The repository has been moved to a new organization and the latest progress is here，https://github.com/swanchain/go-computing-provider

Computing Provider

A computing provider is an individual or organization that participates in the decentralized computing network by offering computational resources such as processing power (CPU and GPU), memory, storage, and bandwidth. Their primary role is to execute tasks posted by users on the Lagrange platform.

Table of Content

Prerequisites
Install the Kubernetes
Install and config the Nginx
Install the Hardware resource-exporter
Install the Redis service
Build and config the Computing Provider
Install AI Inference Dependency(Optional)
Start the Computing Provider
CLI of Computing Provider

Prerequisites

Before you install the Computing Provider, you need to know there are some resources required:

Possess a public IP
Have a domain name (*.example.com)
Have an SSL certificate
Go version must 1.19+, you can refer here:

wget -c https://golang.org/dl/go1.19.7.linux-amd64.tar.gz -O - | sudo tar -xz -C /usr/local

echo "export PATH=$PATH:/usr/local/go/bin" >> ~/.bashrc && source ~/.bashrc

Install the Kubernetes

The Kubernetes version should be v1.24.0+

Install Container Runtime Environment

If you plan to run a Kubernetes cluster, you need to install a container runtime into each node in the cluster so that Pods can run there, refer to here. And you just need to choose one option to install the Container Runtime Environment

Option 1: Install the `Docker` and `cri-dockerd` （Recommended）

To install the Docker Container Runtime and the cri-dockerd, follow the steps below:

Install the Docker:
- Please refer to the official documentation from here.
Install cri-dockerd:
- cri-dockerd is a CRI (Container Runtime Interface) implementation for Docker. You can install it refer to here.

Option 2: Install the `Containerd`

Containerd is an industry-standard container runtime that can be used as an alternative to Docker. To install containerd on your system, follow the instructions on getting started with containerd.

Optional-Setup a docker registry server

If you are using the docker and you have only one node, the step can be skipped.

If you have deployed a Kubernetes cluster with multiple nodes, it is recommended to set up a private Docker Registry to allow other nodes to quickly pull images within the intranet.

Create a directory /docker_repo on your docker server. It will be mounted on the registry container as persistent storage for our docker registry.
```
sudo mkdir /docker_repo
sudo chmod -R 777 /docker_repo
```

Launch the docker registry container:

sudo docker run --detach \
--restart=always \
--name registry \
--volume /docker_repo:/docker_repo \
--env REGISTRY_STORAGE_FILESYSTEM_ROOTDIRECTORY=/docker_repo \
--publish 5000:5000 \
registry:2

Add the registry server to the node
- If you have installed the Docker and cri-dockerd(Option 1), you can update every node's configuration:
```
sudo vi /etc/docker/daemon.json
```
```
## Add the following config
"insecure-registries": ["<Your_registry_server_IP>:5000"]
```
Then restart the docker service
```
sudo systemctl restart docker
```
- If you have installed the containerd(Option 2), you can update every node's configuration:

[plugins."io.containerd.grpc.v1.cri".registry]
  [plugins."io.containerd.grpc.v1.cri".registry.mirrors]
    [plugins."io.containerd.grpc.v1.cri".registry.mirrors."<Your_registry_server_IP>:5000"]
      endpoint = ["http://<Your_registry_server_IP>:5000"]

[plugins."io.containerd.grpc.v1.cri".registry.configs]
  [plugins."io.containerd.grpc.v1.cri".registry.configs."<Your_registry_server_IP>:5000".tls]
      insecure_skip_verify = true

Then restart containerd service

sudo systemctl restart containerd

: the intranet IP address of your registry server.

Finally, you can check the installation by the command:

docker system info

Create a Kubernetes Cluster

To create a Kubernetes cluster, you can use a container management tool like kubeadm. The below steps can be followed:

Install the Network Plugin

Calico is an open-source networking and network security solution for containers, virtual machines, and native host-based workloads. Calico supports a broad range of platforms including Kubernetes, OpenShift, Mirantis Kubernetes Engine (MKE), OpenStack, and bare metal services.

