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Wiztelemetry Tracing

OrganizationPopular
kubesphere
wiztelemetry-tracing

Use when working with WizTelemetry Tracing extension for KubeSphere, including installation, configuration, and tracing query API

Overview

Publisherkubesphere
Repositorykubesphere
Skill namewiztelemetry-tracing
Stars
17.1K
Forks
2.8K
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by kubesphere on GitHub. Read the source before you install it.

Installation

Install the Wiztelemetry Tracing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/kubesphere/kubesphere.git /tmp/kubesphere
mkdir -p .claude/skills
cp -r /tmp/kubesphere/skills/wiztelemetry-tracing .claude/skills/wiztelemetry-tracing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wiztelemetry Tracing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Wiztelemetry Tracing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Wiztelemetry Tracing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

WizTelemetry Tracing

Overview

WizTelemetry Tracing is an extension component in the KubeSphere Observability Platform that provides distributed tracing functionality based on the OpenTelemetry standard.

When to Use

  • Installing or configuring the WizTelemetry Tracing extension
  • Understanding tracing architecture (Generator + Operator + Collector + Agent)
  • Using the tracing query API to query traces, spans, service graphs
  • Configuring OpenTelemetry auto-instrumentation for applications

Components

ComponentDescriptionDefault Enabled
generatorWizTelemetry Tracing Generator: generates service graphs from tracing data (StatefulSet)true
operatorOpenTelemetry Operator: manages OpenTelemetry Collector and auto-instrumentationtrue
collectorOpenTelemetry Collector for WizTelemetry: receives traces, exports to Vector and OpenSearchtrue
agentWizTelemetry Tracing Agent: collects tracing data from local log files (DaemonSet)false
demoOpenTelemetry Demo: generates sample tracing data for demonstrationfalse

Dependencies

  • WizTelemetry Platform Service (whizard-telemetry): Required
  • OpenSearch (opensearch): Required

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

bash
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 WizTelemetry Tracing to?
Step 2: Get Latest Version (if not provided by user)

MUST do this to get the latest version:

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

This outputs the latest version (e.g., 1.0.6). Note this down - you'll use it in the InstallPlan.

Step 3: Get Generator Endpoint

Get a node IP from the target cluster:

bash
kubectl get nodes -o jsonpath='{.items[0].status.addresses[?(@.type=="ExternalIP")].address}' 2>/dev/null || \
kubectl get nodes -o jsonpath='{.items[0].status.addresses[?(@.type=="InternalIP")].address}'

This outputs a node IP (e.g., 192.168.1.100). Use this as the generator endpoint.

If multiple shards (e.g., generator.shardCount: 3), generate all endpoints:

bash
NODE_IP="<NODE_IP>"
for i in 0 1 2; do
  PORT=$((32318 + i))
  echo "  - http://${NODE_IP}:${PORT}"
done

Replace <NODE_IP> with the actual node IP from the previous command.

Step 4: Confirm Configuration with User

Before creating the InstallPlan, confirm the following with the user:

I'll install WizTelemetry Tracing with the following configuration:
- Version: <VERSION>
- Target clusters: <TARGET_CLUSTERS>
- Generator endpoint: http://<NODE_IP>:32318
- OpenSearch endpoint: <OPENSEARCH_ENDPOINT>

Do you want to proceed? (yes/no)

If user confirms, proceed to create the InstallPlan. If not, adjust the configuration based on user feedback.

Step 5: Create InstallPlan

CRITICAL: InstallPlan metadata.name MUST be wiztelemetry-tracing. DO NOT use any other name.

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.

