# Patterns to ignore when building packages.
# This supports shell glob matching, relative path matching, and
# negation (prefixed with !). Only one pattern per line.
.DS_Store
# Common VCS dirs
.git/
.gitignore
.bzr/
.bzrignore
.hg/
.hgignore
.svn/
# Common backup files
*.swp
*.bak
*.tmp
*~
# Various IDEs
.project
.idea/
*.tmproj
# OWNERS file for Kubernetes

# How to monitor MinIO server with Prometheus? [![Slack](https://slack.min.io/slack?type=svg)](https://slack.min.io)

MinIO is a high performance distributed object storage server, designed for large-scale private cloud infrastructure. MinIO is designed in a cloud-native manner to scale sustainably in multi-tenant environments. Orchestration platforms like Kubernetes provide perfect cloud-native environment to deploy and scale MinIO.

## MinIO Deployment on Kubernetes

There are multiple options to deploy MinIO on Kubernetes:

configuration using e.g. the `mc admin config` commands you will need to adjust
your deployment.

Even though this change is backward compatible we do not expect that it affects
the vast majority of deployments in any negative way.

> Will an upgrade of an existing MinIO cluster impact the SLA of the cluster or will it even cause downtime?

No, an upgrade should not cause any downtime. However, on the first startup -

## Why is MinIO cloud-native?

# Metrics Version 3

In metrics version 3, all metrics are available under the endpoint:

```
/minio/metrics/v3
```

however, a specific path under this is required.

Metrics are organized into groups at paths **relative** to the top-level endpoint above.

## Metrics Request Handling

Each endpoint below can be queried at different intervals as needed via a scrape configuration in Prometheus or a compatible metrics collection tool.

# **Disaggregated HDP Spark and Hive with MinIO**

## **1. Cloud-native Architecture**

![cloud-native](https://github.com/minio/minio/blob/master/docs/bigdata/images/image1.png?raw=true "cloud native architecture")

Kubernetes manages stateless Spark and Hive containers elastically on the compute nodes. Spark has native scheduler integration with Kubernetes. Hive, for legacy reasons, uses YARN scheduler on top of Kubernetes.