To install Calico, you can follow the below steps, more information can be found here.

step 1: Install the Tigera Calico operator and custom resource definitions

kubectl create -f https://raw.githubusercontent.com/projectcalico/calico/v3.25.1/manifests/tigera-operator.yaml

step 2: Install Calico by creating the necessary custom resource

kubectl create -f https://raw.githubusercontent.com/projectcalico/calico/v3.25.1/manifests/custom-resources.yaml

step 3: Confirm that all of the pods are running with the following command

watch kubectl get pods -n calico-system

step 4: Remove the taints on the control plane so that you can schedule pods on it.

kubectl taint nodes --all node-role.kubernetes.io/control-plane-
kubectl taint nodes --all node-role.kubernetes.io/master-

If you have installed it correctly, you can see the result shown in the figure by the command kubectl get po -A

Note:

If you are a single-host Kubernetes cluster, remember to remove the taint mark, otherwise, the task can not be scheduled to it.
```
kubectl taint node ${nodeName}  node-role.kubernetes.io/control-plane:NoSchedule-
```

Install the NVIDIA Plugin

If your computing provider wants to provide a GPU resource, the NVIDIA Plugin should be installed, please follow the steps:

Install NVIDIA Driver.

Recommend NVIDIA Linux drivers version should be 470.xx+
Install NVIDIA Device Plugin for Kubernetes.

If you have installed it correctly, you can see the result shown in the figure by the command kubectl get po -n kube-system

Install the Ingress-nginx Controller

The ingress-nginx is an ingress controller for Kubernetes using NGINX as a reverse proxy and load balancer. You can run the following command to install it:

kubectl apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/controller-v1.7.1/deploy/static/provider/cloud/deploy.yaml

If you have installed it correctly, you can see the result shown in the figure by the command:

Run kubectl get po -n ingress-nginx

Run kubectl get svc -n ingress-nginx

Install and config the Nginx

Install Nginx service to the Server
```
sudo apt update
sudo apt install nginx
```
Add a configuration for your Domain name Assume your domain name is *.example.com
```
vi /etc/nginx/conf.d/example.conf
```

map $http_upgrade $connection_upgrade {
    default upgrade;
    ''      close;
}

server {
        listen 80;
        listen [::]:80;
        server_name *.example.com;                                           # need to your domain
        return 301 https://$host$request_uri;
        #client_max_body_size 1G;
}
server {
        listen 443 ssl;
        listen [::]:443 ssl;
        ssl_certificate  /etc/letsencrypt/live/example.com/fullchain.pem;     # need to config SSL certificate
        ssl_certificate_key  /etc/letsencrypt/live/example.com/privkey.pem;   # need to config SSL certificate

        server_name *.example.com;                                            # need to config your domain
        location / {
          proxy_pass http://127.0.0.1:<port>;   # Need to configure the Intranet port corresponding to ingress-nginx-controller service port 80 
          proxy_set_header Host $http_host;
          proxy_set_header Upgrade $http_upgrade;
          proxy_set_header Connection $connection_upgrade;
       }
}

Note:
- server_name: a generic domain name
- ssl_certificate and ssl_certificate_key: certificate for https.
- proxy_pass: The port should be the Intranet port corresponding to ingress-nginx-controller service port 80
Reload the Nginx config
```
sudo nginx -s reload
```
Map your "catch-all (wildcard) subdomain(*.example.com)" to a public IP address

Install Hardware resource-exporter

The resource-exporter plugin is developed to collect the node resource constantly, computing provider will report the resource to the Lagrange Auction Engine to match the space requirement. To get the computing task, every node in the cluster must install the plugin. You just need to run the following command:

cat <<EOF | kubectl apply -f -
apiVersion: apps/v1
kind: DaemonSet
metadata:
  namespace: kube-system
  name: resource-exporter-ds
  labels:
    app: resource-exporter
spec:
  selector:
    matchLabels:
      app: resource-exporter
  template:
    metadata:
      labels:
        app: resource-exporter
    spec:
      containers:
      - name: resource-exporter
        image: filswan/resource-exporter:v11.2.5
        imagePullPolicy: IfNotPresent
EOF

If you have installed it correctly, you can see the result shown in the figure by the command: kubectl get po -n kube-system

Install Redis service

Install the redis-server

sudo apt update
sudo apt install redis-server

Run Redis service:

systemctl start redis-server.service

Build and config the Computing Provider

Build the Computing Provider

Firstly, clone the code to your local:

git clone https://github.com/lagrangedao/go-computing-provider.git
cd go-computing-provider
git checkout v0.3.0

Then build the Computing provider follow the below steps:

make clean && make
make install

Update Configuration The computing provider's configuration sample locate in ./go-computing-provider/config.toml.sample

cp config.toml.sample config.toml

Edit the necessary configuration files according to your deployment requirements. These files may include settings for the computing-provider components, container runtime, Kubernetes, and other services.

