Welcome To Cybernode

What is it for

Сybernode is designed to help Сyber decentralize and help its Heroes become Content Providers. After completing the installation, you will end up with the following endpoints served from your server:

rpc.bostrom.<yourdomain.ai> - for bostrom RPC endpoint
lcd.bostrom.<yourdomain.ai> - for bostrom LCD endpoint
grpc.bostrom.<yourdomain.ai> - for bostrom GRPC endpoint
ipfs.<yourdomain.ai> - for ipfs gateway endpoint
grafana.<yourdomain.ai> - for grafana monitor
index.<yourdomain.ai>- to interact with the index

All of them could be later added to the skill registry to be used as chain data provider in cyb.ai:

Requirements

Network: Static ip address, domain name directed to this IP
CPU: 6 cores
RAM: 32 GB
SSD: 4+ TB NVME SSD
Connection: 30+Mbps, Stable and low-latency connection
GPU: Nvidia GeForce (or Tesla/Titan/Quadro) with CUDA-cores; 4+ Gb of video memory*
Software: Ubuntu 20.04 LTS / 22.04 LTS
Optional: VPS for Grafana monitoring server (standard config for Cybernode includes automatic installation)

Domain name preparation

You will need a domain name to serve endpoints to the outer world. Use one of the domain name providers (like Namecheap) to buy one, and set up wildcard (*) forwarding to your server static ip:

If you are willing to use the second layer domain, set up wildcard forward for it as well.

!!!Applying a domain name to your server IP can take up to 1 day, keep this in mind if errors occur when launching cybernode!!!

Cybernode setup

To avoid possible misconfiguration issues and simplify the setup of $ENV, we recommend performing all the commands as root (here root - is literally root, not just a user with root privileges). For the case of a dedicated server for cybernode, it should be considered as ok from the security side.

Login as a root user

sudo -i

Third-party software

The main distribution unit for Cyber is a docker container. All images are in the default Dockerhub registry. To access the GPU from the container, Nvidia driver version 410+ and Nvidia docker runtime should be installed on the host system.

All commands below suppose amd64 architecture, as the different architectures commands may differ accordingly.

Install Docker

Copy the commands below and paste them into CLI.

Install packages to allow apt to use a repository over HTTPS:

sudo apt-get update
sudo apt install -y \
     apt-transport-https \
     ca-certificates \
     curl \
     gnupg-agent \
     software-properties-common

Add Docker’s official GPG key:

sudo install -m 0755 -d /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg
sudo chmod a+r /etc/apt/keyrings/docker.gpg

echo \
  "deb [arch="$(dpkg --print-architecture)" signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
  "$(. /etc/os-release && echo "$VERSION_CODENAME")" stable" | \
  sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

Update the apt package index:
```
sudo apt-get update
```

Install the latest version of Docker CE and containerd:

sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

Install docker-compose

Download latest version of binary from docker-compose releases page or just do the following(asssuming that you have x86-64 architecture):

wget https://github.com/docker/compose/releases/latest/download/docker-compose-linux-x86_64
chmod +x docker-compose-linux-x86_64
mv docker-compose-linux-x86_64 /usr/local/bin/docker-compose

To check docker-compose is working correctly, run:

docker-compose version

You should get a reply with the version you have installed.

Install Nvidia drivers

To proceed, first add the ppa:graphics-drivers/ppa repository:

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update

Install Ubuntu drivers:

sudo apt install -y ubuntu-drivers-common

Next, check what is recommended drivers for your card:

ubuntu-drivers devices

You should see something similar to this:

== /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 ==
modalias : pci:v000010DEd00001BA1sv00001462sd000011E4bc03sc00i00
vendor   : NVIDIA Corporation
model    : GP104M [GeForce GTX 1070 Mobile]
driver   : nvidia-driver-418 - third-party free
driver   : nvidia-driver-430 - third-party free
driver   : nvidia-driver-440 - third-party free
driver   : nvidia-driver-460 - third-party free recommended
driver   : xserver-xorg-video-nouveau - distro free builtin

We need the 410+ drivers release. As you can see the v460 is recommended. The command below will install the recommended version of the drivers:

sudo ubuntu-drivers autoinstall

To install a specific version of a driver, use sudo apt install nvidia-driver-460

The driver installation takes approximately 10 minutes.

