# core.solver.ReliabilityModel { #mlsysim.core.solver.ReliabilityModel }

```python
core.solver.ReliabilityModel()
```

Calculates Mean Time Between Failures (MTBF) and optimal checkpointing intervals.

This solver handles the reliability modeling of massive clusters, helping
determine the 'Goodput' of long-running training jobs. It identifies
the probability of a job failure before completion and calculates the
Young-Daly optimal interval to minimize wasted compute time.

Literature Source:
1. Young (1974), "A First-Order Approximation to the Optimum Checkpoint
   Interval."
2. Daly (2006), "A Higher Order Estimate of the Optimum Checkpoint
   Interval for Restart-Dump Strategy."

## Methods

| Name | Description |
| --- | --- |
| [solve](#mlsysim.core.solver.ReliabilityModel.solve) | Calculates reliability and checkpointing metrics for a fleet. |

### solve { #mlsysim.core.solver.ReliabilityModel.solve }

```python
core.solver.ReliabilityModel.solve(
    fleet,
    job_duration_hours,
    checkpoint_time_s=60.0,
)
```

Calculates reliability and checkpointing metrics for a fleet.