Based on your selections:

  • Target clusters: User-confirmed cluster names
  • OpenSearch endpoint: User-provided (default: https://opensearch-cluster-data.kubesphere-logging-system.svc:9200)
  • OpenSearch credentials: User-provided (default user: admin)
Template
yaml
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: wiztelemetry-tracing
  namespace: kubesphere-system
spec:
  extension:
    name: wiztelemetry-tracing
    version: <VERSION>  # From Step 2
  enabled: true
  upgradeStrategy: Manual
  config: |
    global:
      generator:
        endpoints:
          - http://<HOST_NODE_IP>:32318
      storage:
        opensearch:
          auth:
            strategy: basic
            user: <OPENSEARCH_USER>
            password: <OPENSEARCH_PASSWORD>
          endpoints:
            - <OPENSEARCH_ENDPOINT>
    generator:
      shardCount: 1
      service:
        nodePort: 32318
  clusterScheduling:
    placement:
      clusters:
        - <TARGET_CLUSTERS>

Replace placeholders:

  • <VERSION>: From Step 2 (e.g., 1.0.6)
  • <HOST_NODE_IP>: Node IP from Step 3 (e.g., 192.168.1.100)
  • <OPENSEARCH_USER>: OpenSearch username
  • <OPENSEARCH_PASSWORD>: OpenSearch password
  • <OPENSEARCH_ENDPOINT>: OpenSearch endpoint (e.g., https://opensearch-cluster-data.kubesphere-logging-system.svc:9200)
  • <TARGET_CLUSTERS>: User-confirmed cluster names

Enable Agent (Log File Collection)

To enable tracing data collection from local log files, set agent.enabled: true in the config. This deploys a DaemonSet that scans log files and forwards traces to the generator.

Enable Demo

To enable the OpenTelemetry Demo (generates sample trace data), set demo.enabled: true in the config.

Send Traces to Tempo

To forward traces to Tempo instead of OpenSearch, modify the collector.collector.config:

yaml
collector:
  enabled: true
  collector:
    config: |
      exporters:
        otlp:
          endpoint: <TEMPO_DISTRIBUTOR_GRPC_ENDPOINT>
          headers:
            x-scope-orgid: wiztelemetry-tracing-ks
          tls:
            insecure: true
      service:
        pipelines:
          traces:
            exporters:
              - otlp
              - otlphttp

Multiple Generator Instances

To scale the generator for higher throughput, increase generator.shardCount and update global.generator.endpoints:

yaml
global:
  generator:
    endpoints:
      - http://<HOST_NODE_IP>:32318
      - http://<HOST_NODE_IP>:32319
      - http://<HOST_NODE_IP>:32320

generator:
  shardCount: 3
  service:
    nodePort: 32318

shardCount must match the number of endpoints in global.generator.endpoints. The nodePort of each shard increases in sequence starting from the configured service.nodePort.

Configuration Parameters

Global Parameters

DNS Service
ParameterTypeDefaultDescription
global.dnsServicestringcorednsDNS service name
Generator Global Parameters
ParameterTypeDefaultDescription
global.generator.endpointslist["http://<ip>:32318"]Endpoints of all generator shards. Tracing data is routed to different shards by traceId.
OpenSearch Storage Parameters
ParameterTypeDefaultDescription
global.storage.opensearch.auth.strategystringbasicAuth strategy
global.storage.opensearch.auth.userstringadminOpenSearch username
global.storage.opensearch.auth.passwordstringadminOpenSearch password
global.storage.opensearch.endpointslistOpenSearch endpoint URLs
global.storage.opensearch.index.prefixstringwiz-tracing-spanIndex prefix
global.storage.opensearch.index.timestringstring%Y.%m.%dIndex time format (strftime pattern)

Generator Parameters

ParameterTypeDefaultDescription
generator.shardCountint1Number of generator shards. Must equal the number of entries in global.generator.endpoints.
generator.image.tagstringv1.0.2Generator image tag
generator.image.imagePullPolicystringIfNotPresentImage pull policy
generator.service.nodePortint32318NodePort of the first shard. Subsequent shards use consecutive ports.
generator.resources.limits.cpustring2CPU limit
generator.resources.limits.memorystring2000MiMemory limit
generator.resources.requests.cpustring100mCPU request
generator.resources.requests.memorystring100MiMemory request

Operator Parameters

ParameterTypeDefaultDescription
operator.enabledbooltrueEnable OpenTelemetry Operator
operator.fullnameOverridestringwiztelemetry-tracing-operatorOverride name for the operator deployment

