Agent Platform Endpoint Management

Agent Platform Endpoint Management

Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read Usage Attribution. For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix gcloud with CLOUDSDK_METRICS_REQUEST_ATTRIBUTION and append the attribution suffix to User-Agent headers:

CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:agent-platform-endpoint-management)"
User-Agent: <existing_user_agent> agent-skills/1.0 (skill:agent-platform-endpoint-management)

Overview

This skill provides procedural knowledge for managing Agent Platform Endpoints. Endpoints are logical serving hosts that provide a stable URL for online predictions. You must create an endpoint before you can deploy a model to it.

Safety & Confirmation Tiers (CRITICAL)

Before executing any commands on behalf of the user, you MUST adhere to the following safety tiers based on the action requested:

1. Tier R: Read-only (list, describe, get)

   • No confirmation needed. Execute immediately to gather information.

2. Tier M: Mutating & Reversible (create, update)

   • Requires interactive confirmation with 'Yes'/'No' options. The confirmation prompt MUST contain the exact, literal command string with all required flags (e.g. --region=us-central1, --display-name="...") — natural-language paraphrases are NOT sufficient.

   • Same-turn restriction: NEVER execute the command in the same turn as presenting the confirmation prompt. Stop and wait for the user's reply; only execute after explicit 'Yes' / approval.

3. Tier D: Destructive & Irreversible (delete)

   • Requires explicit typed confirmation (e.g. "I confirm" or "Yes, delete it"). Ask for confirmation IMMEDIATELY — before any pre-flight checks (don't describe first, don't check if the endpoint is empty first).

   • Same-turn restriction: NEVER execute in the same turn as asking for typed confirmation. Wait for the user to reply in a new turn.

Phase 0: Environment Setup

CRITICAL: Before running any commands, you MUST ensure the environment is correctly initialized by following these steps:

1. Google Cloud Authentication: Authenticate with your Google Cloud credentials and configure active Application Default Credentials (ADC) for Agent Platform access:

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   gcloud auth login
   gcloud auth application-default login

2. Set Project: Configure the active project for subsequent commands:

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   gcloud config set project $PROJECT_ID

3. Region: Always specify --region=$LOCATION_ID on each command below. Do NOT use global. Ask the user to specify the region if not provided.

1. Listing Endpoints (Tier R)

Use this command to discover existing endpoints in a specific region and retrieve their IDs. No confirmation is required.

gcloud ai endpoints list \
    --region=$LOCATION_ID

(Optional) To bound the result, use --limit=$LIMIT; --page-size=$PAGE_SIZE controls API chunking only and does NOT limit the total output. Use --page-token=$PAGE_TOKEN to continue from a previous batch.

[!IMPORTANT]

Always specify the --region. Do NOT use 'global'. Ask the user to specify if not provided.

2. Describing an Endpoint (Tier R)

Retrieve the full metadata for a specific endpoint. No confirmation is required.

gcloud ai endpoints describe $ENDPOINT_ID \
    --region=$LOCATION_ID

The models deployed on an endpoint are its deployedModels in this output. In the Python SDK they are endpoint.gca_resource.deployed_models; aiplatform.Endpoint has no deployed_models attribute.

3. Creating an Endpoint (Tier M)

Create a new endpoint resource. The parent resource is the location. Action requires an inline confirmation card before proceeding.

gcloud ai endpoints create \
    --region=$LOCATION_ID \
    --display-name="my-endpoint"

The command has no --asynchronous flag: it waits for the operation and prints the new endpoint's resource name, whose last segment is the endpoint ID.

[!IMPORTANT]

You MUST seek interactive confirmation first. Your confirmation prompt MUST show the literal command string. For example:

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gcloud ai endpoints create --region=$LOCATION_ID --display-name="my-endpoint"

Or the exact flags. Do not execute this command in the same turn as proposing the confirmation.

4. Updating an Endpoint (Tier M)

Update endpoint metadata such as display name or labels. Action requires an inline confirmation card before proceeding.

gcloud ai endpoints update $ENDPOINT_ID \
    --region=$LOCATION_ID \
    --display-name="new-display-name"

Check if the endpoint exists first by either listing or describing the endpoint.

[!IMPORTANT]

You MUST seek interactive confirmation first. Your confirmation prompt MUST show the literal command string. For example:

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gcloud ai endpoints update $ENDPOINT_ID --region=$LOCATION_ID --display-name="new-display-name"

Or the exact flags. CRITICAL: You are strictly prohibited from executing this command in the same turn as asking for confirmation. When you ask for confirmation, you MUST stop immediately and wait for the user to reply.

5. Deleting an Endpoint (Tier D)

Permanently delete an endpoint resource. Action requires explicit typed confirmation before proceeding.

gcloud ai endpoints delete $ENDPOINT_ID \
    --region=$LOCATION_ID

[!WARNING]

All models must be undeployed from the endpoint before it can be deleted. Do not run describe until AFTER you have received typed confirmation to delete.

6. Traffic Splitting (Tier M)

You can manage traffic split between different models deployed on the same endpoint during an update. Action requires an inline confirmation card before proceeding.

# Example: Deploying a model with a specific traffic split is usually done
# via 'gcloud ai endpoints deploy-model'.

Refer to the agent-platform-deploy skill for instructions on deploying and undeploying models.

Troubleshooting

• 403 Permission Denied: Ensure aiplatform.admin or owner role is assigned.

• Quota Exceeded: Verify the region's endpoint quota in the Cloud Console.

• Resource Busy: If a deletion fails, check if models are still being undeployed.