Requirements

• Kubernetes. For local k8s development environment, we encourage you to use k3s/k3d lightweight k8s distro. Note you need to use k8s <=v1.21 by the moment.
• kubectl
• Kustomize (>=v4.2)
• helm (>=3.5.3)
• bash. If you are using MacOS to deploy using k3d on docker, you will find problems using zsh as shell while copy pasting :)

Local deployment

There currently are two ways to deploy Dandelion:

• Render and deploy Kustomize manifests
• Leverage ArgoCD to perform more advanced deploys. Check the specific docs here

Minimum Requirements

Network	CPU	RAM	DISK
Testnet	4vCPU	8GB	50gb
Mainnet	24vCPU	24GB	120gb

NOTE: vCPUs are recommended to be dedicated for the db synchronization to stay close to blokchain tip.

Setup local k3d

Assuming you are already running docker locally, and have both, kubectl and k3d binaries installed, you could create a k3d cluster like this (customize port mappings if you feel to):

CLUSTER_NAME=dandelion-dev
k3d cluster create \
  -p "80:80@loadbalancer" \
  -p "443:443@loadbalancer" \
  ${CLUSTER_NAME}
kubectl config use-context k3d-${CLUSTER_NAME}
kubectl get pods -A

You can also export the kubeconfig file from k3d like this:

CLUSTER_NAME=dandelion-dev
k3d kubeconfig merge ${CLUSTER_NAME} --output ~/.kube/dandelion-dev.yaml

So in case you have different clusters and don't want to deal with contexts (having a single huge kubeconfig file, you can choose which cluster/file to use like this:

export KUBECONFIG=$HOME/.kube/dandelion-dev.yaml
kubectl get pods -A

Clone this repository

• For example, using command line like this:

mkdir Projects
cd Projects
git clone https://gitlab.com/gimbalabs/dandelion/kustomize-dandelion

• Then enter the directory and execute the following steps from there:

cd kustomize-dandelion

Render k8s manifests

Before directly rendering an overlay, you might want to enable/disable some components (rosetta, postgrest...) by removing the corresponding bases from the kustomization.yaml in the overlay dir.

You need to execute this from the top dir of this git repository:

# OVERLAY=mainnet-full
OVERLAY=iohk-preprod-full
OUTPUT_FILE=overlays/${OVERLAY}/output.yaml # this will contain the whole deploy manifest
kustomize build \
  --enable-helm \
  overlays/${OVERLAY} > overlays/${OVERLAY}/output.yaml

Deploy k8s manifests

You need to execute one of these options from the top dir of this git repository:

• A) Using plain kubectl:

# NAMESPACE=dandelion-mainnet
# OVERLAY=mainnet-full
NAMESPACE=dandelion-iohk-preprod
OVERLAY=iohk-preprod-full
kubectl get ns ${NAMESPACE} || kubectl create ns ${NAMESPACE}
kubectl apply --validate=false -n ${NAMESPACE} -f overlays/${OVERLAY}/output.yaml

• B) Using convenient kapp tool to get diff between local manifests and currently deployed ones in cluster:

# NAMESPACE=dandelion-mainnet
# OVERLAY=mainnet-full
OVERLAY=iohk-preprod-full
NAMESPACE=dandelion-${OVERLAY}
APP_NAME=${NAMESPACE}
kubectl get ns ${NAMESPACE} || kubectl create ns ${NAMESPACE}
kapp deploy -c \
  --app ${APP_NAME} \
  --namespace ${NAMESPACE} \
  --file overlays/${OVERLAY}/output.yaml

Enable your deployment to be exposed behind the community service

Execute this from the top dir of this git repository:

• Deploy testnet ingresses:

NETWORK=iohk-preprod
NAMESPACE=dandelion-${NETWORK}
kubectl apply -n ${NAMESPACE} -f base/dandelion-${NETWORK}-public-ingresses/ingress.yaml

• Deploy mainnet ingresses:

NETWORK=mainnet
NAMESPACE=dandelion-${NETWORK}
kubectl apply -n ${NAMESPACE} -f base/dandelion-${NETWORK}-public-ingresses/ingress.yaml

Deploy in multi-node

In order to deploy services into different kubernetes nodes/workers you can use the affinity-ready overlay ${NETWORK}-multi-node (check patches here). We've coupled some services (ie, db ones), decoupled some others (node and graphql) and let others to float around the cluster (any other "consumer" API). Besides the services label below, you'll also need to add the corresponding network label to your workers: k8s.dandelion.link/cardano-network=mainnet.

