AMP Project Specification

AMP projects include a project metadata file that provides configuration and setup details. These details may include environment variables and tasks to be run on startup.

YAML File Specification ‒ Version 1.0

The project metadata file is a YAML file. It must be placed in your project's root directory, and must be named .project-metadata.yaml. The specifications for this file are listed below. You can also look at an example for one of the AMPs, such as:.project-metadata.yaml.

Fields

Fields for this YAML file are in snake_case. String fields are generally constrained by a fixed character size, for example string(64) is constrained to contain at most 64 characters. Click Show to see the list of fields.

Field Name Type Example Description

name

string(200)

ML Demo

Required: The name of this project prototype. Prototype names do not need to be unique.

description

string(2048)

This demo shows off some cool applications of ML.

Required: A description for this project prototype.

author

string(64)

Cloudera Engineer

Required: The author of this prototype (can be the name of an individual, team, or organization).

date

date string

"2020-08-11"

The date this project prototype was last modified. It shall be in the format: "YYYY-MM-DD" (quotation marks are required).

specification_version

string(16)

0.1

Required: The version of the YAML file specification to use.

prototype_version

string(16)

1.0

Required: The version of this project prototype.

shared_memory_limit

number

0.0625

Additional shared memory in GB available to sessions running in this project. The default is 0.0625 GB (64MB).

environment_variables

environment variables object

See below

Global environment variables for this project prototype.

feature_dependencies feature_dependencies See below A list of feature dependencies of this AMP. A missing dependency in workspace blocks the creation of the AMP.
engine_images engine_images See below Engine images to be used with the AMP. These are recommendations and it does not prevent the user from launching an AMP with non recommended engine images.
runtimes runtimes See below Runtimes to be used with the AMP. These are recommendations and it does not prevent the user from launching an AMP with non recommended runtimes.

tasks

task list

See below

A sequence of tasks, such as running Jobs or deploying Models, to be run after project import.

Example

name: ML Demo
description: >-
This demo shows off some cool applications of ML.
author: Cloudera Engineer
date: '2020-08-11T17:40:00.839Z'
specification_version: 1.0
environment_variables:
...
tasks:
...

Environment variables object

The YAML file can optionally define any number of global environment variables for the project under the environment field. This field is an object, containing keys representing the names of the environment variables, and values representing details about those environment variables. Click Show to see the list of fields in the Environment variables object.

Field Name

Type

Example

Description

default

string

"3"

The default value for this environment variable. Users may override this value when importing this project prototype.

description

string

The number of Model replicas, 3 is standard for redundancy.

A short description explaining this environment variable.

required

boolean

true

Whether the environment variable is required to have a non-empty value, the default is false.

Example: This example creates four environment variables.

environment_variables:
  AWS_ACCESS_KEY:
    default: ""
    description: "Access Key ID for accessing S3 bucket"
  AWS_SECRET_KEY:
    default: ""
    description: "Secret Access Key for accessing S3 bucket"
    required: true
  HADOOP_DATA_SOURCE:
    default: ""
    description: "S3 URL to large data set"
    required: false
  MODEL_REPLICAS:
    default: "3"
    description: "Number of model replicas, 3 is standard for redundancy"
    required: true

Feature Dependencies

AMPs might depend on some optional features of a workspace. The feature_dependencies field accepts a list of such features. Unsatisified feature dependencies prevent the AMP from being launched in a workspace, and display an appropriate error message. The supported feature dependencies are as follows:

  • model_metrics

Runtimes Specification

The runtimes field accepts a list of runtimes objects defined as follows. This Runtimes specification can be added per task or per project.

- editor: the_name_of_the_editor # case-sensitive string required. e.g. Workbench, Jupyter, etc. (how it appears in the UI)
  kernel: the_kernel # case-sensitive string required. e.g. Python 3.6, Python 3.8, R 3.6, etc. (how it appears in the UI)
  edition: the_edition # case-sensitive string required. e.g. Standard, Nvidia GPU, etc. (how it appears in the UI)
  version: the_short_version # case-sensitive string optional. e.g. 2021.03, 2021.05, etc. (how it appears in the UI)
  addons: the_list_addons_needed # list of case-sensitive strings optional. e.g Spark 2.4.7 - CDP 7.2.11 - CDE 1.13, etc. (how it appears in the UI)

This example specifies the Runtimes the Workbench version for Python 3.8.

runtimes:
  - editor: Workbench
    kernel: Python 3.8
    edition: Standard
    addons: ['Spark 2.4.7 - CDP 7.2.11 - CDE 1.13']

Engine Images Specification

The engine_images field accepts a list of engine_image objects defined as follows:

- image_name: the_name_of_the_engine_image # string (required)
  tags: # list of strings (optional)
    - the_tag_of_engine_image
    - ...

