Using kubernetes opentelemetry.io with projectcalico.org

Question

Pulumi · Accepted Answer

OpenTelemetry is an open-source project that provides a set of APIs, libraries, agents, and instrumentation to enable observability for cloud-native software. Project Calico, on the other hand, is an open-source networking and network security solution for containers, virtual machines, and native cloud services.

When combining OpenTelemetry with Calico in a Kubernetes environment, it typically means you are aiming to gain observability into the network traffic, including the ability to trace network calls, log network events, and monitor network performance within a Kubernetes cluster that uses Calico for networking.

To implement this with Pulumi, you would first set up a Kubernetes cluster with Calico as the networking plugin. Then you would deploy OpenTelemetry components into your cluster to collect telemetry data, such as traces and metrics.

Below is a program written in TypeScript using Pulumi to set up such an environment.

```typescript
import * as k8s from "@pulumi/kubernetes";

// Assuming that a Kubernetes cluster with Calico has been created and configured
// Now we set up OpenTelemetry components on this cluster.

// Define the namespace for OpenTelemetry components
const ns = new k8s.core.v1.Namespace("opentelemetry-namespace", {
    metadata: {
        name: "opentelemetry",
    },
});

// Apply OpenTelemetry Operator to handle deployment and management of OpenTelemetry components
const otelOperator = new k8s.yaml.ConfigFile("opentelemetry-operator", {
    file: "https://github.com/open-telemetry/opentelemetry-operator/releases/latest/download/opentelemetry-operator.yaml",
    namespace: ns.metadata.name,
}, { dependsOn: [ns] });

// Define an OpenTelemetry Collector to gather telemetry data across the cluster.
const otelCollector = new k8s.apiextensions.CustomResource("opentelemetry-collector", {
    apiVersion: "opentelemetry.io/v1alpha1",
    kind: "OpenTelemetryCollector",
    metadata: {
        namespace: ns.metadata.name,
        name: "opentelemetry-collector",
    },
    spec: {
        config: `
receivers:
  otlp:
    protocols:
      grpc:
      http:
exporters:
  logging:
    loglevel: debug
service:
  pipelines:
    traces:
      receivers: [otlp]
      exporters: [logging]
    metrics:
      receivers: [otlp]
      exporters: [logging]
    logs:
      receivers: [otlp]
      exporters: [logging]
`,
    },
}, { dependsOn: [otelOperator, ns] });

// Export the OpenTelemetry Collector's service name that one would use to send trace and metric data to
export const collectorServiceName = otelCollector.metadata.name;
```

This Pulumi program performs the following steps:

1. It sets up a Kubernetes namespace called `opentelemetry`. This namespace will host our OpenTelemetry components.
2. It then applies the OpenTelemetry Operator using a YAML configuration file directly from the OpenTelemetry Operator's GitHub release page. This operator assists in the management and deployment of OpenTelemetry components.
3. It creates an OpenTelemetry Collector custom resource that defines how data will be collected within your Kubernetes cluster. In this case, the collector is set up to receive telemetry via otlp (OpenTelemetry Protocol) on both gRPC and HTTP protocols and export the data in log format with a debug log level.

In this code, we're not specifically setting up Calico-related resources with Pulumi because Calico setup typically happens at cluster creation time, and it's often done through manual installation or as part of managed Kubernetes services like EKS or AKS, which support Calico out-of-the-box.

Remember that you should have a Kubernetes cluster with networking configured to use Calico before running this program, and you would need to have `@pulumi/kubernetes` package installed in your Pulumi project. You can find more information about how to work with Kubernetes resources using Pulumi in the [Pulumi Kubernetes documentation](https://www.pulumi.com/docs/reference/pkg/kubernetes/).

Keep in mind that while this program sets up the OpenTelemetry Collector, you will need to configure your Kubernetes workloads to send telemetry to the collector. This typically involves setting up instrumentation in your workloads or configuring agents that can automatically collect data on their behalf.