Define one bounded outcome
Name the condition, customer scope, expected state, owner, risk, and proof required before choosing actions.
Governed automation playbook
Design MSP automation that can pause, prove, recover, and improve
Use a practical signal-to-proof playbook for scoping automation, applying policy, routing approvals, verifying actions, and handling failure.
Signal, policy, approval, action, verification, and evidence
Start with the operating decision
Choose where automation helps and where authority must stop it.
Separate policy from execution
Evaluate entitlement, permission, maintenance state, and approval before dispatching a change through its owning module.
Treat verification as work
Read back the resulting state, preserve evidence, and keep a failed or unknown result open for recovery or escalation.
Signal to proof
Build each workflow around a visible control path.
- 01 · Signal
Normalize the trigger and scope
Capture source, tenant, customer, affected object, severity, current state, and a stable identity for the prospective run.
- 02 · Policy
Decide whether the workflow may proceed
Apply role, entitlement, customer policy, maintenance, rate, data-region, and risk controls to the current state.
- 03 · Approval
Route sensitive work to the right authority
Present the exact scope, proposed action, impact, evidence, and expiry, then revalidate the request before execution.
- 04 · Action and proof
Execute through the owner and verify
Dispatch an idempotent action, read back the result, preserve attempts and evidence, and route failure to retry, rollback, or escalation.
Review implementation detailsCapabilities · Controls remain available without extending the main decision path.
Playbook checkpoints
Review the controls before a workflow reaches production.
Scope review
Confirm tenant, customer, object selection, exclusions, credentials, entitlements, and the module that owns each action.
Safety review
Define approval, step-up authentication, maintenance, rate limits, idempotency, retry ceilings, and rollback or containment paths.
Evidence review
Record trigger data, policy version, decision, actor, approver, attempts, provider response class, verification, and final state.
Failure is part of the design
Keep retries, rollback, escalation, and evidence explicit.
RadiantOS keeps scope, access, approval, data placement, and audit evidence visible where the decision happens.
Review the security approachAutomation does not create authority
A workflow remains constrained by current permission, entitlement, customer policy, approval, and action-owner controls.
Dispatch is not success
The workflow should settle only after the expected state is verified or the unresolved result is assigned for follow-up.
Questions, answered
Governed automation playbook — questions to resolve before you decide.
Which workflow should I automate first?
Choose a frequent, bounded decision with dependable inputs, a clear owner, reversible or containable actions, and a result that can be verified.
When should approval be required?
Use approval when risk, customer policy, destructive scope, privilege, cost, data exposure, or separation-of-duty requirements demand another decision-maker.
What should happen after verification fails?
Keep the run unresolved, preserve evidence, stop dependent actions, and follow the defined retry, rollback, containment, or escalation path.