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Knative Serving

Use this skill when a task involves Knative Serving on Kubernetes, including designing or deploying serverless container workloads, converting Deployments to...
Use this skill when a task involves Knative Serving on Kubernetes, including designing or deploying serverless container workloads, converting Deployments to...
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未分类 clawhub v1.0.1 1 版本 99431.8 Key: 无需
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概述

Knative Serving

Use this skill for Knative Serving work on Kubernetes clusters. Prefer current cluster state over assumptions: inspect resources with kubectl and kn, then make the smallest manifest or command change that matches the user's deployment model.

Workflow

  1. Identify the scope: deploy/update, Deployment conversion, autoscaling, revision/traffic, networking, container runtime, or debugging.
  2. Check the cluster context before changing live resources:

```bash

kubectl config current-context

kubectl get ns

kubectl get ksvc,route,configuration,revision -A

```

  1. Prefer kn for fast operational changes and examples; prefer YAML plus kubectl apply when the user needs reviewable declarative config.
  2. For production manifests, keep all per-revision behavior under spec.template so Knative creates a new Revision for behavior-changing changes.
  3. Validate with status, conditions, and traffic targets, not only Pods:

```bash

kn service describe -n

kubectl get ksvc -n -o yaml

kubectl get revision -n

kubectl get route -n -o yaml

```

References

Read only the files needed for the task:

  • references/overview-and-crds.md: Serving resource model, CRD schema discovery, core objects, Serving API fields, and important labels/annotations.
  • references/kn-cli.md: kn CLI workflows for create, update, describe, revisions, traffic, domain, and service operations.
  • references/autoscaling.md: KPA/HPA, metrics, concurrency, RPS target, scale-to-zero, scale bounds, scale windows/delays, and autoscaling annotations.
  • references/container-settings.md: container image, ports, env, secrets/config, resources, probes, timeouts, volumes, private registries, multi-container, and queue-proxy implications.
  • references/revisions-and-traffic.md: immutable Revisions, rollout, pinning, tagging, splitting, rollback, and garbage collection.
  • references/networking.md: Route, ingress, external URL, cluster-local/private services, DomainMapping, default domains, TLS, ingress class, Kourier/Istio/Contour notes.
  • references/observability.md: Serving metrics, queue-proxy and autoscaler signals, logs, tracing, and config-observability/config-logging.
  • references/debugging.md: diagnosis flow, commands, condition interpretation, logs/events, and common error patterns.
  • references/common-errors.md: quick lookup table for frequent Knative Serving failures and fixes.

Defaults

  • Use Service (ksvc) for normal workloads; reach for lower-level Route/Configuration only when the user explicitly needs them.
  • Treat annotations under spec.template.metadata.annotations as Revision-scoped unless the reference says otherwise.
  • Treat cluster-local visibility as a label on the Service/Route/Kubernetes Service unless the live installed version says otherwise.
  • Do not list full CRD schemas in answers. Show how to inspect them with kubectl explain, kubectl get crd, and OpenAPI output.
  • When autoscaling is involved, state whether the setting is global ConfigMap, Operator config, or per-Revision annotation/spec field.
  • When debugging, follow the object chain: Service -> Route/Configuration -> Revision -> PodAutoscaler/ServerlessService -> Deployment/Pod -> ingress.

Safety

  • Do not assume kn can install Knative Serving or Eventing; use it for resource operations after Knative is installed.
  • Do not expose a private Service with DomainMapping unless the user explicitly wants that. A DomainMapping can make a private Service reachable through the mapped domain.
  • Do not assume metrics/logging/tracing export is enabled. Check config-observability, config-logging, and the cluster monitoring stack first.
  • Avoid setting low containerConcurrency as a generic fix. It can increase queueing, latency, and cold starts.
  • Do not mix KPA-only metrics with HPA-only metrics. KPA supports concurrency and rps; HPA handles CPU, memory, and custom metrics when configured.
  • For traffic changes, ensure traffic percentages sum to 100 before applying manifests or commands.

版本历史

共 1 个版本

  • v1.0.1 当前
    2026-06-01 12:53

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