DKMS: install completed.
Setting up libxdamage1:i386 (1:1.1.4-3) ...
Setting up libxext6:i386 (2:1.3.3-1) ...
Setting up libxfixes3:i386 (1:5.0.3-1) ...
Setting up libnvidia-decode-415:i386 (460.84-0ubuntu0~gpu18.04.1) ...
Setting up build-essential (12.4ubuntu1) ...
Setting up libnvidia-gl-415:i386 (460.84-0ubuntu0~gpu18.04.1) ...
Setting up libnvidia-encode-415:i386 (460.84-0ubuntu0~gpu18.04.1) ...
Setting up nvidia-driver-415 (460.84-0ubuntu0~gpu18.04.1) ...
Setting up libxxf86vm1:i386 (1:1.1.4-1) ...
Setting up libglx-mesa0:i386 (18.0.5-0ubuntu0~18.04.1) ...
Setting up libglx0:i386 (1.0.0-2ubuntu2.2) ...
Setting up libgl1:i386 (1.0.0-2ubuntu2.2) ...
Setting up libnvidia-ifr1-415:i386 (460.84-0ubuntu0~gpu18.04.1) ...
Setting up libnvidia-fbc1-415:i386 (460.84-0ubuntu0~gpu18.04.1) ...
Processing triggers for libc-bin (2.27-3ubuntu1) ...
Processing triggers for initramfs-tools (0.130ubuntu3.1) ...
update-initramfs: Generating /boot/initrd.img-4.15.0-45-generic

Reboot the system for the changes to take effect.
```
sudo reboot
```

Check the installed drivers:

nvidia-smi

You should see this: (Some version/driver numbers might differ. You might also have some processes already running)

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.84       Driver Version: 460.84       CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 1070    Off  | 00000000:01:00.0 Off |                  N/A |
| 26%   36C    P5    26W / 180W |      0MiB /  8119MiB |      2%      Default |
+-------------------------------+----------------------+----------------------+  
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

Install Nvidia container runtime for docker

Add package repositories:

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
      && curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
      && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \
            sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
            sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

Install nvidia-container toolkit and reload the Docker daemon configuration

sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker

Test nvidia-smi with the latest official CUDA image

docker run --gpus all nvidia/cuda:11.4.0-base nvidia-smi

Output logs should coincide as earlier:

Unable to find image 'nvidia/cuda:11.4.0-base' locally
11.1-base: Pulling from nvidia/cuda
54ee1f796a1e: Pull complete 
f7bfea53ad12: Pull complete 
46d371e02073: Pull complete 
b66c17bbf772: Pull complete 
3642f1a6dfb3: Pull complete 
e5ce55b8b4b9: Pull complete 
155bc0332b0a: Pull complete 
Digest: sha256:774ca3d612de15213102c2dbbba55df44dc5cf9870ca2be6c6e9c627fa63d67a
Status: Downloaded newer image for nvidia/cuda:11.1-base
Mon Jun 21 14:07:52 2021 
+------------------------------------------------------------------------+
|NVIDIA-SMI 460.84      Driver Version:460.84      CUDA Version: 11.4    |
|-----------------------------+--------------------+---------------------+
|GPU  Name       Persistence-M| Bus-Id       Disp.A| Volatile Uncorr. ECC|
|Fan  Temp  Perf Pwr:Usage/Cap|        Memory-Usage| GPU-Util  Compute M.|
|                             |                    |               MIG M.|
|=============================+====================+=====================|
|  0  GeForce GTX165...  Off  |00000000:01:00.0 Off|                  N/A|
|N/A   47C    P0   16W /  N/A |      0MB /  3914MiB|      0%      Default|
|                             |                    |                  N/A|
+-----------------------------+--------------------+---------------------+                                                                 
+------------------------------------------------------------------------+
|Processes:                                                              |
| GPU   GI   CI       PID   Type   Process name                GPU Memory|
|       ID   ID                                                Usage     |
|========================================================================|
| No running processes found                                             |
+------------------------------------------------------------------------+

Your machine is ready to launch the cybernode.

