Install it (non GCP)

Note

The Helm values, the Docker repositories and the image names below use swiftflow, TxFlow’s original name. That is current and intended — keep them as written.

Installation using Helm

Prerequisites

You will need the below tools installed in order to deploy TxFlow on premise :

• helm
• kubectl
• docker

Request Helm package and Docker images

You can contact us on info@alpina-analytics.com in order to request the necessary archives (Helm package and Docker images) plus a dedicated license to deploy TxFlow on premise.

Install the Application resource definition

An Application resource is a collection of individual Kubernetes components, such as Services, Deployments, and so on, that you can manage as a group.

To set up your cluster to understand Application resources, run the following command:

kubectl apply -f "https://raw.githubusercontent.com/GoogleCloudPlatform/marketplace-k8s-app-tools/master/crd/app-crd.yaml"

You need to run this command once.

The Application resource is defined by the Kubernetes SIG-apps community. The source code can be found on github.com/kubernetes-sigs/application.

Deploy TxFlow using Helm

Let’s assume that you want to deploy TxFlow in the default kubernetes namespace and give the Helm release name “MY_RELEASE”. Let’s also assume that you have stored the TxFlow Helm archive in the current directory and that the Docker repository for both TxFlow and its data is “my.docker.repo/swiftflow”.

helm install \
  --set swiftflow.image.repo="my.docker.repo/swiftflow" \
  --set swiftflow.image.tag="1.0" \
  --set swiftflow.image.data.tag="1.0" \
  --set swiftflow.replicas=1 \
  --set swiftflow.serviceaccount="default" \
  --set swiftflow.resources.requests.cpu="100m" \
  --set swiftflow.resources.request.memory="2Gi"\
  --set swiftflow.resources.limits.cpu="2000m" \
  --set swiftflow.resources.limits.memory="4Gi"\
  --set imageNginx="nginx:1.19.9" \
  --set nominatim.local=false . MY_RELEASE \
  --set swiftflow.license="MY_LICENSE" \
  --set imageSqlite="swiftflow-sqlite:1.0"

Values references

Value	Description
swiftflow.image.repo	the repository url where you image is stored
swiftflow.image.tag	the swiftflow image tag you want to deploy
swiftflow.image.data.tag	the swiftflow data image tag you want to deploy
swiftflow.replicas	the number of pods hosting swiftflow API you want to deploy
swiftflow.serviceaccount	the service account name you want to be used by your Pods
swiftflow.resources.request.cpu	the CPU request for each swiftflow Pod
swiftflow.resources.request.memory	the Memory request for each swiftflow Pod
swiftflow.resources.limits.cpu	the CPU limits for each swiftflow Pod
swiftflow.resources.limits.memory	the Memory limit for each swiftflow Pod
swiftflow.persistence.storageClass	the storage class for the swiftflow Pod persistence volume claim
swiftflow.persistence.size	the swiftflow Pod persistence volume claim size
imageNginx	the fully qualified url of the Nginx image repository(repository + tag)
nominatim.local	selector for using a custom nominatim instance, should be false until this feature has been released with Swiftflow
swiftflow.license	license received by e-mail
imageSqlite	image version of the SQLite database

Installation as standalone application

Prerequisites

TxFlow requires at least Java 8 installed on the target system and present in your PATH.

Request the TxFlow jar and its data

You can contact us on info@alpina-analytics.com in order to request the necessary archives (Jar file and its location data file) plus a dedicated license to deploy TxFlow on premise.

Start Txflow

Make sure to properly configure your swiftflow.conf configuration file (see the Admin guide). Execute the below command to start TxFlow :

java -Dfile.encoding=UTF8 -jar swiftflow-api.jar

You can now access TxFlow at http://localhost:9000/.