name: gke-deployment
description: Deploy, configure, and manage Kubernetes workloads on GKE with Deployments, Services, Ingress, HPA, health probes, ConfigMaps, and Secrets. Use when deploying containers to GKE, configuring load balancers, setting up autoscaling, writing health checks, managing environment configs, or troubleshooting pod issues.
license: MIT
metadata:
version: 1.0.0
audience: developers
workflow: infrastructure
GKE Deployment
Production-ready Kubernetes deployment patterns for Google Kubernetes Engine.
What I Do
- Write Kubernetes Deployments with proper update strategies
- Configure Services (ClusterIP, NodePort, LoadBalancer) and Ingress
- Implement HPA with CPU, memory, and custom metrics
- Define resource requests/limits and health probes
- Manage ConfigMaps, Secrets, and Workload Identity
When to Use Me
- Deploy applications or microservices to GKE
- Configure Ingress with HTTPS and managed certificates
- Set up autoscaling based on metrics
- Write health check endpoints and probe configurations
- Troubleshoot pod crashes, restarts, or scheduling issues
- Implement blue-green or canary deployment strategies
Deployment Patterns
Rolling Update (Zero Downtime)
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app
spec:
replicas: 3
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
selector:
matchLabels:
app: my-app
template:
spec:
containers:
- name: my-app
image: us-docker.pkg.dev/PROJECT/REPO/my-app:TAG # Artifact Registry (preferred)
# Or legacy: gcr.io/PROJECT/my-app:TAG
resources:
requests:
cpu: 100m
memory: 256Mi
limits:
cpu: 500m
memory: 512Mi
Service Configuration
| Type |
Use Case |
External |
| ClusterIP |
Internal services |
No |
| NodePort |
Dev, custom LB |
Via node |
| LoadBalancer |
Direct external |
GCP L4 LB |
Health Probes
containers:
- name: my-app
startupProbe:
httpGet: {path: /healthz, port: 8080}
periodSeconds: 10
failureThreshold: 30
livenessProbe:
httpGet: {path: /healthz, port: 8080}
periodSeconds: 15
failureThreshold: 3
readinessProbe:
httpGet: {path: /ready, port: 8080}
periodSeconds: 5
failureThreshold: 3
| Probe |
Purpose |
On Failure |
| Startup |
Wait for slow apps |
Block other probes |
| Liveness |
Detect deadlocks |
Restart container |
| Readiness |
Control traffic |
Remove from Service |
Horizontal Pod Autoscaler
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
behavior:
scaleDown:
stabilizationWindowSeconds: 300
Context7 Integration
Use Context7 MCP server for up-to-date Kubernetes docs:
context7_resolve-library-id("kubernetes", "HPA configuration")
context7_query-docs("/kubernetes/website", "Ingress path types")
Quick Decision Matrix
| Need |
Solution |
| Zero-downtime deploy |
maxUnavailable: 0 |
| External HTTPS |
Ingress + ManagedCertificate |
| Auto-scale on load |
HPA with CPU target |
| Slow app startup |
startupProbe, high failureThreshold |
| Pod spread across zones |
topologySpreadConstraints |
| GCP API access |
Workload Identity |
Common Errors
| Error |
Cause |
Solution |
CrashLoopBackOff |
App crashes |
Check logs, verify probes |
ImagePullBackOff |
Can't pull image |
Verify path, imagePullSecrets |
Pending pod |
No resources |
Check capacity, adjust requests |
OOMKilled |
Memory exceeded |
Increase limit or fix leak |
Unhealthy backend |
Health check fails |
Ensure /healthz returns 200 |
Resource Guidelines
| Workload |
CPU |
Memory |
| Web API |
100m-500m |
256Mi-512Mi |
| Worker |
250m-1000m |
512Mi-1Gi |
| Sidecar |
10m-50m |
32Mi-64Mi |
Security Checklist
GKE-Specific Patterns
Workload Identity (GCP API Access)
# ServiceAccount annotation
apiVersion: v1
kind: ServiceAccount
metadata:
name: my-app
annotations:
iam.gke.io/gcp-service-account: my-app@PROJECT.iam.gserviceaccount.com
# Bind KSA to GSA
gcloud iam service-accounts add-iam-policy-binding \
my-app@PROJECT.iam.gserviceaccount.com \
--role roles/iam.workloadIdentityUser \
--member "serviceAccount:PROJECT.svc.id.goog[NAMESPACE/my-app]"
GKE Ingress with Managed Certificate
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
annotations:
kubernetes.io/ingress.class: "gce"
networking.gke.io/managed-certificates: "my-cert"
spec:
rules:
- host: api.example.com
http:
paths:
- path: /*
pathType: ImplementationSpecific
backend:
service:
name: my-app
port:
number: 80
---
apiVersion: networking.gke.io/v1
kind: ManagedCertificate
metadata:
name: my-cert
spec:
domains:
- api.example.com
Container-Native Load Balancing (NEG)
apiVersion: v1
kind: Service
metadata:
annotations:
cloud.google.com/neg: '{"ingress": true}' # Enable NEGs
spec:
type: ClusterIP # Not NodePort
See references/research.md for detailed examples and advanced patterns.
Related Skills
| Skill |
Use When |
| kubernetes-debugging |
Troubleshooting pod issues |
| helm-charts |
Packaging deployments as charts |
| github-actions |
CI/CD pipeline setup |
Resources