/vector

name: vector
description: Use when installing or configuring the WizTelemetry Data Pipeline (vector) extension for KubeSphere, which provides data collection, transformation, and routing for observability data including logs, auditing, events, and notifications

WizTelemetry Data Pipeline (Vector)

Overview

WizTelemetry Data Pipeline is an extension based on vector (https://vector.dev/) that provides the ability to collect, transform, and route observability data. It is a core dependency for other WizTelemetry extensions like Logging, Auditing, Events, and Notification.

When to Use

• Installing or configuring the WizTelemetry Data Pipeline extension
• Setting up data collection for logs, auditing, events, and notifications
• Configuring Vector sinks (OpenSearch)
• Managing Vector agent components

Installation

Prerequisites

**REQUIRED: Complete all steps in order before generating InstallPlan.**

Step 1: Get Available Clusters and Confirm Target

**⚠️ CRITICAL: DO NOT proceed until target clusters are determined.**

**Step 1.1: Get available clusters**

kubectl get clusters -o jsonpath='{.items[*].metadata.name}'

**Step 1.2: Determine target clusters**

• If user **explicitly specified** target clusters in the request → Use those clusters directly, proceed to Step 2
• If user **did NOT specify** target clusters → Ask user to confirm which clusters to deploy to, then proceed to Step 2

**Ask user (if not specified):**

Available clusters: host, dev
Which clusters do you want to deploy Vector to?

Step 2: Get OpenSearch Endpoint and Credentials (MUST DO)

• If user **already provided** OpenSearch endpoint and credentials in the request → Use those directly, proceed to Step 3
• If user **did NOT provide** → **You MUST ask user** for OpenSearch endpoint and credentials

**Ask user for (if not provided):**

1. **OpenSearch endpoint URL** (required)

• Example: `http://<node-ip>:30920` or `https://opensearch.example.com:9200`

2. **OpenSearch credentials** (required)

• Username (default: `admin`)
• Password

**DO NOT proceed to Step 3 until user provides both endpoint and credentials.**

Step 3: Get Latest Vector Version (if not provided by user)

**MUST do this to get the latest version:**

kubectl get extensionversions -l kubesphere.io/extension-ref=vector -o jsonpath='{range .items[*]}{.spec.version}{"\n"}{end}' | sort -V | tail -1

This outputs the latest version (e.g., `1.1.4`). Note this down - you'll use it in the InstallPlan.

Install Vector Extension

**⚠️ IMPORTANT: Complete prerequisite steps (1-3) BEFORE this step.**

**⚠️ CRITICAL: InstallPlan `metadata.name` MUST be `vector`. DO NOT use any other name.**

Based on your selections:

• **Target clusters**: Use the user-confirmed cluster names
• **OpenSearch endpoint**: User-provided endpoint
• **OpenSearch credentials**: User-provided username and password

**⚠️ CRITICAL: `config` field is YAML format. You MUST:**

• Use the config structure exactly as shown in the template
• **DO NOT** add configuration fields that are not shown in the template
• **DO NOT** modify the structure or hierarchy

**⚠️ CRITICAL: All placeholders MUST be replaced with actual values. DO NOT leave them as placeholders.**

Template

apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: vector
spec:
  extension:
    name: vector
    version: <VECTOR_VERSION>  # From Step 3
  enabled: true
  upgradeStrategy: Manual
  config: |
    agent:
      sinks:
        opensearch:
          auth:
            strategy: basic
            user: <OPENSEARCH_USER>
            password: <OPENSEARCH_PASSWORD>
          endpoints:
            - <OPENSEARCH_ENDPOINT>
  clusterScheduling:
    placement:
      clusters:
        - <TARGET_CLUSTERS>

**Replace placeholders:**

• `<VECTOR_VERSION>`: From Step 2 (e.g., `1.1.4`)
• `<OPENSEARCH_ENDPOINT>`: User-provided endpoint (e.g., `http://<node-ip>:30920`)
• `<OPENSEARCH_USER>`: User-provided username (default: `admin`)
• `<OPENSEARCH_PASSWORD>`: User-provided password
• `<TARGET_CLUSTERS>`: User-confirmed cluster names

**⚠️ DO NOT generate InstallPlan until all placeholders have real values.**

Wait for Deployment

**After applying InstallPlan, you MUST wait for deployment to complete:**

# Wait for Vector pods to be ready (on each cluster)
kubectl wait --for=condition=Ready pods -n kubesphere-logging-system -l app.kubernetes.io/instance=vector --timeout=300s

# Verify deployment status
kubectl get pods -n kubesphere-logging-system -l app.kubernetes.io/instance=vector

**Show deployment summary to user:**

• Which clusters Vector was deployed to
• OpenSearch endpoint used
• Pod status (Ready/Total)

Enable Metrics Export

apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: vector
spec:
  extension:
    name: vector
    version: <VECTOR_VERSION>  # From Step 2
  enabled: true
  upgradeStrategy: Manual
  config: |
    agent:
      sinks:
        opensearch:
          auth:
            strategy: basic
            user: <OPENSEARCH_USER>
            password: <OPENSEARCH_PASSWORD>
          endpoints:
            - <OPENSEARCH_ENDPOINT>
      exportMetrics:
        enabled: true
  clusterScheduling:
    placement:
      clusters:
        - <TARGET_CLUSTERS>

Configuration Parameters

Agent Parameters

| Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `agent.role` | string | "Agent" | Role identifier | | `agent.image.tag` | string | "0.53.0-debian" | Vector image tag | | `agent.resources.requests.cpu` | string | "100m" | CPU request | | `agent.resources.requests.memory` | string | "100Mi" | Memory request | | `agent.resources.limits.cpu` | string | "2000m" | CPU limit | | `agent.resources.limits.memory` | string | "2000Mi" | Memory limit | | `agent.service.ports` | list | see values.yaml | Service ports | | `agent.export