1-3-deploy-tfs.md

1.3. Deploy TeraFlowSDN over MicroK8s

This section describes how to deploy TeraFlowSDN controller on top of MicroK8s using the environment configured in the previous sections.

1.3.1. Install prerequisites

sudo apt-get install -y git curl jq

1.3.2. Clone the Git repository of the TeraFlowSDN controller

Important: Right now, we have two repositories hosting the code of TeraFlowSDN: GitLab.com and ETSI owned GitLab repository. Nowadays, only GitLab.com repository accepts code contributions that are periodically mirrored to ETSI labs. In the near future, we plan to swap the repository roles and new contributions will be accepted only at ETSI labs, while GitLab.com will probably be kept as a mirror of ETSI. If you plan to contribute code to the TeraFlowSDN controller, by now, clone from GitLab.com. We will update the tutorial as soon as roles of repositories are swapped.

Clone from GitLab (if you want to contribute code to TeraFlowSDN):

mkdir ~/tfs-ctrl
git clone https://gitlab.com/teraflow-h2020/controller.git ~/tfs-ctrl

Clone from ETSI owned GitLab (if you do not plan to contribute code):

mkdir ~/tfs-ctrl
git clone https://labs.etsi.org/rep/tfs/controller.git ~/tfs-ctrl

1.3.3. Checkout the appropriate Git branch

By default 'master' branch is checked out. If you want to deploy 'develop' that incorporates the most up-to-date code contributions and features, run the following command:

cd ~/tfs-ctrl
git checkout develop

Important: During the elaboration and validation of the tutorials, you should checkout branch "feat/microk8s-deployment". Otherwise, you will not have important files such as "my_deploy.sh" or "deploy.sh". As soon as the tutorials are completed and approved, we will remove this note and merge the "feat/microk8s-deployment" into "develop" and later into "master", and then the previous step will be effective.

1.3.4. Prepare a deployment script with the deployment settings

Create a new deployment script, e.g., my_deploy.sh, adding the appropriate settings as follows. This script, by default, makes use of the private Docker registry enabled in MicroK8s, as specified in TFS_REGISTRY_IMAGE. It builds the Docker images for the subset of components defined in TFS_COMPONENTS, tags them with the tag defined in TFS_IMAGE_TAG, deploys them in the namespace defined in TFS_K8S_NAMESPACE, and (optionally) deploys the extra Kubernetes manifests listed in TFS_EXTRA_MANIFESTS. Besides, it lets you specify in TFS_GRAFANA_PASSWORD the password to be set for the Grafana admin user.

cd ~/tfs-ctrl
tee my_deploy.sh >/dev/null <<EOF
export TFS_REGISTRY_IMAGE="http://localhost:32000/tfs/"
export TFS_COMPONENTS="context device automation service compute monitoring webui"
export TFS_IMAGE_TAG="dev"
export TFS_K8S_NAMESPACE="tfs"
export TFS_EXTRA_MANIFESTS="manifests/nginx_ingress_http.yaml"
export TFS_GRAFANA_PASSWORD="admin123+"
EOF

1.3.5. Deploy TFS controller

First, source the deployment settings defined in the previous section. This way, you do not need to specify the environment variables in each and every command you execute to operate the TFS controller. Be aware to re-source the file if you open new terminal sessions. Then, run the following command to deploy TeraFlowSDN controller on top of the MicroK8s Kubernetes platform.

cd ~/tfs-ctrl
source my_deploy.sh
./deploy.sh

The script does the following steps:

1. Build the Docker images for the components defined in TFS_COMPONENTS
2. Tag the Docker images with the value of TFS_IMAGE_TAG
3. Push the Docker images to the repository defined in TFS_REGISTRY_IMAGE
4. Create the namespace defined in TFS_K8S_NAMESPACE
5. Deploy the components defined in TFS_COMPONENTS
6. Create the file tfs_runtime_env_vars.sh with the environment variables for the components defined in TFS_COMPONENTS defining their local host addresses and their port numbers.
7. Create an ingress controller listening at port 80 for HTTP connections to enable external access to the TeraFlowSDN WebUI, Grafana Dashboards, Context Debug endpoints, and Compute NBI interfaces.
8. Initialize and configure the Grafana dashboards
9. Report a summary of the deployment (see 1.5. Show Deployment and Log per Component)