Start with the affected resource
A cloud incident needs more than a provider name. Resolve the intended target and gather the available inspection evidence before proposing changes. AutoSolve combines incident context, observed findings, relevant resolution history, and execution constraints. Missing information can be surfaced as work to complete before dispatch.
Three implemented cloud command paths
AWS execution dispatches commands through Systems Manager. Azure execution uses VM Run Command. Google Cloud execution uses Compute Engine SSH through gcloud. These are command-execution paths, alongside inventory and context integrations. Each needs its configured credentials, connectivity, target support, and permissions; access to cloud inventory alone does not authorize a change.
Prepare a package an operator can review
A remediation package can include prerequisites, preflight checks, execution, verification, and defined rollback steps. AutoSolve evaluates available paths against the action's requirements. A useful review answers which resource is targeted, what will change, which identity authorizes it, and what evidence should establish the outcome. Rollback availability depends on the action.
Generate a response when history does not fit
AutoSolve can reuse or adapt an applicable resolution. For unfamiliar problems it can generate a proposed response with AI, grounded in observed evidence and target facts. Generation is part of preparation: configured controls and approvals still govern execution. The operator can inspect the proposal and its requirements before proceeding.
Verify the service outcome
A command returning without error is not always the desired result. Define an action-specific check, such as the expected service state or diagnostic response, and inspect its evidence after execution. Failed or incomplete outcomes remain available for follow-up. When generated-plan retry is enabled, failure context can inform a bounded revision that requires fresh approval.
Build the cloud pilot around measurable work
Start with an agreed workload and target set. Establish existing hands-on minutes, incident volume, and the manual definition of completion. Test successful execution, denied access, missing prerequisites, and a failed verification. Compare verified resolutions and remaining human effort; expand only into environments whose ownership and execution boundaries are understood.
Questions before you connect
Does connecting a cloud account enable unrestricted execution?
No. Execution depends on the configured target, credentials, permissions, runtime requirements, and applicable policy.
Can AutoSolve generate a new cloud remediation?
It can generate and prepare a proposed solution using evidence and target context when a suitable existing solution does not match. Validation and approval requirements still apply.
How do we measure a cloud remediation pilot?
Agree on eligible issue types and measure verified resolutions, failed or held work, and human intervention against a manual baseline.