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AlamLinux 9.4 install 설치하기

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almaLinux 로 포멧을 다시 진행하였고, 해당 과정을 간단하게 기록해본다.

기본 포멧 및 설치하기#

기본 패키지 업그레이드#

dnf upgrade

네트워크 인터페이스 잡기 (ONBOOT 수정)#

cd /etc/sysconfig/network-scripts/ vi ifcfg-enp70s0 DEVICE=enp70s0 BOOTPROTO=dhcp ONBOOT=yes

firewalld 비활성화#

systemctl stop firewalld systemctl disable firewalld

semanage 22960 port 추가#

dnf install policycoreutils-python-utils semanage port -a -t ssh_port_t -p tcp 22960

sshd port 변경#

cd /etc/ssh vim sshd_config Port 22960 PermitRootLogin yes systemctl restart sshd

디스크 마운트#

lsblk -f NAME FSTYPE FSVER LABEL UUID FSAVAIL FSUSE% MOUNTPOINTS sda ext4 1.0 b1f8274b-8367-46a3-af7a-9cc6415cebf8 nvme0n1 ├─nvme0n1p1 vfat FAT32 E636-00F9 591.8M 1% /boot/efi ├─nvme0n1p2 xfs 6784e138-f5c2-43b1-ad84-a977dfa9d206 683.4M 29% /boot └─nvme0n1p3 LVM2_member LVM2 001 kj7k6S-ph7v-BwDG-q3ad-tTph-OvTE-CR3pbI ├─almalinux_ollama--api-root xfs f260f019-aff5-419c-a402-7815b60da6a6 68G 3% / ├─almalinux_ollama--api-swap swap 1 ba20f638-52df-466a-b02a-f1ead179b24d [SWAP] └─almalinux_ollama--api-home xfs 732350a1-a9fc-4f37-83e7-c8147ad755e1 849.5G 1% /home nvme1n1 xfs 62a1faab-d641-4bc3-bacf-627f1f291c71 fdisk -l /dev/sda fdisk -l /dev/nvme1n1

폴더 생성하기#

mkdir /db mkdir /data

폴더에 디스크 마운트 하기#

mount /dev/nvme1n1 /db mount /dev/sda /data lsblk -f NAME FSTYPE FSVER LABEL UUID FSAVAIL FSUSE% MOUNTPOINTS sda ext4 1.0 b1f8274b-8367-46a3-af7a-9cc6415cebf8 8T 6% /data nvme0n1 ├─nvme0n1p1 vfat FAT32 E636-00F9 591.8M 1% /boot/efi ├─nvme0n1p2 xfs 6784e138-f5c2-43b1-ad84-a977dfa9d206 683.4M 29% /boot └─nvme0n1p3 LVM2_member LVM2 001 kj7k6S-ph7v-BwDG-q3ad-tTph-OvTE-CR3pbI ├─almalinux_ollama--api-root xfs f260f019-aff5-419c-a402-7815b60da6a6 68G 3% / ├─almalinux_ollama--api-swap swap 1 ba20f638-52df-466a-b02a-f1ead179b24d [SWAP] └─almalinux_ollama--api-home xfs 732350a1-a9fc-4f37-83e7-c8147ad755e1 849.5G 1% /home nvme1n1 xfs 62a1faab-d641-4bc3-bacf-627f1f291c71 868.6G 7% /db

/etc/fstab 수정 (자동 마운트)#

# auto-mount > 추가 설정 UUID=62a1faab-d641-4bc3-bacf-627f1f291c71 /db xfs defaults 0 0 UUID=b1f8274b-8367-46a3-af7a-9cc6415cebf8 /data ext4 defaults 0 0

재부팅 후 auto mount 잘 적용됬는지 아래 명령어로 확인#

reboot lsblk -f

저장소 추가#

dnf install dnf-plugins-core dnf install epel-release dnf config-manager --set-enabled crb

기본 패키지 설치#

dnf install vim htop net-tools iputils dnsutils curl wget rsync lsof ncdu which tcpdump unzip lsscsi bash-completion lm_sensors sensors-detect

기본 패키지 업그레이드#

dnf upgrade

현재 리눅스 및 커널 버전 확인#

hostnamectl Static hostname: (unset) Transient hostname: server.local Icon name: computer-desktop Chassis: desktop 🖥️ Machine ID: 474b2ef929ea40a9b94cad40ae267e9f Boot ID: 9109fff82bde405b80c6977b8be00840 Operating System: AlmaLinux 9.4 (Seafoam Ocelot) CPE OS Name: cpe:/o:almalinux:almalinux:9::baseos Kernel: Linux 5.14.0-427.18.1.el9_4.x86_64 Architecture: x86-64 Hardware Vendor: ASUS Hardware Model: ROG ZENITH II EXTREME ALPHA Firmware Version: 2102

cron.d 에 추가#

0 0 * * * /bin/sync && echo 1 > /proc/sys/vm/drop_caches

nvidia driver 설치하기#

설치하기#

https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#nvidia-open-gpu-kernel-modules 주소에 설치 방법이 나와있다.

dnf install tar bzip2 wget make automake gcc gcc-c++ pciutils elfutils-libelf-devel libglvnd-devel bind-utils kernel-headers kernel-devel freeglut-devel libX11-devel libXi-devel libXmu-devel mesa-libGLU-devel freeimage-devel libglfw3-devel lspci | grep VGA dnf config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel9/x86_64/cuda-rhel9.repo dnf module install nvidia-driver:open-dkms reboot nvidia-smi nvidia-smi nvlink --status

여기서 nvidia Persistence 모드 활성화를 해준다.

systemctl enable nvidia-persistenced systemctl start nvidia-persistenced

docker 설치하기#

설치하기#

dnf erase podman buildah dnf update dnf config-manager --add-repo https://download.docker.com/linux/rhel/docker-ce.repo dnf -y install docker-ce docker-ce-cli containerd.io docker-compose-plugin systemctl --now enable docker docker compose version docker --version docker network create frontend docker network create backend

nvidia-toolkit docker 설치하기#

https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html

curl -s -L https://nvidia.github.io/libnvidia-container/stable/rpm/nvidia-container-toolkit.repo | \ sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo dnf config-manager --set-enabled nvidia-container-toolkit-experimental dnf install -y nvidia-container-toolkit nvidia-ctk runtime configure --runtime=docker systemctl restart docker

성능 최적화#

TCP 튜닝#

/etc/sysctl.conf net.core.rmem_max = 16777216 net.core.wmem_max = 16777216 net.ipv4.tcp_rmem = 4096 87380 16777216 net.ipv4.tcp_wmem = 4096 65536 16777216 net.core.netdev_max_backlog = 5000 net.ipv4.tcp_window_scaling = 1 net.ipv4.tcp_moderate_rcvbuf = 1 net.ipv4.tcp_congestion_control = cubic sysctl -p

파일 디스크립터 한도 증가#

/etc/security/limits.conf * soft nofile 65536 * hard nofile 65536

이렇게 설치하면, 서버 컴퓨터의 리눅스 설치를 정상적으로 하게 된 것이다.

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