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Installation using Helm
Prerequisites
You will need the below tools installed in order to deploy Swiftflow on premise :
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 Swiftflow 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 Swiftflow using Helm
Let’s assume that you want to deploy Swiftflow in the default kubernetes namespace and give the Helm release name “MY_RELEASE”. Let’s also assume that you have stored the Swiftflow Helm archive in the current directory and that the Docker repository for both Swiftflow 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
Swiftflow requires at least Java 8 installed on the target system and present in your PATH.
Request the Swiftflow 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 Swiftflow on premise.
Start Swiftflow
Make sure to properly configure your swiftflow.conf
configuration file (see the Admin guide).
Execute the below command to start swiftflow :
java -Dfile.encoding=UTF8 -jar swiftflow-api.jar
You can now access Swiftflow at http://localhost:9000/.