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

1. Enable the Workload Manager API:

   gcloud services enable workloadmanager.googleapis.com --quiet
   

2. Authenticate locally using Application Default Credentials (ADC) before
   using client libraries:

   gcloud auth application-default login
   

3. Ensure the Workload Manager service agent has the required roles granted in
   your project (mandatory for API/client library usage, see
   IAM & Security).

4. 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