This example specifies the official engine image with version 11 or 12:

engine_images:
  - image_name: engine
    tags:
      - 12
      - 11

This example specifies the most recent version of the dataviz engine image in the workspace:

engine_images:
  - image_name: cmldataviz
  - image_name: cdswdataviz

Note that when specifying CDV images, both cmldataviz and cdswdataviz must be specified. When tags are not specified, the most recent version of the engine image with the matching name is recommended. The following rule is used to determine the most recent engine_image with the matching name:

Official Engine (engine) and CDV (cmldataviz and cdswdataviz) images

Since the officially released engine images follow semantic versioning (where a newer version is always larger than any older version, when compared with >), the most recent engine image is the one with the largest tag. For example, engine:14 will be recommended over engine:13 and cmldataviz:6.3.4-b13 is recommended over cmldataviz:6.2.1-b12.

Custom engine images

There is no way for Cloudera Machine Learning to determine the rules for customer custom engine image tags, and therefore there is no reliable way to determine the most recent custom engine image. Use the engine image that has the correct matching name and has the newest ID. The newest ID means that the engine image is the most recently added engine image.

Task list

This defines a list of tasks that can be automatically run on project import. Each task will be run sequentially in the order they are specified in this YAML file. Click Show to see the list of fields.

Field Name

Type

Example

Description

type

string

create_job

Required: The type of task to be executed. See below for a list of allowed types.

short_summary

string

Creating a Job that will do a task.

A short summary of what this task is doing.

long_summary

string

Creating a Job that will do this specific task. This is important because it leads up to this next task.

A long summary of what this task is doing.

Jobs

Create Job

Example

- type: create_job
  name: howdy
  entity_label: howdy
  script: greeting.py
  arguments: Ofek 21
  short_summary: Creating a job that will greet you.
  environment_variables:
  SAMPLE_ENVIRONMENT_VARIABLE: CREATE/RUN_JOB
  kernel: python3
      

Click Show to see the list of fields.

Field Name

Type

Example

Description

type

string

create_job

Required: Must be create_job.

name

string

howdy

Required: Job name.

entity_label

string

howdy

Required: Uniquely identifies this job for future tasks, i.e. run_job tasks. Entity labels must be lowercase alphanumeric, and may contain hyphens or underscores.

script

string

greeting.py

Required: Script for this Job to run.

kernel

string

python3

Required: What kernel this Job shall use. Acceptable values are python2, python3, r, and scala. Note that scala might not be supported for every cluster.

arguments

string

Ofek 21

Command line arguments to be given to this Job when running.

environment_variables

environment variables object

See above

See above

cpu

number

1.0

The amount of CPU virtual cores to allocate for this Job, the default is 1.0.

memory

number

1.0

The amount of memory in GB to allocate for this Job, the default is 1.0.

gpu

integer

0

The amount of GPU to allocate for this Job, the default is 0.

timeout

integer

10

The amount of time in minutes to wait before timing out this Job, the default is 10.

timeout_kil

boolean

false

Whether or not to stop this Job when it times out, the default is false.

Run Job

Example run job task:

- type: run_job
  entity_label: howdy
  short_summary: Running the job that will greet you.
  long_summary: >-
    Running the job that will greet you. It will greet you by the name
    which is the first and only command line argument.
      

Most Job run tasks shall just contain the type and entity_label fields. Click Show to see the list of fields.

Field Name

Type

Example

Description

type

string

run_job

Required: Must be run_job.

entity_label

string

howdy

Required: Must match an entity_label of a previous create_job task.

However, they can optionally override previously defined fields. Click Show to see the list of fields.