Collector Parameters

ISM Policy Parameters
ParameterTypeDefaultDescription
collector.ism_policy.enablebooltrueEnable OpenSearch Index State Management policy
collector.ism_policy.span_index_patternstring*wiz-tracing-span*Index pattern for span indices
collector.ism_policy.service_index_patternstring*wiz-tracing-service*Index pattern for service indices
collector.ism_policy.min_index_agestring7dMinimum index retention period
collector.ism_policy.span_index_priorityint9950Index priority for span indices
Collector Deployment Parameters
ParameterTypeDefaultDescription
collector.enabledbooltrueEnable OpenTelemetry Collector
collector.collector.modestringdeploymentDeployment mode (deployment or daemonset)
collector.collector.replicasint2Number of collector replicas
collector.collector.upgradeStrategystringautomaticUpgrade strategy

Agent Parameters

ParameterTypeDefaultDescription
agent.enabledboolfalseEnable Tracing Agent (DaemonSet)
agent.dockerRootDirstring/var/lib/dockerDocker root directory
agent.config.scanIntervalstring1mLog file scan interval
agent.config.deletionDelaystring5mDelay before deleting processed files
agent.config.logPathstring/app/logs/*/*trace*.logPath pattern for trace log files
agent.config.podLabelSelectormap{}Filter pods by label selector
agent.config.namespaceLabelSelectormap{}Filter namespaces by label selector
agent.config.includeNamespaceslist[]List of namespaces to include
agent.config.excludeNamespaceslist[]List of namespaces to exclude
agent.resources.limits.cpustring500mCPU limit
agent.resources.limits.memorystring500MiMemory limit
agent.resources.requests.cpustring10mCPU request
agent.resources.requests.memorystring10MiMemory request
agent.vector.resources.limits.cpustring2Vector sidecar CPU limit
agent.vector.resources.limits.memorystring2000MiVector sidecar memory limit
agent.vector.resources.requests.cpustring100mVector sidecar CPU request
agent.vector.resources.requests.memorystring100MiVector sidecar memory request

Demo Parameters

ParameterTypeDefaultDescription
demo.enabledboolfalseEnable OpenTelemetry Demo

Tracing Query API

Query Traces

bash
curl -X POST "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/traces" \
  -H "X-Remote-User: admin" \
  -H "Content-Type: application/json" \
  -d '{"condition": {}, "limit": 20}'

Query Spans

bash
curl -X POST "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/spans" \
  -H "X-Remote-User: admin" \
  -H "Content-Type: application/json" \
  -d '{"condition": {}, "limit": 20}'

Get Service Graph

bash
curl -X POST "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/servicegraphs" \
  -H "X-Remote-User: admin" \
  -H "Content-Type: application/json" \
  -d '{"condition": {"start": "<START_TIME>", "end": "<END_TIME>"}}'

Get Services

bash
curl -X GET "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/services" \
  -H "X-Remote-User: admin"

Get Tags

bash
curl -X GET "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/tags" \
  -H "X-Remote-User: admin"

Get Values by Tag

bash
curl -X GET "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/values?tags=span.kind&limit=100" \
  -H "X-Remote-User: admin"

Get Histogram

bash
curl -X GET "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/histogram?key=<KEY>&kind=1&interval=15m&startTime=<START>&endTime=<END>" \
  -H "X-Remote-User: admin"

Query Parameters:

ParameterTypeDescription
keystringThe key of node or edge
kindintHistogram kind: 1=RequestTotal, 2=RequestTimeAverage, 3=FailedRequestTotal, 4=ResponseTotal, 5=ResponseTimeAverage, 6=FailedResponseTotal
intervalstringTime interval (e.g., 15m, 1h, 1d)
startTimestringStart time in seconds since epoch
endTimestringEnd time in seconds since epoch

Get Associated Workloads

bash
curl -X GET "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/workloads?keys=<KEYS>&startTime=<START>&endTime=<END>" \
  -H "X-Remote-User: admin"

Query Parameters:

ParameterTypeDescription
keysstringComma-separated list of node keys
startTimestringStart time in seconds since epoch
endTimestringEnd time in seconds since epoch

Get/Set Apdex Thresholds

bash
# Get apdex thresholds
curl -X GET "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/apdex/thresholds?keys=<KEYS>" \
  -H "X-Remote-User: admin"

