After Prometheus is configured, you can use Grafana to visualize MinIO metrics. Refer the [document here to setup Grafana with MinIO prometheus metrics](https://github.com/minio/minio/blob/master/docs/metrics/prometheus/grafana/README.md).

## List of metrics exposed by MinIO

- MinIO exports Prometheus compatible data by default as an authorized endpoint at `/minio/v2/metrics/cluster`. 

```
~ mc admin config set alias/ scanner
KEY:
scanner  manage namespace scanning for usage calculation, lifecycle, healing and more

ARGS:

The additional node specific metrics which include additional go metrics or process metrics are exposed at
`<Address for MinIO Node>/minio/v2/metrics/node`.

The additional bucket specific metrics which include additional go metrics or process metrics are exposed at
`<Address for MinIO Node>/minio/v2/metrics/bucket`.

The additional resource specific metrics which include additional go metrics or process metrics are exposed at

On the target bucket, `s3:PutObject` event shows `X-Amz-Replication-Status` status of `REPLICA` in the metadata. Additional metrics to monitor backlog state for the purpose of bandwidth management and resource allocation are exposed via Prometheus - see <https://github.com/minio/minio/blob/master/docs/metrics/prometheus/list.md> for more details.

### Sync/Async Replication

-   Continuous jobs (Run on every GitHub commit)
    -   Uses `pycpp.sh`
-   Presubmit jobs (Run on every GitHub PR)
    -   Uses `pycpp.sh`, `code_check_changed_files.sh`

These "env" files match up with an environment matrix that roughly covers:

-   Different Python versions
-   Linux, MacOS, and Windows machines (these pool definitions are internal)
-   x86 and arm64
-   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs