[Grafana](https://grafana.com/) allows you to query, visualize, alert on and understand your metrics no matter where they are stored. Create, explore, and share dashboards with your team and foster a data driven culture.

## Prerequisites

- Prometheus and MinIO configured as explained in [document here](https://github.com/minio/minio/blob/master/docs/metrics/prometheus/README.md).

- Target location from where the objects must be copied to
- Fine grained filtering is available to pick relevant objects from source to copy from

MinIO batch jobs framework also provides

- Retrying a failed job automatically driven by user input
- Monitoring job progress in real-time
- Send notifications upon completion or failure to user configured target

In most setups this is sufficient to heal the content after drive replacements. Setting `max_sleep` to a *lower* value and setting `max_io` to a *higher* value would make heal go faster.

If you have traditional spinning (hdd) drives, some applications with high concurrency might require MinIO cluster to be tuned such that to avoid random I/O on the drives. The way to convert high concurrent I/O into a sequential I/O is by reducing the number of concurrent operations allowed per cluster. This allows MinIO cluster to be operationally resilient to such workloads, while also making sure the drives are at optimal efficiency and responsive.

*Note*: Standalone MinIO is intended for early development and evaluation. For production clusters, deploy a [Distributed](https://min.io/docs/minio/container/operations/install-deploy-manage/deploy-minio-single-node-multi-drive.html) MinIO deployment.

### Homebrew (recommended)

Run the following command to install the latest stable MinIO package using [Homebrew](https://brew.sh/). Replace ``/data`` with the path to the drive or directory in which you want MinIO to store data.

```sh

- Run the Apache Spark Pi job in yarn-client mode, using code from **org.apache.spark**:

```
./bin/spark-submit --class org.apache.spark.examples.SparkPi \
    --master yarn-client \
    --num-executors 1 \
    --driver-memory 512m \
    --executor-memory 512m \
    --executor-cores 1 \
    examples/jars/spark-examples*.jar 10
```

The job should produce an output as shown below. Note the value of pi in the output.

```

1. The controller does not accept any dynamic user config through flags. All user interaction is through the
IstioOperator CR.
1. The controller has additional logic that mirrors istioctl commands like upgrade, but is driven from the declarative
API rather than command line.

### Quick tour of CLI commands

#### Flags

The `istioctl` command supports the following flags:

drives.  Therefore, the number of drives you present must be a multiple of one of these numbers.  Each object is written to a single erasure-coding set.

Minio uses the largest possible EC set size which divides into the number of drives given. For example, *18 drives* are configured as *2 sets of 9 drives*, and *24 drives* are configured as *2 sets of 12 drives*.  This is true for scenarios when running MinIO as a standalone erasure coded deployment. In [distributed setup however node (affinity)...

two parity drives, 100 MiB file takes only approximately 114 MiB.

Below is a list of data/parity drives and corresponding _approximate_ storage space usage on a 16 drive MinIO deployment. The field _storage
usage ratio_ is simply the drive space used by the file after erasure-encoding, divided by actual file size.

| Total Drives (N) | Data Drives (D) | Parity Drives (P) | Storage Usage Ratio |