MR
Mayur Rathi
@sickn33
⭐ 47.3k GitHub stars

service-mesh

service-mesh is an engineering AI skill with a core value of Implement Istio and Linkerd service meshes. It helps developers solve real-world problems in the engineering domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

Implement Istio and Linkerd service meshes. Configure mTLS, traffic management, and observability. Use when managing microservices communication.

Last verified on: 2026-10-06

Quick Facts

Category engineering
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 47.3k
Last Verified 2026-10-06
Risk Level Low
mkdir -p ./skills/service-mesh && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/service-mesh/SKILL.md -o ./skills/service-mesh/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Service Mesh


Implement service-to-service communication management with mTLS, traffic shaping, observability, and policy enforcement using Istio or Linkerd.


When to Use


- Securing microservice communication with automatic mTLS.

- Implementing canary deployments, traffic splitting, or A/B testing.

- Adding circuit breakers, retries, and timeouts without changing application code.

- Gaining service-level observability (latency, error rates, request volume).

- Enforcing authorization policies between services.


Prerequisites


- Kubernetes cluster (1.26+) with kubectl configured.

- Helm 3 installed (for some installation methods).

- Sufficient cluster resources (Istio control plane needs ~2 GB RAM).

- For Istio: `istioctl` CLI installed.

- For Linkerd: `linkerd` CLI installed.


Istio Installation


Install with istioctl


bash 
# Download istioctl
curl -L https://istio.io/downloadIstio -o /tmp/downloadIstio.sh && sh /tmp/downloadIstio.sh && rm /tmp/downloadIstio.sh
cd istio-*
export PATH=$PWD/bin:$PATH

# Install with the production profile
istioctl install --set profile=default -y

# Or use the demo profile (includes all addons, good for learning)
istioctl install --set profile=demo -y

# Verify installation
istioctl verify-install

# Check running components
kubectl get pods -n istio-system

Enable Sidecar Injection


bash 
# Enable automatic sidecar injection for a namespace
kubectl label namespace default istio-injection=enabled

# Verify label
kubectl get namespace default --show-labels

# Restart existing pods to inject sidecars
kubectl rollout restart deployment -n default

# Check sidecar status
kubectl get pods -n default -o jsonpath='{range .items[*]}{.metadata.name}{" containers: "}{range .spec.containers[*]}{.name}{" "}{end}{"\n"}{end}'

Install Observability Addons


bash 
# Install Kiali, Prometheus, Grafana, Jaeger
kubectl apply -f samples/addons/prometheus.yaml
kubectl apply -f samples/addons/grafana.yaml
kubectl apply -f samples/addons/jaeger.yaml
kubectl apply -f samples/addons/kiali.yaml

# Wait for rollout
kubectl rollout status deployment/kiali -n istio-system

# Access dashboards
istioctl dashboard kiali
istioctl dashboard grafana
istioctl dashboard jaeger

Traffic Management


VirtualService (Routing Rules)


yaml 
# virtualservice.yaml — canary deployment with traffic split
apiVersion: networking.istio.io/v1beta1
kind: VirtualService
metadata:
  name: my-app
  namespace: default
spec:
  hosts:
    - my-app
  http:
    # Header-based routing (canary testers)
    - match:
        - headers:
            x-canary:
              exact: "true"
      route:
        - destination:
            host: my-app
            subset: canary
    # Percentage-based traffic split
    - route:
        - destination:
            host: my-app
            subset: stable
          weight: 90
        - destination:
            host: my-app
            subset: canary
          weight: 10
      timeout: 30s
      retries:
        attempts: 3
        perTryTimeout: 10s
        retryOn: gateway-error,connect-failure,refused-stream

DestinationRule (Subsets and Connection Policy)


yaml 
# destinationrule.yaml
apiVersion: networking.istio.io/v1beta1
kind: DestinationRule
metadata:
  name: my-app
  namespace: default
spec:
  host: my-app
  trafficPolicy:
    connectionPool:
      tcp:
        maxConnections: 100
      http:
        h2UpgradePolicy: DEFAULT
        http1MaxPendingRequests: 100
        http2MaxRequests: 1000
        maxRequestsPerConnection: 10
    outlierDetection:
      consecutive5xxErrors: 5
      interval: 10s
      baseEjectionTime: 30s
      maxEjectionPercent: 50
  subsets:
    - name: stable
      labels:
        version: v1
    - name: canary
      labels:
        version: v2

Gateway (Ingress Traffic)


yaml 
# gateway.yaml — expose service to external traffic
apiVersion: networking.istio.io/v1beta1
kind: Gateway
metadata:
  name: app-gateway
  name

🎯 Best For

  • Claude users
  • AI users

💡 Use Cases

  • Using service-mesh in daily workflow
  • Automating repetitive engineering tasks

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply service-mesh to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install service-mesh?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/service-mesh/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Not reading the full skill

Skills contain important context and edge cases beyond the quick start.

🔗 Related Skills

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