LLM observability connects each model request to the route selected, attempts made, tokens used, cost incurred, latency experienced, and application outcome. It should let an operator answer what happened, why it happened, and what changed without exposing sensitive prompt content by default.
The INFRO view: INFRO unifies route, usage, latency, cost, and recovery data so multi-provider traffic can be operated as one system.
The minimum useful request trace
Every trace should carry a stable request ID, project or environment, model requested, route selected, attempt chain, status, input and output units, computed cost, time to first token, and total duration. Add application tags such as feature or tenant where policy allows them.
Raw prompts are not required for most operational questions. Metadata-first tracing reduces privacy exposure and makes retention decisions easier.
Metrics that reveal different failures
Availability, latency, cost, and quality fail independently, so one dashboard cannot collapse them into a single score.
- Reliability: final error rate, attempt count, fallback rate, and circuit state.
- Latency: queue time, provider connection time, time to first token, and total duration.
- Economics: input units, output units, media duration or frames, cache effects, and cost per successful task.
- Quality: schema validation, tool completion, user correction, escalation, and task-specific evaluation scores.
From metrics to decisions
A metric earns its place when it changes an action. Rising fallback rate should remove or investigate a route. Increasing cost per solved task should trigger model reevaluation. A malformed-output spike should stop a rollout even if status codes remain green.
Define service-level objectives around the user outcome, not provider uptime. A provider can be technically available while time-to-first-token makes the product unusable.
Privacy and retention
Classify trace fields by sensitivity. Keep operational metadata longer than content, redact secrets before logging, and provide a way to disable payload capture for regulated workloads. Access to traces should follow the same project and role boundaries as access to production keys.
Document the policy before the first incident. Emergency debugging is the worst time to decide who can read customer prompts.
Where INFRO fits
The INFRO console is designed around three questions: what happened to one request, whether a route or provider degraded, and where spend went. That shared ledger avoids reconciling incompatible dashboards after an incident.
See the console walkthrough, security page, and enterprise controls. During private early access, confirm retention and payload-handling requirements before sending sensitive production traffic.
Frequently asked questions
What is LLM observability?
It is the practice of tracing model requests across application, gateway, model, cost, latency, and outcome so operators can explain and improve production behavior.
Do I need to store prompts for observability?
No. Route, timing, usage, error, and application metadata answer many operational questions without retaining raw content.
How does INFRO help with LLM monitoring?
INFRO records requests across supported models and routes in one operational view, including routing, latency, usage, cost, and eligible failover activity.
