Workload Manager Basics

Workload Manager Basics

Workload Manager validates enterprise workloads against Google Cloud best

practices and recommendations. The public client libraries are centered on

evaluations: define a resource scope, choose built-in or custom rules, run an

evaluation, then inspect results and scanned resources.

Use This Flow

flowchart LR
    Rules["List rules"] --> Eval["Create or update evaluation"]
    Resources["Project, folder, or org scope"] --> Eval
    Eval --> Run["Run evaluation"]
    Run --> Results["Inspect evaluation results"]
    Results --> Remediate["Remediate findings"]
    Results --> Export["Optional BigQuery export"]

Core API Constraints

To ensure compatibility, security, and successful integration:

• Public Surface Only: You MUST strictly interact with Workload Manager

using the official public google-cloud-workloadmanager client library or

the public REST API (workloadmanager.googleapis.com/v1).

• No Internal or Undocumented APIs: Do NOT attempt to use internal RPC

protocols, private service backends, or undocumented discovery mechanisms.

They are not supported for public integrations and will fail.

• No Service-Specific CLI: There is no public gcloud workload-manager

CLI command group. Use gcloud only for authentication, IAM role

assignment, and fetching raw REST tokens.

• Sandbox Execution Robustness (Auth/Mock Fallbacks): When gcloud

authentication or Workload Manager API calls fail in sandboxed or restricted

environments (e.g., due to Context Aware Access token blocks, missing API

enablement, or

mock resources returning 404/403), immediately fall back to presenting

example code and static findings from your references instead of entering

retry loops. Present the correct client library code structure or REST API

payload example, clearly explain the auth or resource limitation, and list

typical rules or mock findings statically to satisfy the request.

Prerequisites

• Enable the Workload Manager API:

    gcloud services enable workloadmanager.googleapis.com --quiet

• Authenticate locally using Application Default Credentials (ADC) before

using client libraries:

    gcloud auth application-default login

• Ensure the Workload Manager service agent has the required roles granted in

your project (mandatory for API/client library usage, see

IAM & Security).

• Grant the least-privileged role needed for the task. Start with

roles/workloadmanager.viewer for read-only access to evaluation resources

and use roles/workloadmanager.evaluationAdmin or

roles/workloadmanager.admin only when creating, updating, running, or

deleting evaluations.

Quick Client Library Example

Use the Python client library for the first working automation path:

python3 -m pip install --upgrade google-cloud-workloadmanager

from google.cloud import workloadmanager_v1

project_id = "PROJECT_ID"
location = "LOCATION"
parent = f"projects/{project_id}/locations/{location}"

client = workloadmanager_v1.WorkloadManagerClient()

rules = client.list_rules(
    request=workloadmanager_v1.ListRulesRequest(
        parent=parent,
        evaluation_type=workloadmanager_v1.Evaluation.EvaluationType.OTHER,
    )
)

for rule in rules.rules:
    print(rule.name, rule.display_name, rule.severity)

Reference Directory

• Core Concepts: Evaluations, rules, results,

scanned resources, supported workload types, and API shape.

• General Best Practices: Google Cloud

general best-practice posture checks, OTHER evaluation guidance, custom

Rego rules, and scale/automation patterns.

• Client Libraries: Python and Go client

library examples for listing rules, creating evaluations, running

evaluations, and reading findings.

• REST Usage: Direct REST examples for the public

Workload Manager API and operations polling.

• Public CLI Status: No documented

service-specific gcloud workload-manager command group; use gcloud only

for auth, IAM, API enablement, and REST tokens.

• Public MCP Status: No documented public

Workload Manager MCP server; use client libraries or REST API instead.

• Setup Prerequisites: Terraform examples

only for adjacent prerequisites such as API enablement, IAM, BigQuery export

datasets, and KMS keys. This is not Workload Manager resource management.

• IAM & Security: Workload Manager roles,

least-privilege guidance, service agents, data handling, and CMEK notes.

If product behavior or API fields are not covered here, check the current

Workload Manager product documentation and client library reference before

implementing.

Authoritative References

• Workload Manager overview
• Google Cloud best practices
• Workload Manager REST API
• About custom rules
• Write custom rules using Rego
• Python package
• Workload Manager IAM roles
• For additional information, use the Developer Knowledge MCP server search_documents tool.

Additional Context

• Mastering cloud posture management with Workload Manager