDK usage by lambda.

The custom base lambda image is intended for complex lambdas for which not enough opportunities of lpa-lambda-base or lpa-lambda-base-fsdk base images (For example, multi-stage docker container building, including large libraries or data into docker container).

There are several requirements for custom base lambda image:

  • It must use lpa-lambda-base or lpa-lambda-base-fsdk as base image

  • It must not remove or modify any installed dependencies (python3, gcc and so on)

  • It must located at the same registry as other base lambda images

To use custom lambda base image it requires to specify it’s name and tag for lambda creation request or put lambda request.

Lambda - Archive requirements

Lambda creation is initiated by lambda creation request which is required archive which has the following requirements:

  • zip archive without a password

  • minimum required content is a lambda_main.py file (see python code requirements for details)

  • it is possible to add a requirements.txt file - all requirements from the file will be included in the lambda docker image

    example:

    requirements.txt
      numpy==1.24.2

  • it is possible to add additional command to docker container building stage. See create lambda for api description.

    Keep in mind that lambda use CentOS 8 docker image as basic image while working with system dependencies.

    For example to use pillow library in lambda make the following steps:

    • add pillow to requirements.txt

    • add the following list of command to user_docker_commands (in lambda creation request)

      RUN yum install -y epel-release
RUN yum install -y libjpeg-turbo-devel

    • perform all other standard actions to create lamdba

    Warning

    It is not recommended to perform actions which are not required root access using root user.

    To switch between users, use USER root and USER luna commands.

    For more information about docker build commands see dockerfile reference

    Warning

    It is not possible to perfectly validate additional user specified docker commands so use it on your own risk

  • there are several files and folders whose addition to archive will take no effect, because these modules will be automatically replaced during lambda creation:

    (from the root archive folder)
     ├──run.py
 └──luna_lambda_tools

  • you can add custom documentation to the zip archive with the lambda. It’s recommended to be used with standalone lambdas. Documentation must be placed in docs directory in HTML and YAML formats. Files must be named as lambda.yml and lambda.html. Both HTML and YAML files are required.

    (example zip structure)
     lambda.zip
 ├── docs
 │  ├── lambda.html
 │  └── lambda.yml
 └── lambda_main.py

Lambda - General python code requirements

General requirements:

  • Python 3.11 or higher.

  • The luna-lambda-tools library is required for development. Available in VL pypi.

    Example of luna-lambda-tools installation using pip:

    pip install --trusted-host pypi.visionlabs.ru --extra-index-url http://pypi.visionlabs.ru/root/public/+simple luna-lambda-tools
  • The lambda entry point is the main function in lambda_main.py file. It must:

    • represents an asynchronous function

    • takes one argument - request: StandaloneLambdaRequest (for standalone lambda) / request: HandlersLambdaRequest (for handlers lambda) (More information about lambda types and differences of handlers and others available at lambda types description.)

    • returns dictionary

    example:

    from luna_lambda_tools import StandaloneLambdaRequest

async def main(request: StandaloneLambdaRequest) -> dict:
    result = request.json["data"]
    return {"result": result}

More possibilities described at lambda development