SkillsAdd

smithery/raphaelmansuy

knative-serving

Deploy serverless workloads with Knative Serving for scale-to-zero and autoscaling.

Installation

$ npx skills add smithery/raphaelmansuy --skill knative-serving
View on skills.sh ↗ Website ↗

Summary

  • Deploy serverless workloads with Knative Serving for scale-to-zero and autoscaling.
  • Use for creating Knative Services, configuring autoscaling, traffic splitting, and revisions.
  • Triggers on "knative service", "scale-to-zero", "serverless deployment", "ksvc", "knative autoscaling", "traffic splitting", or when deploying agents as serverless workloads.

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Also in this package

Other skills from smithery/raphaelmansuy.

npx skills add smithery/raphaelmansuy
docusaurus-expert 0 agentctl-cli 0

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 10,481 B
  • docs SUMMARY.md 375 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Knative Serving

Overview

Deploy AI agents as serverless workloads using Knative Serving, enabling automatic scale-to-zero and request-based autoscaling.

Knative Architecture

                    Request
                        │
                        ▼
┌─────────────────────────────────────────────────────────────┐
│                      Knative Service                        │
│  ┌───────────────────────────────────────────────────────┐  │
│  │  Route                                                │  │
│  │  • Traffic splitting between revisions                │  │
│  │  • A/B testing, canary deployments                    │  │
│  └───────────────────────────────────────────────────────┘  │
│                          │                                   │
│  ┌───────────────────────────────────────────────────────┐  │
│  │  Configuration                                        │  │
│  │  • Desired state specification                        │  │
│  │  • Creates new Revision on each update                │  │
│  └───────────────────────────────────────────────────────┘  │
│                          │                                   │
│  ┌───────────────────────────────────────────────────────┐  │
│  │  Revision (Immutable)                                 │  │
│  │  • Snapshot of code + config                          │  │
│  │  • Autoscaled via KPA/HPA                             │  │
│  └───────────────────────────────────────────────────────┘  │
└─────────────────────────────────────────────────────────────┘

Knative Service Definition

Basic Service

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: customer-support-agent
  namespace: agents
  labels:
    agentstack.io/agent-id: agt_abc123
    agentstack.io/project-id: prj_xyz789
    agentstack.io/framework: google-adk
spec:
  template:
    metadata:
      annotations:
        # Autoscaling configuration
        autoscaling.knative.dev/class: kpa.autoscaling.knative.dev
        autoscaling.knative.dev/metric: concurrency
        autoscaling.knative.dev/target: "10"
        autoscaling.knative.dev/min-scale: "0"
        autoscaling.knative.dev/max-scale: "100"
        autoscaling.knative.dev/scale-down-delay: "30s"
        # Container configuration
        autoscaling.knative.dev/initial-scale: "1"
    spec:
      containerConcurrency: 10
      timeoutSeconds: 300  # 5 minutes for LLM calls
      containers:
        - image: ghcr.io/raphaelmansuy/customer-support-agent:v1.0.0
          ports:
            - containerPort: 8080
              protocol: TCP
          env:
            - name: AGENT_ID
              value: "agt_abc123"
            - name: PROJECT_ID
              value: "prj_xyz789"
            - name: OPENAI_API_KEY
              valueFrom:
                secretKeyRef:
                  name: agent-secrets
                  key: OPENAI_API_KEY
          resources:
            requests:
              cpu: 100m
              memory: 512Mi
            limits:
              cpu: 2000m
              memory: 2Gi
          readinessProbe:
            httpGet:
              path: /health
              port: 8080
            initialDelaySeconds: 5
            periodSeconds: 5

Production Service with Queue-Proxy Config

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: enterprise-agent
  namespace: agents
  annotations:
    # Revision history limit
    serving.knative.dev/rolloutDuration: "120s"
spec:
  template:
    metadata:
      annotations:
        # Use HPA for production
        autoscaling.knative.dev/class: hpa.autoscaling.knative.dev
        autoscaling.knative.dev/metric: cpu
        autoscaling.knative.dev/target: "70"
        autoscaling.knative.dev/min-scale: "2"
        autoscaling.knative.dev/max-scale: "50"
        # Queue-proxy settings
        queue.sidecar.serving.knative.dev/resourcePercentage: "20"
    spec:
      containerConcurrency: 0  # Unlimited (use with HPA)
      timeoutSeconds: 600
      serviceAccountName: agent-runner
      containers:
        - image: ghcr.io/raphaelmansuy/enterprise-agent:v2.0.0
          ports:
            - containerPort: 8080
          resources:
            requests:
              cpu: 500m
              memory: 1Gi
            limits:
              cpu: 4000m
              memory: 4Gi
          volumeMounts:
            - name: model-cache
              mountPath: /cache
      volumes:
        - name: model-cache
          emptyDir:
            sizeLimit: 5Gi