Field Name

Type

Example

Description

script

string

greeting.py

Required: Script for this Job to run.

kernel

string

python3

Required: What kernel this Job shall use. Acceptable values are python2, python3, r, and scala. Note that scala might not be supported for every cluster.

arguments

string

Ofek 21

Command line arguments to be given to this Job when running.

environment_variables

environment variables object

See above

See above

cpu

number

1.0

The amount of CPU virtual cores to allocate for this Job, the default is 1.0

memory

number

1.0

The amount of memory in GB to allocate for this Job, the default is 1.0.

gpu

integer

0

The amount of GPU to allocate for this Job, the default is 0.

shared_memory_limit

number

0.0625

Limits the additional shared memory in GB that can be used by this Job, the default is 0.0625 GB (64MB).

Models

Note: All models have authentication disabled, so their access key alone is enough to interact with them.

Resources object

Models may define a resources object which overrides the amount of resources to allocate per Model deployment.

Click Show to see the list of fields.

Field Name

Type

Example

Description

cpu

number

1.0

The number of CPU virtual cores to allocate per Model deployment.

memory

number

2.0

The amount of memory in GB to allocate per Model deployment.

gpu

integer

0

The amount of GPU to allocate per Model deployment.

For example:

resources:
  cpu: 1
  memory: 2

Replication policy object

Models may define a replication policy object which overrides the default replication policy for Model deployments.

Click Show to see the list of fields.

Field Name

Type

Example

Description

type string fixed Must be fixed if present.
num_replicas integer 1 The number of replicas to create per Model deployment.

For example:

replication_policy:
  type: fixed
  num_replicas: 1
      

Model examples list

Models may include examples, which is a list of objects containing a request and response field, each containing a valid object inside, as shown in the example:

examples:
  - request:
      name: Ofek
      age: 21
    response: 
      greeting: Hello Ofek (21)
  - request:
      name: Jimothy
      age: 43
    response:
      greeting: Hello Coy (43)
      

Click Show to see the list of fields.

Field Name

Type

Example

Description

request

string

See above

Required: An example request object.

response

string

See above

Required: The response to the above example request object.

Create Model

Example:

- type: create_model
  name: Say hello to me
  entity_label: says-hello
  description: This model says hello to you
  short_summary: Deploying a sample model that you can use to greet you
  access_key_environment_variable: SHTM_ACCESS_KEY
  default_resources:
  cpu: 1
  memory: 2
      

Click Show to see the list of fields.

Field Name

Type

Example

Description

type

string

create_model

Required: Must be create_model.

name

string

Say hello to me

Required: Model name

entity_label

string

says-hello

Required: Uniquely identifies this model for future tasks, i.e. build_model and deploy_model tasks. Entity labels must be lowercase alphanumeric, and may contain hyphens or underscores.

access_key_environment_variable

string

SHTM_ACCESS_KEY

Saves the model's access key to an environment variable with the specified name.

default_resources

resources object

See above

The default amount of resources to allocate per Model deployment.

default_replication_policy

replication policy object

See above

The default replication policy for Model deployments.

description

string

This model says hello to you

Model description.

visibility

string

private

The default visibility for this Model.

Build Model

Example

- type: build_model
  entity_label: says-hello
  comment: Some comment about the model
  examples:
    - request:
        name: Ofek
        age: 21
    response: 
      greeting: Hello Ofek (21)
  target_file_path: greeting.py
  target_function_name: greet_me
  kernel: python3
  environment_variables:
    SAMPLE_ENVIRONMENT_VARIABLE: CREATE/BUILD/DEPLOY_MODEL

Field Name

Type

Example

Description

type

string

build_model

Required: Must be build_model.

entity_label

string

says-hello

Required: Must match an entity_label of a previous create_model task.

target_file_path

string

greeting.py

Required: Path to file that will be run by Model.

target_function_name

string

greet_me

Required: Name of function to be called by Model.

kernel

string

python3

What kernel this Model shall use. Acceptable values are python2, python3, r, and scala. Note that scala might not be supported for every cluster.

comment

string

Some comment about the model

A comment about the Model.

examples

model examples list

See above

A list of request/response example objects.

environment_variables

environment variables object

See above

See above

Deploy Model

Example:

- type: deploy_model
  entity_label: says-hello
  environment_variables:
  SAMPLE_ENVIRONMENT_VARIABLE: CREATE/BUILD/DEPLOY_MODEL

Most deploy model tasks shall only contain the type and entity_label fields. Click Show to see the list of fields.

Field Name

Type

Example

Description

type

string

deploy_model

Required: Must be deploy_model.

entity_label

string

says-hello

Required: Must match an entity_label of a previous deploy_model task.

