Large Language Model Operations Checklist Form
Large Language Model Operations Checklist Form — track readiness and ongoing operational practices for your LLM systems.
Model and version documentation
Record the model name, provider, and exact version or release identifier.
Document the intended use, supported tasks, and known limitations.
Keep model documentation and change history in a shared, maintained location.
Prompt and configuration management
Store production prompts and templates in version control.
Document configuration values, dependencies, and environment-specific settings.
Review and test prompt or configuration changes before release.
Data handling and privacy safeguards
Document what data is sent to the model and why it is needed.
Apply data minimization and remove or mask unnecessary sensitive content.
Review provider data retention, processing, and deletion practices.
Define retention and deletion procedures for prompts, outputs, and related logs.
Access control and security
Limit model, platform, and deployment access to authorized roles.
Use approved secret-management practices for service credentials and keys.
Review permissions regularly and remove access that is no longer needed.
Assess threats such as prompt injection, unsafe tool use, and data exposure.
Pre-deployment evaluation and testing
Define acceptance criteria and representative test cases for intended use.
Evaluate output quality, reliability, and relevant safety behaviors.
Test edge cases, failure modes, and misuse scenarios before release.
Record evaluation results, known risks, and release decisions.
Deployment and rollback readiness
Document the deployment process, release owner, and approval steps.
Validate the production environment and dependencies before release.
Prepare and test a rollback or traffic-disable procedure.
Define release health checks and criteria for halting or reversing deployment.
Production monitoring and logging
Monitor availability, latency, error rates, and model or provider failures.
Track output quality or other relevant performance indicators over time.
Configure alerts with clear thresholds and responsible responders.
Ensure logs are access-controlled and avoid retaining unnecessary sensitive content.
Cost and usage tracking
Track request volume, token usage, and provider or infrastructure costs.
Set usage or spending budgets and alert thresholds.
Review usage trends and investigate unexpected increases.
Identify practical controls for reducing unnecessary requests or compute.
Incident response and escalation
Document response steps for service outages, unsafe outputs, and data exposure concerns.
Define severity levels, escalation paths, and response contacts by role.
Provide a way to disable, limit, or route around affected functionality.
Record incident decisions, actions, and follow-up improvements.
Ownership, review cadence, and governance
Assign accountable owners for the model, service, and operational controls.
Set a recurring review cadence for performance, risks, and operational readiness.
Define governance approval and change-review responsibilities.
Reassess documentation and controls when the model, use, or provider changes.
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