Autoscaling Configuration

Concurrency-Based (KPA) - Default

Best for request-heavy workloads:

annotations:
  autoscaling.knative.dev/class: kpa.autoscaling.knative.dev
  autoscaling.knative.dev/metric: concurrency
  autoscaling.knative.dev/target: "10"       # Target concurrent requests per pod
  autoscaling.knative.dev/target-utilization-percentage: "70"

CPU-Based (HPA)

Best for compute-intensive agents:

annotations:
  autoscaling.knative.dev/class: hpa.autoscaling.knative.dev
  autoscaling.knative.dev/metric: cpu
  autoscaling.knative.dev/target: "70"       # Target CPU percentage

RPS-Based

For rate-limited scenarios:

annotations:
  autoscaling.knative.dev/class: kpa.autoscaling.knative.dev
  autoscaling.knative.dev/metric: rps
  autoscaling.knative.dev/target: "100"      # Target requests per second

Scale Bounds

annotations:
  autoscaling.knative.dev/min-scale: "0"     # Scale to zero (default)
  autoscaling.knative.dev/max-scale: "100"   # Maximum replicas
  autoscaling.knative.dev/initial-scale: "1" # Initial pods on deploy

Scale-Down Delay

Prevent thrashing:

annotations:
  autoscaling.knative.dev/scale-down-delay: "30s"    # Wait before scaling down
  autoscaling.knative.dev/stable-window: "60s"       # Stability window
  autoscaling.knative.dev/panic-window-percentage: "10"
  autoscaling.knative.dev/panic-threshold-percentage: "200"

Traffic Splitting

Canary Deployment

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: customer-support-agent
spec:
  template:
    metadata:
      name: customer-support-agent-v2
    spec:
      containers:
        - image: ghcr.io/raphaelmansuy/customer-support-agent:v2.0.0
  traffic:
    - revisionName: customer-support-agent-v1
      percent: 90
    - revisionName: customer-support-agent-v2
      percent: 10

Blue-Green Deployment

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: customer-support-agent
spec:
  template:
    metadata:
      name: customer-support-agent-green
    spec:
      containers:
        - image: ghcr.io/raphaelmansuy/customer-support-agent:v2.0.0
  traffic:
    # Route all traffic to previous version
    - revisionName: customer-support-agent-blue
      percent: 100
    # Tag new version for testing
    - revisionName: customer-support-agent-green
      percent: 0
      tag: green  # Accessible at green-<service>.<domain>

Rollout Complete Traffic

traffic:
  - revisionName: customer-support-agent-green
    percent: 100
  - revisionName: customer-support-agent-blue
    percent: 0

Private Services (Internal Only)

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: internal-agent
  labels:
    networking.knative.dev/visibility: cluster-local
spec:
  template:
    spec:
      containers:
        - image: ghcr.io/raphaelmansuy/internal-agent:v1.0.0

Domain Mapping

apiVersion: serving.knative.dev/v1beta1
kind: DomainMapping
metadata:
  name: support.agentstack.io
  namespace: agents
spec:
  ref:
    name: customer-support-agent
    kind: Service
    apiVersion: serving.knative.dev/v1

ConfigMaps for Global Settings

apiVersion: v1
kind: ConfigMap
metadata:
  name: config-autoscaler
  namespace: knative-serving
data:
  # Global defaults
  container-concurrency-target-default: "100"
  container-concurrency-target-percentage: "0.7"
  enable-scale-to-zero: "true"
  scale-to-zero-grace-period: "30s"
  scale-to-zero-pod-retention-period: "0s"
  stable-window: "60s"
  panic-window-percentage: "10.0"
  panic-threshold-percentage: "200.0"
  max-scale: "100"

Observability Integration

Enable Metrics

apiVersion: v1
kind: ConfigMap
metadata:
  name: config-observability
  namespace: knative-serving
data:
  metrics.backend-destination: prometheus
  metrics.request-metrics-backend-destination: prometheus
  metrics.opencensus-address: ""

Enable Tracing

apiVersion: v1
kind: ConfigMap
metadata:
  name: config-tracing
  namespace: knative-serving
data:
  backend: zipkin
  zipkin-endpoint: "http://zipkin.observability:9411/api/v2/spans"
  sample-rate: "0.1"

Resources

  • references/cold-start-optimization.md - Reducing cold start latency
  • references/kagent-integration.md - Integrating with kagent orchestrator
  • assets/service-template.yaml - Base service template