ai-inference-service-mesh – skill Khác cho agent AI
Dùng các mẫu service mesh đã được kiểm chứng để quản lý lưu lượng suy luận AI, mTLS, phát hành canary, thực thi chính sách và khả năng chịu lỗi giữa các cluster.
Cài skill ai-inference-service-mesh bằng một lệnh
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Claude Code
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Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
AI Inference Service Mesh
Apply Istio/Linkerd mesh controls to secure and optimize east-west AI traffic across inference microservices.
Why Mesh for AI
- Enforce mTLS between gateway, retriever, reranker, and model services
- Apply fine-grained traffic policies without app code changes
- Run progressive delivery for model-serving backends
- Observe latency hops for retrieval + generation chains
- Route inference requests by model version, tenant, or priority tier
- Protect expensive GPU-backed services from cascading failures
Prerequisites
Confirm the exact cluster/context, mesh version, CRD schemas, owned namespace and authorized mutation scope. Examples are alternative fragments, not a manifest to apply wholesale: multiple DestinationRules for the same host must be consolidated under the installed version's merge rules. Preview and validate in a disposable environment; protect production routes and rollback evidence.
# Illustrative mutating install; default is not a validated production configuration
istioctl install --set profile=default \
--set meshConfig.accessLogFile=/dev/stdout \
--set meshConfig.defaultConfig.holdApplicationUntilProxyStarts=true
# Label inference namespace for sidecar injection
kubectl create namespace ai-inference
kubectl label namespace ai-inference istio-injection=enabled
# Verify installation
istioctl verify-install
istioctl analyze -n ai-inferenceCore Patterns
mTLS Strict Mode Cluster-Wide
apiVersion: security.istio.io/v1beta1
kind: PeerAuthentication
metadata:
name: default
namespace: istio-system
spec:
mtls:
mode: STRICT
---
# Workload-level override; portLevelMtls requires a workload selector.
apiVersion: security.istio.io/v1beta1
kind: PeerAuthentication
metadata:
name: ai-inference-mtls
namespace: ai-inference
spec:
selector:
matchLabels:
app: model-server
mtls:
mode: STRICT
portLevelMtls:
# gRPC inference port
8081:
mode: STRICT
# Prometheus metrics port - allow plaintext scraping
9090:
mode: PERMISSIVEAuthorizationPolicy Per Service Account
apiVersion: security.istio.io/v1beta1
kind: AuthorizationPolicy
metadata:
name: model-server-access
namespace: ai-inference
spec:
selector:
matchLabels:
app: model-server
action: ALLOW
rules:
- from:
- source:
principals:
- "cluster.local/ns/ai-inference/sa/api-gateway"
- "cluster.local/ns/ai-inference/sa/orchestrator"
to:
- operation:
methods: ["POST"]
paths: ["/v1/predict", "/v1/embeddings", "/v2/models/*/infer"]
---
apiVersion: security.istio.io/v1beta1
kind: AuthorizationPolicy
metadata:
name: deny-external-to-retriever
namespace: ai-inference
spec:
selector:
matchLabels:
app: vector-retriever
action: DENY
rules:
- from:
- source:
notNamespaces: ["ai-inference"]Egress Policy for Approved Model Endpoints
apiVersion: networking.istio.io/v1alpha3
kind: ServiceEntry
metadata:
name: openai-api
namespace: ai-inference
spec:
hosts:
- api.openai.com
ports:
- number: 443
name: https
protocol: TLS
resolution: DNS
location: MESH_EXTERNALA ServiceEntry registers a service; it is not a complete egress firewall. Namespace AuthorizationPolicy controls requests to selected workloads, not arbitrary outbound HTTPS by destination host. Enforce approved egress through a verified gateway/network policy and test bypass routes. For application-originated HTTPS, do not also originate TLS in a DestinationRule without a designed HTTP-to-TLS route (double TLS breaks the connection).
Official guidance: [Istio egress control](https://istio.io/latest/docs/tasks/traffic-management/egress/egress-control/).
