gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints
Install / Use
npx skills add google/skills --skill gke-reliabilityInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
MarketingSupported Platforms
Our assessment of gke-reliability
gke-reliability scores 94/100 on our quality scale, 36th of 176 Marketing skills we index (top 21%).
Its SKILL.md is 6.8 KB long, well organised into 16 sections with 7 code examples: a thorough specification that gives an agent plenty to work with.
With 20,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 2 days ago, so gke-reliability is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
gke-reliability compared with similar skills
All 4 of these similar skills score higher than gke-reliability; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| gke-reliability (this skill)by google | 94 | 20.3k | 2d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.5k | 10d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.8k | today | CLAUDE.md |
| rufloby ruvnet | 100 | 73.3k | 1d ago | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.1k | today | CLAUDE.md |
Frequently asked questions
- How do I install gke-reliability?
- Run
npx skills add google/skills --skill gke-reliability. The install tabs above show the steps for each supported agent. - Which AI agents does gke-reliability work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is gke-reliability safe to use?
- It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is gke-reliability still maintained?
- The repository was last updated 2 days ago, so gke-reliability is actively maintained.
Skill content
View source on GitHubname: gke-reliability description: >- Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead). metadata: version: "1.0.0" category: Containers
GKE Reliability
This reference covers high availability and reliability configuration for GKE clusters and workloads.
MCP Tools:
get_cluster,get_k8s_resource,describe_k8s_resource,apply_k8s_manifest,list_k8s_events
Golden Path Reliability Defaults
| Setting | Golden Path Value | Notes |
| ---------------- | --------------------- | -------------------------------- |
| Cluster type | Regional (4 zones: | Control plane replicated across |
: : us-central1-a/b/c/f) : zones :
| Upgrade strategy | SURGE (maxSurge: 1) | Rolling upgrades with extra |
: : : capacity :
| Auto-repair | true | Unhealthy nodes replaced |
: : : automatically :
| Auto-upgrade | true | Nodes follow control plane |
: : : version :
| Release channel | REGULAR | Balanced freshness and stability |
| Stateful HA | Enabled | Leader election for stateful |
: : : workloads :
Workflows
1. Verify Cluster High Availability
# MCP (preferred)
get_cluster(name="projects/<PROJECT>/locations/<REGION>/clusters/<CLUSTER>",
readMask="location,locations,nodePools.locations")
# gcloud fallback
gcloud container clusters describe <CLUSTER> --region <REGION> \
--format="json(location, locations)" \
--quiet
- If
locationis a region (e.g.,us-central1), the control plane is regional - If
locationshas multiple entries, nodes span multiple zones
2. Pod Disruption Budgets (PDBs)
PDBs ensure minimum pod availability during voluntary disruptions (node upgrades, autoscaler scale-down).
Check existing PDBs:
# MCP (preferred)
get_k8s_resource(parent="...", resourceType="poddisruptionbudget")
# kubectl fallback
kubectl get pdb --all-namespaces
Create PDB:
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
name: my-app-pdb
namespace: default
spec:
minAvailable: 2 # Or use maxUnavailable: 1
selector:
matchLabels:
app: my-app
Every production Deployment with 2+ replicas should have a PDB.
3. Health Probes
Every production container should have liveness and readiness probes. Startup probes are recommended for slow-starting apps.
Check existing probes:
# MCP (preferred)
describe_k8s_resource(parent="...", resourceType="deployment", name="<APP>", namespace="<NS>")
# kubectl fallback
kubectl get deployment <APP> -n <NS> -o yaml | grep -E "livenessProbe|readinessProbe|startupProbe"
Recommended probe configuration:
spec:
containers:
- name: app
livenessProbe:
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 15
periodSeconds: 10
timeoutSeconds: 2
failureThreshold: 3
readinessProbe:
httpGet:
path: /readyz
port: 8080
initialDelaySeconds: 5
periodSeconds: 5
timeoutSeconds: 2
failureThreshold: 3
startupProbe: # For slow-starting apps
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 10
periodSeconds: 5
timeoutSeconds: 2
failureThreshold: 30 # 30 * 5s = 150s max startup time
- Readiness: Determines when a pod can accept traffic
- Liveness: Determines when to restart a container
- Startup: Disables liveness/readiness until the app is ready (prevents premature restarts)
4. Graceful Shutdown
Ensure applications handle SIGTERM and drain in-flight requests:
spec:
terminationGracePeriodSeconds: 30 # Default; increase for long-running requests
containers:
- name: app
lifecycle:
preStop:
exec:
command: ["/bin/sh", "-c", "sleep 5"] # Allow LB to deregister
5. Topology Spread Constraints
Distribute pods across zones and nodes to survive failures:
spec:
topologySpreadConstraints:
- maxSkew: 1
topologyKey: topology.kubernetes.io/zone
whenUnsatisfiable: DoNotSchedule
labelSelector:
matchLabels:
app: my-app
- maxSkew: 1
topologyKey: kubernetes.io/hostname
whenUnsatisfiable: ScheduleAnyway
labelSelector:
matchLabels:
app: my-app
- Zone spread (
DoNotSchedule): Hard requirement -- pods must be balanced across zones - Node spread (
ScheduleAnyway): Best-effort -- prefer distribution but don't block scheduling
6. Replicas
| Workload Type | Minimum Replicas | Reason | | -------------------- | -------------------- | ------------------------------ | | Stateless web/API | 2 | Survive single pod/node | : : : failure : | Critical services | 3 | Survive zone failure with zone | : : : spread : | Stateful (databases) | 3 (with replication) | Application-level quorum | | Batch/jobs | 1 | Ephemeral by nature |
Best Practices & Production Guidelines
- Regional clusters for production: Always use regional clusters to survive zone failures.
- PDBs for everything: Every production workload with 2+ replicas needs a PodDisruptionBudget (PDB) to protect against voluntary disruptions.
- Probes with Explicit Timeouts: Every production container must have both
liveness and readiness probes defined. Always explicitly define
initialDelaySeconds,periodSeconds, andtimeoutSecondsfor all probes. Never rely on the Kubernetes default timeout of 1 second if your application requires more, but always set a strict limit to prevent hanging connections. - Zone spreading: Use topology spread constraints to distribute pods across failure domains (zones and nodes).
- Graceful shutdown: Handle
SIGTERMand set appropriateterminationGracePeriodSecondswith apreStopsleep hook to allow load balancer deregistration. - Maintenance windows: Schedule upgrades during low-traffic periods (see
the
gke-upgradesskill).
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