Firewall setup

To make everything work, you will need to allow specific ports on your server firewall:

sudo ufw allow 80,443,26656,8090,3000,4001/tcp

Those are necessary for Nginx, node's p2p, and ipfs p2p connections. Also, if your server is behind a NAT router, remember to set up PORT mapping for the same ports.

Also, if you're installing Grafana on a separate machine, allow port 9090 to give access to the node's metrics.

Main part installation

Clone the repository

git clone https://github.com/cybercongress/cybernode.git && cd cybernode

To start cybernode, you must run the script and follow its instructions.

./start.sh

You can check the health of services using docker command

docker ps -a

Node snapshot application

To speed up the synchronization of the bostrom node, you may pull an archive snap from snapshot.cybernode.ai and check out the snapshot guide to get familiar with it.

Setup monitoring

If you decide to install Graphana on the same server as the cybernode, then be careful, because if the service fails, you may not know about it.

Go to your browser, and in the address bar, type: your-ip-address:3000
login - admin
password - admin

If you want, you can set your own password after this step

Next step: Add your first data source, select 'Prometheus' Type in the field "URL" address of your server with Prometheus and set the Name.
Then click Save & test. If everything is configured correctly, a green check mark will be displayed

For further work, you will need to find out your data source uid. It is located in your browser address bar Next step: import CyberNode dashboard to your text editor. https://github.com/cybercongress/cybernode/blob/master/grafana_dashboard
Then select the entire text with the ctrl + A command, turn on the search function with the ctrl + F command, find the string <PUT_YOUR_UID>, select it and replace it with your value from the previous step
Repeat the previous step only this time search for the string <PUT_YOUR_HOST_NAME> and replace it with your hostname
After that, import your JSON file and click Load button
Set the Name and click Import and you can notice how the graphs have come to life:

Setting alerts

If you want to set up alerts to always be aware of your cybernode's work, then select the schedule that interests you and click the edit button:

You will see the advanced settings of a specific schedule:

Select an alert
Edit all the fields that interest you
Save before exiting

You may use variable options to receive alerts, including email, Telegram or even calls.

Congrats

It seems like you did it! Open your cybernode endpoints in browser to verify them working correctly. You should have:

https://rpc.bostrom.<yourdomain.ai>
https://lcd.bostrom.<yourdomain.ai>
https://grpc.bostrom.<yourdomain.ai>
https://ipfs.<yourdomain.ai>/ipfs/CID
https://grafana.<yourdomain.ai>/login
https://index.<yourdomain.ai>/console

In case of any questions, do not hesitate to ask them in our Telegram channel for cyber Heroe's.

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

cybernode_manual.md

cybernode_manual.md

Welcome To Cybernode

What is it for

Requirements

Domain name preparation

Cybernode setup

Third-party software

Install Docker

Install docker-compose

Install Nvidia drivers

Install Nvidia container runtime for docker

Firewall setup

Main part installation

Node snapshot application

Setup monitoring

Setting alerts

Congrats

Files

cybernode_manual.md

Latest commit

History

cybernode_manual.md

File metadata and controls

Welcome To Cybernode

What is it for

Requirements

Domain name preparation

Cybernode setup

Third-party software

Install Docker

Install docker-compose

Install Nvidia drivers

Install Nvidia container runtime for docker

Firewall setup

Main part installation

Node snapshot application

Setup monitoring

Setting alerts

Congrats