[API]
Port = 8085                                     # The port number that the web server listens on
MultiAddress = "/ip4/<public_ip>/tcp/<port>"    # The multiAddress for libp2p
Domain = ""                                     # The domain name

RedisUrl = "redis://127.0.0.1:6379"           # The redis server address
RedisPassword = ""                            # The redis server access password

[LOG]
CrtFile = "/YOUR_DOMAIN_NAME_CRT_PATH/server.crt"   # Your domain name SSL .crt file path
KeyFile = "/YOUR_DOMAIN_NAME_KEY_PATH/server.key"       # Your domain name SSL .key file path

[LAG]
ServerUrl = "https://api.lagrangedao.org"     # The lagrangedao.org API address
AccessToken = ""                              # Lagrange access token, acquired from “https://lagrangedao.org  -> setting -> Access Tokens -> New token”

[MCS]
ApiKey = ""                                   # Acquired from "https://www.multichain.storage" -> setting -> Create API Key
BucketName = ""                               # Acquired from "https://www.multichain.storage" -> bucket -> Add Bucket
Network = "polygon.mainnet"                   # polygon.mainnet for mainnet, polygon.mumbai for testnet
FileCachePath = "/tmp"                        # Cache directory of job data

[Registry]                                    
ServerAddress = ""                            # The docker container image registry address, if only a single node, you can ignore
UserName = ""                                 # The login username, if only a single node, you can ignore
Password = ""                                 # The login password, if only a single node, you can ignore

Install AI Inference Dependency

It is necessary for Computing Provider to deploy the AI inference endpoint. But if you do not want to support the feature, you can skip it.

export CP_PATH=xxx
./install.sh

Start the Computing Provider

You can run computing-provider using the following command

export CP_PATH=xxx
nohup computing-provider run >> cp.log 2>&1 &

CLI of Computing Provider

Check the current list of tasks running on CP, display detailed information for tasks using -v
```
computing-provider task list 
```
Retrieve detailed information for a specific task using space_uuid
```
computing-provider task get [space_uuid]
```

Delete task by space_uuid

computing-provider task delete [space_uuid]

Getting Help

For usage questions or issues reach out to the Swan team either in the Discord channel or open a new issue here on GitHub.

License

Apache

lagrangedao / go-computing-provider

readme

Computing Provider

Table of Content

Prerequisites

Install the Kubernetes

Install Container Runtime Environment

Option 1: Install the `Docker` and `cri-dockerd` （Recommended）

Option 2: Install the `Containerd`

Optional-Setup a docker registry server

Create a Kubernetes Cluster

Install the Network Plugin

Install the NVIDIA Plugin

Install the Ingress-nginx Controller

Install and config the Nginx

Install Hardware resource-exporter

Install Redis service

Build and config the Computing Provider

Install AI Inference Dependency

Start the Computing Provider

CLI of Computing Provider

Getting Help

License

lagrangedao / go-computing-provider

readme

Computing Provider

Table of Content

Prerequisites

Install the Kubernetes

Install Container Runtime Environment

Option 1: Install the Docker and cri-dockerd （Recommended）

Option 2: Install the Containerd

Optional-Setup a docker registry server

Create a Kubernetes Cluster

Install the Network Plugin

Install the NVIDIA Plugin

Install the Ingress-nginx Controller

Install and config the Nginx

Install Hardware resource-exporter

Install Redis service

Build and config the Computing Provider

Install AI Inference Dependency

Start the Computing Provider

CLI of Computing Provider

Getting Help

License

Option 1: Install the `Docker` and `cri-dockerd` （Recommended）

Option 2: Install the `Containerd`