Platform/Monitoring

AI App Monitoring & Observability

Logs, traces, and performance metrics out of the box — proactively monitored and investigated by AI so you can catch issues before your users do.

What’s included

  • Built-in monitoring that's already optimized for your application
  • Structured logs with request and user context attached
  • Real-time metrics with performance dashboards
  • AI-powered alerting — anomalies surfaced and triaged automatically
  • No agents to install, no dashboards to configure — it's just on
23ms-12%

Observability from the beginning

Modelence is a full-stack framework. Observability isn’t a feature you bolt on — it’s inherent to the framework. Every method invocation, cron job, and database call is instrumented. No configuration needed. It’s just there.

And, importantly: the telemetry feeds straight into the AI agent. If there’s a problem, the agent doesn’t need you to describe it. It reads the signal itself — and fixes the issue.

All methods, already instrumented

Framework-level instrumentation means every method in your app is timed and logged the moment it's created. You'll know which methods are slow, which are failing, and how often — without writing any monitoring code.

All cron jobs checked in

Silent failures are a scheduled job's bread and butter. It fails at 3am, you don't notice until data is missing or a process is halted. In Modelence, every scheduled job is monitored: did it start, did it finish, how long did it take, what was the result. You'll know it failed before you go looking.

An AI agent that can see what’s wrong

When your Modelence app throws an uncaught exception, blows out memory, or an N+1 query is dragging performance — the AI agent doesn’t get a description of the problem. It has the actual telemetry. It reads the error. It traces the slow path. It proposes a fix — and applies it. On other builders, “fix my bug” means pasting an error into a chat box. On Modelence, the agent already knows what went wrong.

Infrastructure built for the job

Observability is only as good as the infrastructure underneath. Modelence runs on infrastructure designed for long-running workloads — not serverless functions that collapse under load. The observability system is tracking an app that is meant to keep running, not one that’s about to crash.

Guessing vs. knowing

The practical difference between an app with built-in observability and one without it.

When your app crashes
Without observability
You find out from a user. You guess at the cause.
With Modelence built-in
You see the exact exception, the stack trace, and when it started — before anyone emails you.
Slow queries
Without observability
Invisible. You notice when users complain about speed.
With Modelence built-in
Every method is timed. Slow paths surface automatically.
Memory spike
Without observability
App restarts. You have no idea why.
With Modelence built-in
The spike is logged, timestamped, and traceable to the offending job.
Cron job failure
Without observability
Silent. The task just doesn’t run.
With Modelence built-in
Every scheduled job is tracked. Failures are surfaced immediately.
Debugging a bug
Without observability
Copy logs from one tool, paste into another. Guess.
With Modelence built-in
The AI agent reads your telemetry directly and tells you what went wrong.
Cost of fixing it
Without observability
Hundreds in burned credits. Weeks of time.
With Modelence built-in
Actionable. The agent sees the error and fixes it.

More from the platform

Authentication

Users, sessions, and roles built-in

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Database

Enterprise-scale database, no setup

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Deployment

One-click deploys with auto-scaling

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