Deploy to Kubernetes

Deploy the gateway through different options that fit diverse infrastructure needs. Choose from a multi-platform binary for direct installation on various operating systems, or use a Docker image that integrates into containerized environments like Kubernetes. This flexibility lets teams deploy the gateway in ways that best fit their workflow on local machines, cloud platforms, or hybrid infrastructures.

Kubernetes offers popular container orchestration with wide adoption for its scalability, reliability, and powerful ecosystem. This ecosystem includes tools like Helm, which simplifies the deployment and management of Kubernetes workloads through a templated, versioned, and reusable configuration framework. Use Helm to package applications into charts and streamline complex workload deployments consistently across environments.

Grafbase provides a Helm chart to simplify gateway deployment. The GitHub Container Registry hosts it with Open Container Initiative (OCI) compliance. Find the chart and versions at:

https://ghcr.io/grafbase/helm-charts/gateway

The chart includes default installation configuration for quick gateway setup with minimal configuration. While functional and easy to start with, tune this setup to accommodate real use cases.

Follow these steps to install the default configuration and customize settings for:

1. Number of replicas
2. Auto-scaling
3. Compute resources
4. External federated schema
5. External configuration

Complete these prerequisites before deploying:

1. Kubernetes Cluster: Get access to a Kubernetes cluster. Set up a local cluster like kind if needed.
2. helm: Install Helm. Get started here.
3. kubectl: Install kubectl and point it to your cluster. Get started here.

Start running the gateway with:

helm install test oci://ghcr.io/grafbase/helm-charts/gateway --version <version>

Verify gateway operation:

kubectl get pods

Look for a running pod named test-gateway.

Use a Helm values file to customize your deployment:

# 1. number of desired replicas running
replicaCount: 2

# 2. auto-scaling behaviour
autoscaling:
  enabled: true
  minReplicas: 2
  maxReplicas: 10
  targetCPUUtilizationPercentage: 70
  targetMemoryUtilizationPercentage: 70

# 3. compute resources
resources:
  limits:
    cpu: 2
    memory: 2Gi
  requests:
    cpu: 1
    memory: 1Gi

# 4. and 5. External schema and configuration from cluster configmaps
gateway:
  externalConfig: true
  externalSchema: true
  args:
    - --config
    - /etc/grafbase/config/config.toml
    - --schema
    - /etc/grafbase/schema/schema.sdl
volumes:
  - name: configuration
    configMap:
      name: grafbase-gateway-configuration
  - name: schema
    configMap:
      name: grafbase-gateway-schema
volumeMounts:
  - name: configuration
    mountPath: /etc/grafbase/config
  - name: schema
    mountPath: /etc/grafbase/schema

This configuration:

1. Maintains 2 gateway replicas
2. Sets auto-scaling between 2 and 10 instances, scaling up at 70% CPU or memory usage
3. Allocates 1-2 CPU and 1-2GB memory per replica
4. Uses cluster configmaps for gateway configuration and federated schema, mounting them in specified paths

View all customizable values with:

helm show values oci://ghcr.io/grafbase/helm-charts/gateway --version <version>

To apply customizations:

1. Save your settings to a file
2. Run:

helm upgrade test oci://ghcr.io/grafbase/helm-charts/gateway --version <version> -f custom-values.yaml

Verify the deployment:

helm list

kubectl get pods