## 1. Prerequisites

- Familiarity with [MinIO deployment process on Kubernetes](https://min.io/docs/minio/kubernetes/upstream/operations/installation.html).

- Kubernetes cluster with `kubectl` configured.

- Acquire TLS certificates, either from a CA or [create self-signed certificates](https://min.io/docs/minio/kubernetes/upstream/operations/network-encryption.html).

| `rootPassword`          | `rootPassword`         | Root password. | yes      |

All corresponding variables will be ignored in values file.

### Configure TLS

cryptographically secure pseudo-random number generator ([CSPRNG](#csprng)). However, in the context of SSE, the MinIO server does not require that the CSPRNG generates values that are indistinguishable from truly random bit strings. Instead, it is sufficient if the generated values are unique - which is a weaker requirement. Nevertheless other parts - for example the TLS-stack - may require that CSPRNG-generated values are indistinguishable from truly random bit strings.

### Server-Side Encryption with...

These values are enabled using server's configuration or environment variables.

## Examples

### Configuring connection limit

and can heal one object at a time. For RAID, healing can be done only at the volume level which translates into high downtime. As MinIO encodes each object individually, it can heal objects incrementally. Storage servers once deployed should not require drive replacement or healing for the lifetime of the server. MinIO's erasure coded backend is designed for operational efficiency and takes full advantage of hardware acceleration whenever available.

![Erasure](https://github.com/minio/m...

Use the following commands to run a standalone MinIO server as a container.

Standalone MinIO servers are best suited for early development and evaluation. Certain features such as versioning, object locking, and bucket replication
require distributed deploying MinIO with Erasure Coding. For extended development and production, deploy MinIO with Erasure Coding enabled - specifically,

workloads typically interact with object stores in the same way they do with HDFS. These workloads rely on HDFS atomic rename functionality to complete writing data to the datastore. Object storage operations are atomic by nature and they do not require/implement rename API. The default S3A committer emulates renames through copy and delete APIs. This interaction pattern causes significant loss of performance because of the write amplification. _Netflix_, for example, developed two new staging committers...