Traffic Management
VirtualService for A/B Model Testing
apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
name: model-server
namespace: ai-inference
spec:
hosts:
- model-server
http:
# Route by header for explicit model version selection
- match:
- headers:
x-model-version:
exact: "v2-experimental"
route:
- destination:
host: model-server
subset: v2-experimental
timeout: 120s
# Route by header for A/B test cohort
- match:
- headers:
x-ab-cohort:
exact: "treatment"
route:
- destination:
host: model-server
subset: v2-experimental
weight: 100
timeout: 120s
# Default traffic split: 90/10 canary
- route:
- destination:
host: model-server
subset: v1-stable
weight: 90
- destination:
host: model-server
subset: v2-experimental
weight: 10
timeout: 60s
retries:
attempts: 2
perTryTimeout: 30s
retryOn: unavailable,resource-exhaustedDestinationRule with Subsets
apiVersion: networking.istio.io/v1alpha3
kind: DestinationRule
metadata:
name: model-server
namespace: ai-inference
spec:
host: model-server
trafficPolicy:
connectionPool:
http:
h2UpgradePolicy: UPGRADE
maxRequestsPerConnection: 100
tcp:
maxConnections: 200
connectTimeout: 5s
loadBalancer:
simple: LEAST_REQUEST
subsets:
- name: v1-stable
labels:
version: v1
trafficPolicy:
connectionPool:
http:
maxRequestsPerConnection: 50
- name: v2-experimental
labels:
version: v2
trafficPolicy:
connectionPool:
http:
maxRequestsPerConnection: 20Circuit Breaking for Inference Backends
apiVersion: networking.istio.io/v1alpha3
kind: DestinationRule
metadata:
name: model-server-circuit-breaker
namespace: ai-inference
spec:
host: model-server
trafficPolicy:
connectionPool:
tcp:
maxConnections: 100
connectTimeout: 10s
http:
http1MaxPendingRequests: 50
http2MaxRequests: 200
maxRequestsPerConnection: 10
maxRetries: 3
outlierDetection:
consecutive5xxErrors: 3
interval: 15s
baseEjectionTime: 30s
maxEjectionPercent: 50
minHealthPercent: 30
splitExternalLocalOriginErrors: true
---
# Separate circuit breaker for the vector retriever
apiVersion: networking.istio.io/v1alpha3
kind: DestinationRule
metadata:
name: vector-retriever-circuit-breaker
namespace: ai-inference
spec:
host: vector-retriever
trafficPolicy:
connectionPool:
tcp:
maxConnections: 300
http:
http1MaxPendingRequests: 200
http2MaxRequests: 500
outlierDetection:
consecutive5xxErrors: 5
interval: 10s
baseEjectionTime: 15s
maxEjectionPercent: 30Retry Budget for Streaming Requests
apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
name: streaming-inference
namespace: ai-inference
spec:
hosts:
- model-server
http:
# Streaming endpoint: no retries, long timeout
- match:
- uri:
prefix: /v1/stream
route:
- destination:
host: model-server
subset: v1-stable
timeout: 300s
retries:
attempts: 0
# Embeddings: retries can duplicate billed computation; enable only with a verified deduplication policy
- match:
- uri:
prefix: /v1/embeddings
route:
- destination:
host: model-server
subset: v1-stable
timeout: 15s
retries:
attempts: 3
perTryTimeout: 5s
retryOn: 5xx,reset,connect-failure,retriable-status-codesResilience
Locality-Aware Routing
apiVersion: networking.istio.io/v1alpha3
kind: DestinationRule
metadata:
name: model-server-locality
namespace: ai-inference
spec:
host: model-server
trafficPolicy:
loadBalancer:
localityLbSetting:
enabled: true
distribute:
- from: "us-east-1/us-east-1a/*"
to:
"us-east-1/us-east-1a/*": 80
"us-east-1/us-east-1b/*": 20
# Choose distribution OR a separately designed failover policy, not both.
outlierDetection:
consecutive5xxErrors: 3
interval: 10s
baseEjectionTime: 30sObservability
# Telemetry resource for custom metrics on inference services
apiVersion: telemetry.istio.io/v1alpha1
kind: Telemetry
metadata:
name: inference-telemetry
namespace: ai-inference
spec:
metrics:
- providers:
- name: prometheus
overrides:
- match:
metric: REQUEST_DURATION
mode: CLIENT_AND_SERVER
tagOverrides:
# Any model_name label must use a bounded, gateway-validated allowlist.
# Raw client header values can create unbounded time series.
# Do not expose raw tenant IDs as unbounded metric labels.
tracing:
- providers:
- name: zipkin
randomSamplingPercentage: 10.0Kiali Dashboard Check
# Port-forward Kiali
kubectl… (nội dung đầy đủ có trong gói tải về)
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