# Set apdex thresholds
curl -X PUT "http://whizard-telemetry-apiserver.extension-whizard-telemetry.svc:80/kapis/tracing.wiztelemetry.io/v1alpha1/apdex/thresholds" \
  -H "X-Remote-User: admin" \
  -H "Content-Type: application/json" \
  -d '{"serviceA:serviceB": 0.5}'

OpenTelemetry Auto-Instrumentation

Create Instrumentation Resource

bash
kubectl apply -f - <<EOF
apiVersion: opentelemetry.io/v1alpha1
kind: Instrumentation
metadata:
  name: my-instrumentation
spec:
  exporter:
    endpoint: http://wiztelemetry-tracing-collector.wiz-telemetry-tracing:4317
  propagators:
    - tracecontext
    - baggage
    - b3
  sampler:
    type: parentbased_traceidratio
    argument: "0.25"
  python:
    env:
      - name: OTEL_EXPORTER_OTLP_ENDPOINT
        value: http://wiztelemetry-tracing-collector.wiz-telemetry-tracing:4318
  dotnet:
    env:
      - name: OTEL_EXPORTER_OTLP_ENDPOINT
        value: http://wiztelemetry-tracing-collector.wiz-telemetry-tracing:4318
  go:
    env:
      - name: OTEL_EXPORTER_OTLP_ENDPOINT
        value: http://wiztelemetry-tracing-collector.wiz-telemetry-tracing:4318
EOF

Enable Instrumentation via Annotations

Add the following annotation to a pod or namespace:

LanguageAnnotation
Javainstrumentation.opentelemetry.io/inject-java: "true"
NodeJSinstrumentation.opentelemetry.io/inject-nodejs: "true"
Pythoninstrumentation.opentelemetry.io/inject-python: "true"
.NETinstrumentation.opentelemetry.io/inject-dotnet: "true"
Goinstrumentation.opentelemetry.io/inject-go: "true"
Apache HTTPDinstrumentation.opentelemetry.io/inject-apache-httpd: "true"
Nginxinstrumentation.opentelemetry.io/inject-nginx: "true"
SDK onlyinstrumentation.opentelemetry.io/inject-sdk: "true"

Annotation values:

  • "true" - inject from the namespace's Instrumentation resource
  • "my-instrumentation" - use a specific Instrumentation CR in the current namespace
  • "my-ns/my-instrumentation" - use an Instrumentation CR in a different namespace
  • "false" - do not inject

Extension Operations

Check Extension Status

bash
kubectl get installplan wiztelemetry-tracing
kubectl get extensions wiztelemetry-tracing

Check Component Status

bash
kubectl get statefulset -n wiz-telemetry-tracing
kubectl get deployment -n wiz-telemetry-tracing
kubectl get daemonset -n wiz-telemetry-tracing
kubectl get pods -n wiz-telemetry-tracing

Uninstall Extension

Uninstall from all clusters:

bash
kubectl delete installplan wiztelemetry-tracing

Uninstall from specific cluster:

To remove WizTelemetry Tracing from a specific cluster, update the InstallPlan by removing that cluster from clusterScheduling.placement.clusters:

yaml
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
  name: wiztelemetry-tracing
spec:
  extension:
    name: wiztelemetry-tracing
    version: <VERSION>
  enabled: true
  upgradeStrategy: Manual
  clusterScheduling:
    placement:
      clusters:
        - <REMAINING_CLUSTERS>  # Remove the cluster you want to uninstall from

Frequently asked questions

What does the Wiztelemetry Tracing AI skill do?

Use when working with WizTelemetry Tracing extension for KubeSphere, including installation, configuration, and tracing query API

Why use Wiztelemetry Tracing on TypingMind?

Because you install it once and use it with any model. Wiztelemetry Tracing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Wiztelemetry Tracing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kubesphere/kubesphere/tree/master/skills/wiztelemetry-tracing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wiztelemetry Tracing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Wiztelemetry Tracing?

As many as you like. As long as a model supports skills, you can use Wiztelemetry Tracing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Wiztelemetry Tracing AI skill free?

It is published on GitHub by kubesphere. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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