Role	Services	Label	Recommended Node Size (mainnet)	Recommended Node Size (testnet)
db-main	postgres, pgpool, cardano-db-sync	k8s.dandelion.link/role=db-main	4vCPU/16gb RAM	2vCPU/2gb RAM
cardano-graphql	cardano-graphql	k8s.dandelion.link/role=cardano-graphql	4vCPU/8gb RAM	2vCPU/2gb RAM
cardano-node	cardano-node	k8s.dandelion.link/role=cardano-node	4vCPU/8gb RAM	2vCPU/2gb RAM
observability	prometheus, grafana, loki	k8s.dandelion.link/role=observability	2x 2vCPU/2gb RAM	2vCPU/2gb RAM

Usage

Given that everything is listening on localhost we need to specify Host headers for the requests to be properly routed by the Ingress (on k3d, traefik by default). If you prefer, you could fake these hostnames to point to 127.0.0.1 on your /etc/hosts (linux/darwin) file so you don't need to specify them for each request.

• Get available endpoints:

NAMESPACE=dandelion-iohk-preprod
kubectl get ingress -n ${NAMESPACE}

• Check postgres[t] db tables

ENDPOINT=postgrest-api.iohk-preprod.local
curl -kL -H "Host: ${ENDPOINT}" \
  https://localhost

• Check sync progress

ENDPOINT=graphql-api.iohk-preprod.local
curl -kL \
     -H "Host: ${ENDPOINT}" \
     -H 'Accept-Encoding: gzip, deflate, br' \
     -H 'Content-Type: application/json' \
     -H 'Accept: application/json' \
     --data-binary '{"query":"query cardanoDbSyncProgress {\n    cardanoDbMeta {\n        initialized\n        syncPercentage\n    }\n}\n"}' \
     'https://localhost/'

Operations

External database access

If you want to explore the db from outside the cluster (GUI tools, et al), you can expose postgres port locally:

NAMESPACE=dandelion-iohk-preprod
# get read-only user/pass
PGUSER=$(kubectl get secret/init0-postgresql-ha-pgpool-custom-users \
  -n ${NAMESPACE} \
  --template='{{ index .data "usernames" }}' | base64 -d)
PGPASSWORD=$(kubectl get secret/init0-postgresql-ha-pgpool-custom-users \
  -n ${NAMESPACE} \
  --template='{{ index .data "passwords" }}' | base64 -d)

echo "User: ${PGUSER} Pass: ${PGPASSWORD}"
# expose port
kubectl port-forward -n dandelion-iohk-preprod init0-postgresql-ha-postgresql-0 5432:5432

Start from the scratch:

• Destroy namespace

NAMESPACE=dandelion-iohk-preprod
kubectl delete ns ${NAMESPACE}

• Or even destroy the whole cluster

CLUSTER_NAME=dandelion-iohk-preprod
k3d cluster delete  ${CLUSTER_NAME}

• Just deploy again :)

Resync db only

NAMESPACE=dandelion-iohk-preprod

kubectl scale statefulset -n ${NAMESPACE} \
  --replicas=0 \
  cardano-db-sync init0-postgresql-ha-postgresql

kubectl delete pvc -n ${NAMESPACE} \
  dbsync-statedir-cardano-db-sync-0 \
  data-init0-postgresql-ha-postgresql-0

kubectl delete job --all -n ${NAMESPACE}

kubectl scale statefulset -n ${NAMESPACE} \
  --replicas=1 \
  cardano-db-sync init0-postgresql-ha-postgresql

for jobfile in base/cardano-db-sync/job-ro-user-create.yaml base/koios/job-deploy-koios-sql.yaml
do
  kubectl apply -n ${NAMESPACE} -f ${jobfile}
done

kubectl rollout restart deploy -n ${NAMESPACE} postgrest koios-api