Workload Manager Core Concepts

Workload Manager provides validation and automation tooling for enterprise workloads on Google Cloud. Public documentation describes it as a service for automating workload deployment and validating workloads against best practices and recommendations.

Resource Model

flowchart TD
    Scope["Scope: project, folder, or organization"] --> Filter["ResourceFilter"]
    Filter --> Evaluation["Evaluation"]
    Rules["Rule names or evaluation type"] --> Evaluation
    Evaluation --> Execution["Execution"]
    Execution --> RuleResults["Rule execution results"]
    Execution --> Findings["Execution results"]
    Execution --> Scanned["Scanned resources"]
    Findings --> Commands["Remediation commands"]
    Evaluation --> BQ["Optional BigQuery destination"]

Main Resources

• Evaluation: Configuration that defines what to validate. It includes a resource filter, workload evaluation type, rule names, labels, optional fixed schedule, optional custom rules bucket, optional BigQuery destination, and optional CMEK key.
• Rule: A best-practice check with display name, severity, categories, remediation text, tags, and asset type.
• Execution: A run of an evaluation. Executions expose state, timing, engine, run type, rule results, notices, external data sources, and summary counts.
• ExecutionResult: A finding or remediation result from an execution, including rule, severity, violation message, documentation URL, affected resource, details, and suggested commands.
• ScannedResource: A resource scanned by an execution, optionally filtered by rule.

Evaluation Types

The public v1 client libraries expose these evaluation types:

• SAP: SAP best practices.
• SQL_SERVER: SQL Server best practices.
• OTHER: General Google Cloud best practices and custom organizational best-practice rules.

Use list_rules with an evaluation type before creating an evaluation. This keeps the selected rule names aligned with the workload type and current public rule catalog.

For OTHER, start by listing the available rules in the target location. Use the built-in general best-practice catalog for baseline cloud posture checks, and use custom_rules_bucket only when evaluating Rego rules uploaded to Cloud Storage. See General Best Practices for selection patterns.

Evaluation Scope

Use ResourceFilter to constrain blast radius:

• scopes: projects/{project_id}, folders/{folder_id}, or organizations/{organization_id}.
• resource_id_patterns: Regular-expression style resource ID patterns.
• inclusion_labels: Required labels that must be present on included resources.
• gce_instance_filter.service_accounts: Limits Compute Engine instances to selected service accounts.

Prefer the smallest project or label-filtered scope that answers the question. Folder or organization scopes need broader permissions and can produce more results, more logs, and more BigQuery export data.

Scheduling

Evaluation.schedule accepts fixed cron strings documented in the client libraries:

• 0 */1 * * *: hourly
• 0 */6 * * *: every 6 hours
• 0 */12 * * *: every 12 hours
• 0 0 */1 * *: daily
• 0 0 */7 * *: weekly
• 0 0 */14 * *: every 14 days
• 0 0 1 */1 *: monthly

If a user needs an ad hoc run, use run_evaluation instead of adding a schedule.

Public Surface Boundaries

The Python client library package google-cloud-workloadmanager and generated Go client cover evaluation workflows: evaluations, executions, execution results, rules, and scanned resources.

The REST reference may expose additional resources, such as deployments, actuations, discovered profiles, insights, and operations. When a needed resource is not available in a client library, use the REST API directly and keep the request shape close to the REST reference.