Talos Cluster Health: Ensure Your K8s Readiness

When you're embarking on the journey of creating Kubernetes clusters with the Talos Terraform provider, a common hurdle arises: ensuring your cluster is fully ready before you deploy critical applications or configurations. Imagine this: your Terraform script churns along, happily creating your Talos-managed Kubernetes cluster. It successfully retrieves the kubeconfig, a seemingly positive sign! But then, disaster strikes. Your subsequent helm_release or Kubernetes manifest resources fail because the API server isn't quite ready to accept connections. This is a frustrating scenario, and it often leads to messy workarounds.

The Problem with Waiting

The talos_cluster_kubeconfig resource, while essential for authentication, has a known quirk. It can return valid credentials before the Kubernetes API server is fully operational and ready to receive requests. This timing mismatch is precisely where downstream resources stumble. They try to interact with a cluster that, from their perspective, is still waking up. The result? Terraform apply failures, rollbacks, and a significant amount of debugging.

Current Workarounds: A Bit Clunky, Right?

To bridge this gap, users have historically turned to null_resource coupled with local-exec provisioners. This approach involves embedding shell scripts directly within your Terraform configuration to poll the cluster's health. Here’s a glimpse of what that often looks like:

resource "null_resource" "wait_for_cluster" {
  provisioner "local-exec" {
    command = <<-"EOT"
      for i in $(seq 1 60); do
        kubectl --kubeconfig <(echo '${talos_cluster_kubeconfig.this.kubeconfig_raw}') \
          get --raw /healthz && exit 0
        sleep 5
      done
      exit 1
    EOT
  }
  depends_on = [talos_cluster_kubeconfig.this]
}

While this gets the job done, it's far from ideal. Let's break down why:

• Not Idiomatic Terraform: Embedding shell scripts within your Terraform code feels like a detour. It breaks the declarative nature of Terraform and makes your configuration harder to read and maintain.
• External Dependencies: This method requires kubectl (or talosctl) to be installed and configured correctly on the machine running Terraform. This adds complexity, especially in CI/CD pipelines or team environments where everyone might have different setups.
• Cross-Platform Woes: Making these shell scripts work seamlessly across different operating systems, particularly Windows, can be a significant headache.
• Error Handling & State Management: Debugging script failures within local-exec can be challenging. Understanding the exact state of the cluster during a failure and managing that state within Terraform's own state file is also less than straightforward.
• Lack of Visibility: It's not always clear what exactly is being waited on. Is it the API server? Is it etcd? The null_resource approach offers limited insight into the underlying health checks.

These drawbacks highlight a clear need for a more integrated and robust solution. We need something that feels native to Terraform and leverages the Talos ecosystem directly.

Introducing talos_cluster_health: The Native Solution You Need

To address these challenges, we propose the introduction of a new data source: talos_cluster_health. This data source is designed to perform comprehensive health checks on your Talos-managed Kubernetes cluster, mirroring the functionality of the powerful talosctl health command. Crucially, it will block the Terraform apply process until the cluster is deemed healthy or a specified timeout is reached. This ensures that your subsequent resources only proceed when the cluster is truly ready to go.

Example Usage: Seamless Integration

Here’s how talos_cluster_health could be integrated into your Terraform configurations:

data "talos_cluster_health" "this" {
  client_configuration = talos_machine_secrets.this.client_configuration
  endpoints            = ["10.50.0.20"]
  control_plane_nodes  = ["10.50.0.20"]
  worker_nodes         = ["10.50.0.21", "10.50.0.22"]
  timeouts = {
    read = "10m"
  }
}

# Subsequent resources can now safely depend on the cluster's health
resource "helm_release" "cilium" {
  # ... your Helm release configuration ...
  depends_on = [data.talos_cluster_health.this]
}

In this example, the helm_release for Cilium is explicitly configured to depend on the talos_cluster_health data source. This ensures that Terraform won't attempt to deploy Cilium until the data source confirms the cluster is healthy. The endpoints, control_plane_nodes, and worker_nodes arguments provide the necessary information for the data source to probe your cluster's API endpoints and nodes. The timeouts block allows you to define how long Terraform should wait for the cluster to become healthy.

Proposed Schema: Granular Control and Visibility

To provide flexibility and clear feedback, the proposed schema for talos_cluster_health includes the following inputs and outputs:

Inputs:

Outputs:

This schema allows you to specify which nodes to check, whether to include Kubernetes API checks, and provides detailed output on the health status of individual nodes and the cluster's core components. This level of visibility is a significant improvement over the current workaround.

Comprehensive Health Checks

The talos_cluster_health data source will perform a suite of checks, ensuring that your cluster is not just