Deploy TrustGraph in a Scaleway Kubernetes cluster using Pulumi

Overview

This is an installation of TrustGraph on Scaleway using the Kubernetes platform.

The full stack includes:

• A Kubernetes cluster
• Node pool containing 2 nodes
• An IAM application plus policy granting Gen AI access
• Deploys a complete TrustGraph stack of resources in AKS

Keys and other configuration for the AI components are configured into TrustGraph using secrets.

The Pulumi configuration configures a Mistral nemo instruct endpoint.

How it works

This uses Pulumi which is a deployment framework, similar to Terraform but:

• Pulumi has an open source licence
• Pulumi uses general-purposes programming languages, particularly useful because you can use test frameworks to test the infrastructure.

Roadmap to deploy is:

• Install Pulumi
• Setup Pulumi
• Configure your environment with Scaleway credentials, generate an API key
• Modify the local configuration to do what you want
• Deploy
• Use the system

Setting the keys up from the API key looks like this...

export SCW_ACCESS_KEY=KEYGOESHERE
export SCW_SECRET_KEY=SECRETKEYGOESHERE
export SCW_DEFAULT_ORGANIZATION_ID=ORGKEYGOESHERE
export SCW_DEFAULT_PROJECT_ID=PROJECTKEYGOESHERE

Deploy

Deploy Pulumi

cd pulumi

Then:

npm install

Setup Pulumi

You need to tell Pulumi which state to use. You can store this in an S3 bucket, but for experimentation, you can just use local state:

pulumi login --local

Pulumi operates in stacks, each stack is a separate deployment. The git repo contains the configuration for a single stack scaleway, so you could:

pulumi stack init scaleway

and it will use the configuration in Pulumi.scalway.yaml.

Configure your environment with Scaleway credentials

In the console, create an API key for yourself and set the environment variables as instructed:

export SCW_ACCESS_KEY=xxxxxxxxxxxxxxx
export SCW_SECRET_KEY=xxxxxxxxxxxxxxx
export SCW_DEFAULT_ORGANIZATION_ID=xxxxxxxxxxxxxx
export SCW_DEFAULT_PROJECT_ID=xxxxxxxxxxxxxx

Modify the local configuration to do what you want

You can edit:

• settings in Pulumi.STACKNAME.yaml e.g. Pulumi.scaleway.yaml
• change resources.yaml with whatever you want to deploy. The resources.yaml file was created using the TrustGraph config portal, so you can re-generate your own.

The Pulumi.STACKNAME.yaml configuration file contains settings for:

• trustgraph-scaleway:region - Scaleway deployment location (e.g. fr-par).
• trustgraph-scaleway:environment - Name of the environment you are deploying use a name like: dev, prod etc.
• trustgraph-scaleway:ai-model - the AI model, look on the Generative AI page of the console to see other options. Try mistral-nemo-instruct-2407.

Deploy

pulumi up

Just say yes.

If everything works:

• A file kube.cfg will also be created which provides access to the Kubernetes cluster.

To connect to the Kubernetes cluster...

kubectl --kubeconfig kube.cfg -n trustgraph get pods

If something goes wrong while deploying, retry before giving up. pulumi up is a retryable command and will continue from where it left off.

Use the system

To get access to TrustGraph using the kube.cfg file, set up some port-forwarding. You'll need multiple terminal windows to run each of these commands:

kubectl --kubeconfig kube.cfg -n trustgraph port-forward service/api-gateway 8088:8088
kubectl --kubeconfig kube.cfg -n trustgraph port-forward service/workbench-ui 8888:8888
kubectl --kubeconfig kube.cfg -n trustgraph port-forward service/grafana 3000:3000

This will allow you to access Grafana and the Workbench UI from your local browser using http://localhost:3000 and http://localhost:8888 respectively.

Deploy

pulumi destroy

Just say yes.

How the config was built

There's an AI model specified in config.json. Available AI models can be found in Scaleway docs.

The AI model specified in the config.json should match the model in the AI endpoint hostname specified in the Pulumi config.

rm -rf env
python3 -m venv env
. env/bin/activate
pip install --upgrade git+https://github.com/trustgraph-ai/trustgraph-templates@master
tg-configurator -t 1.6 -v 1.6.5 --platform scw-k8s -R > resources.yaml