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scopes_read

Scopes are the definition in nullplatform of a deployable runtime environment. They have a type (Kubernetes, Lambda, EC2), a configuration, and can be deployed with a release.

A scope represents a logical unit where your application assets (Docker images, Lambda functions) run and scale with the same technological specification.

Listing scopes for an application​

To list the scopes of an application:

Api Call:

Method: GET
Endpoint: /scope?application_id=<application_id>

Np Cli:

np scope list --application_id <application_id>

Reading a specific scope​

To get details about a specific scope:

Api Call:

Method: GET
Endpoint: /scope/:id?include_messages=true

** The include_messages=true parameter is optional but recommended to see any relevant messages or errors related to the scope.

Np Cli:

np scope read --id <scope_id>

This will show you the scope configuration, including:

  • Scope type (Kubernetes, Lambda, EC2)
  • Associated dimensions
  • Runtime configuration
  • Status

Listing deployments for a scope​

To check the deployments of a scope:

Api Call:

Method: GET
Endpoint: /deployment?scope_id=<scope_id>&application_id=<application_id>

Np Cli:

np deployment list --application_id <application_id> --scope_id <scope_id>

Optionally you can add --include_messages to get all the deployment messages:

np deployment list --application_id <application_id> --scope_id <scope_id> --include_messages

Reading a specific deployment​

If you want to directly get a particular deployment:

Api Call:

Method: GET
Endpoint: /deployment/:id

Np Cli:

np deployment read --id <deployment_id>

Checking scope dimensions​

Dimensions help group scopes for parameter management. To see which dimensions are assigned to a scope, use the scope read command shown above. The response will include dimension information.

Common scope use cases​

Scopes can be partitioned for different purposes:

  • Regional distribution: Separate scopes for different geographic regions (US, EU, Asia)
  • Environments: Production, staging, development environments
  • Workload separation: Read vs. write workloads
  • Infrastructure sizing: Different hardware specifications for different workloads