However, they can optionally override previously defined fields. Click Show to see the list of fields.

Field Name

Type

Example

Description

cpu

number

1.0

The number of CPU virutal cores to allocate for this Model deployment.

memory

number

2.0

The amount of memory in GB to allocate for this Model deployment.

gpu

integer

0

The amount of GPU to allocate for this Model deployment.

replication_policy

replication policy object

See above

The replication policy for this Model deployment.

environment_variables

environment variables object

See above

Overrides environment variables for this Model deployment.

Applications

Start Application

Example:

- type: start_application
  subdomain: greet
  script: greeting.py
  environment_variables:
    SAMPLE_ENVIRONMENT_VARIABLE: START_APPLICATION
  kernel: python3

Click Show to see the list of fields.

Field Name

Type

Example

Description

bypass_authentication

boolean

True

When enabled, allows unauthenticated access to an application

type

string

start_application

Required: Must be start_application.

subdomain

string

greet

Required: Application subdomain, which must be unique per Application, and must be alphanumeric and hyphen-delimited. Application subdomains are also converted to lowercase.

kernel

string

python3

Required: What kernel this Application shall use. Acceptable values are python2, python3, r, and scala. Note that scala might not be supported for every cluster.

entity_label

string

greeter

Uniquely identifies this application for future tasks. Entity labels must be lowercase alphanumeric, and may contain hyphens or underscores.

script

string

greeting.py

Script for this Application to run.

name

string

Greeter

Application name, defaults to 'Untitled application'.

description

string

Some description about the Application

Application description, defaults to 'No description for the app'.

cpu

number

1.0

The number of CPU virutal cores to allocate for this Application.

memory

number

1.0

The amount of memory in GB to allocate for this Application.

gpu

integer

0

The amount of GPU to allocate for this Application.

shared_memory_limit

number

0.0625

Limits the additional shared memory in GB that can be used by this application, the default is 0.0625 GB (64MB).

environment_variables

environment variables object

See above

See above

static_subdomain

boolean

True

When enabled, subdomain will not get randomized.

Experiments

Run Experiment

Example:

- type: run_experiment
  script: greeting.py
  arguments: Ofek 21
  kernel: python3

Click Show to see the list of fields.

Field Name

Type

Example

Description

type

string

run_experiment Required: Must be run_experiment.

script

string

greeting.py

Required: Script for this Experiment to run.

entity_label

string

test-greeter

Uniquely identifies this experiment for future tasks. Entity labels must be lowercase alphanumeric, and may contain hyphens or underscores.

arguments

string

Ofek 21

Command line arguments to be given to this Experiment when running.

kernel

string

python3

What kernel this Experiment shall use. Acceptable values are python2, python3, r, and scala. Note that scala might not be supported for every cluster.

comment

string

Comment about the experiment

A comment about the Experiment.

cpu

number

1.0

The amount of CPU virtual cores to allocate for this Experiment.

memory

number

1.0

The amount of memory in GB to allocate for this Experiment.

gpu

number

0

The amount of GPU to allocate for this Experiment.

Sessions

Run Sessions

Example:

- type: run_session
  name: How to be greeted interactively
  code: |
    import os
    os.environ['SAMPLE_ENVIRONMENT_VARIABLE'] = 'SESSION'
    
    !python3 greeting.py Ofek 21
    
    import greeting
    greeting.greet_me({'name': 'Ofek', 'age': 21})
  kernel: python3
  memory: 1
  cpu: 1
  gpu: 0

Click Show to see the list of fields.

Field Name

Type

Example

Description

type

string

run_session

Required: Must be run_session.

string

See above for code, greeting.py for script

Required: Either the code or script field is required to exist for the run Session task, not both. code is a direct block of code that will be run by the Session, while script is a script file that will be executed by the Session.

kernel

string

python3

Required: What kernel this Session shall use. Acceptable values are python2, python3, r, and scala. Note that scala might not be supported for every cluster.

cpu

number

1.0

Required: The amount of CPU virtual cores to allocate for this Session.

memory

number

1.0

Required: The amount of memory in GB to allocate for this Session.

entity_label

string

greeter

Uniquely identifies this session for future tasks. Entity labels must be lowercase alphanumeric, and may contain hyphens or underscores.

name

string

How to be greeted interactively

Session name.

gpu

integer

0

The amount of GPU to allocate for this Session.