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cloudfleetaicloudfleetai/cloudfleet-plugin-claude/skills/best-practices/SKILL.md

best-practices

Skill0 starsChanged 10 days agoApache-2.0View on GitHub

This skill should be used when the user creates deployments, services, or asks about resource requests, load balancers, node placement, GPU workloads, or production readiness on CFKE.

33 other projects use a version of this.

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Projects with it also use llm-application-dev, audit-library-health and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 27 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Always set CPU and memory requests on ALL containers, including sidecar init containers.

    line 13
  2. Very specific:

    Always use externalTrafficPolicy: Local.

    line 23
  3. Distinctive:

    Security: No privileged containers, versioned image tags, NetworkPolicies, TLS on Ingresses

    line 39
  4. Very specific:

    GPU/ML: Use cfke.io/accelerator-name label, set nvidia.com/gpu requests

    line 40

“Common” is measured: kept by at least 6 in 10 of the 27 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

CFKE Best Practices

Critical guidance for deploying and operating workloads on Cloudfleet Kubernetes Engine. For detailed examples and YAML snippets, see references/best-practices.md.

1. Resource Requests (CRITICAL)

Always set CPU and memory requests on ALL containers, including sidecar init containers. CFKE's auto-provisioner depends on these for node sizing and scaling.

Do NOT set CPU limits. CPU limits cause unnecessary CFS throttling. Set CPU requests for scheduling only.

CFKE ships a ValidatingAdmissionPolicy named resource-requests-are-not-set that names the containers missing requests. It only warns, so the object is still admitted and the warning is easy to lose in Helm output. Treat it as the signal it is.

Set requests in chart values before the first install of any third-party chart. Upstream charts almost always ship resources: {}.

2. Load Balancer Services (CRITICAL)

Always use externalTrafficPolicy: Local. The default 'Cluster' mode creates LBs in every cloud/region where nodes exist, causing extra costs and inefficient routing.

3. Node Placement Constraints

Without constraints, the auto-provisioner picks the cheapest node from ANY configured provider. Use CFKE node labels to control placement:

  • cfke.io/provider — cloud provider
  • topology.kubernetes.io/zone — availability zone
  • cfke.io/accelerator-name — GPU type

See references/best-practices.md for nodeSelector, affinity, and topologySpreadConstraints examples.

4. Quick Reference

  • PodDisruptionBudgets: Define PDBs for critical workloads
  • Health Checks: Configure liveness/readiness probes on all containers
  • Security: No privileged containers, versioned image tags, NetworkPolicies, TLS on Ingresses
  • GPU/ML: Use cfke.io/accelerator-name label, set nvidia.com/gpu requests
  • Container Registries: CFCR, AWS ECR, and GCP Artifact Registry work without imagePullSecrets

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