# How to Check Resource Utilization
Compare actual resource usage against specified requirements to identify jobs that exceeded their
limits.
## Quick Start
```bash
torc workflows check-resources <workflow_id>
```
Example output:
```
⚠ Found 2 resource over-utilization violations:
15 | train_model | Memory | 8.00 GB | 10.50 GB | +31.3%
15 | train_model | Runtime | 2h 0m 0s | 2h 45m 0s | +37.5%
```
## Show All Jobs
Include jobs that stayed within limits:
```bash
torc workflows check-resources <workflow_id> --all
```
## Check a Specific Run
For workflows that have been reinitialized multiple times:
```bash
torc workflows check-resources <workflow_id> --run-id 2
```
## Automatically Correct Requirements
Use the separate `correct-resources` command to automatically adjust resource allocations based on
actual resource measurements:
```bash
torc workflows correct-resources <workflow_id>
```
This command performs two types of corrections:
### Upscaling (over-utilized resources)
Analyzes completed and failed jobs to detect:
- **Memory violations** — Jobs using more memory than allocated
- **CPU violations** — Jobs using more CPU than allocated
- **Runtime violations** — Jobs running longer than allocated time
### Downsizing (under-utilized resources)
Analyzes successfully completed jobs (return code 0) to detect resources that are significantly
over-allocated. A resource is downsized only when:
- **All** jobs sharing that resource requirement completed successfully
- **All** jobs have peak usage data for that resource type
- The savings exceed minimum thresholds (1 GB for memory, 5 percentage points for CPU, 30 minutes
for runtime)
- **No** job sharing that resource requirement had a violation
Failed jobs are excluded from downsizing analysis because they may terminate early with
under-reported peak usage.
The command will:
- Calculate new requirements using actual peak usage data
- Apply a 1.2x safety multiplier to each resource (configurable)
- Update the workflow's resource requirements for future runs
Example:
```
Resource Correction Summary:
Workflow: 5
Jobs analyzed: 3
Resource requirements updated: 2
Upscale:
Memory corrections: 1
Runtime corrections: 1
CPU corrections: 1
Downscale:
Memory reductions: 2
Runtime reductions: 2
CPU reductions: 0
```
### Preview Changes Without Applying
Use `--dry-run` to see what changes would be made:
```bash
torc workflows correct-resources <workflow_id> --dry-run
```
### Correct Only Specific Jobs
To update only certain jobs (by ID). This filters both upscaling and downsizing:
```bash
torc workflows correct-resources <workflow_id> --job-ids 15,16,18
```
### Disable Downsizing
To only upscale over-utilized resources without reducing over-allocated ones:
```bash
torc workflows correct-resources <workflow_id> --no-downsize
```
### Custom Correction Multipliers
Adjust the safety margins independently (all default to 1.2x):
```bash
torc workflows correct-resources <workflow_id> \
--memory-multiplier 1.5 \
--cpu-multiplier 1.3 \
--runtime-multiplier 1.4
```
## Manual Adjustment
For more control, update your workflow specification with a buffer:
```yaml
resource_requirements:
- name: training
memory: 12g # 10.5 GB peak + 15% buffer
runtime: PT3H # 2h 45m actual + buffer
num_cpus: 7 # Enough for peak CPU usage
```
**Guidelines:**
- Memory: Add 10-20% above peak usage
- Runtime: Add 15-30% above actual duration
- CPU: Round up to accommodate peak percentage (e.g., 501% CPU → 6 cores)
## See Also
- [Resource Monitoring](../monitoring/resource-monitoring.md) — Enable and configure monitoring
- [Resource Requirements Reference](../reference/resources.md) — Specification format