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metadata
language:
  - en
license: apache-2.0
size_categories:
  - 100K<n<1M
task_categories:
  - text-generation
  - question-answering
tags:
  - devops
  - kubernetes
  - infrastructure
  - sft
  - synthetic
  - ci-cd
  - helm
  - terraform
  - gitops
  - argocd
pretty_name: DevOps and Kubernetes SFT 100K

DevOps and Kubernetes SFT 100K

A synthetic supervised fine-tuning dataset of 100,000 high-quality DevOps and Kubernetes conversations designed to train AI assistants capable of supporting platform engineers, SREs, and DevOps practitioners.

Dataset Description

This dataset covers production-grade Kubernetes operations, cloud infrastructure, CI/CD pipelines, GitOps workflows, and platform engineering across 13 specialized categories. Each record follows the ShareGPT conversation format with practical, copy-paste-ready examples.

Categories

Category Description
kubernetes_troubleshooting Pod debugging, CrashLoopBackOff, pending pods
kubernetes_networking Ingress, Services, NetworkPolicies, DNS
kubernetes_security RBAC, PodSecurity, NetworkPolicy, secrets management
kubernetes_storage PVCs, StatefulSets, StorageClasses, volume snapshots
kubernetes_autoscaling HPA, VPA, KEDA, Cluster Autoscaler
kubernetes_debugging Ephemeral containers, network debugging, pprof
kubernetes_cost_optimization Right-sizing, Spot instances, waste identification
ci_cd_pipelines GitHub Actions, Docker build, deployment pipelines
infrastructure_as_code Terraform, EKS, VPC, IRSA
helm_charts Helm chart creation, lifecycle hooks, best practices
gitops_argocd ArgoCD, multi-environment promotion, App of Apps
monitoring_observability Prometheus, Grafana, SLO alerting, kube-prometheus-stack
devops_platform_engineering IDP, Backstage, Crossplane, ephemeral environments

Format

ShareGPT format:

{
  "conversations": [
    {"from": "human", "value": "...DevOps question..."},
    {"from": "gpt", "value": "...structured answer with code examples..."}
  ],
  "metadata": {"category": "...", "context": "..."},
  "id": "uuid"
}

Use Cases

  • Fine-tuning AI coding assistants for platform engineering
  • SRE and DevOps chatbot development
  • Kubernetes operational runbook automation
  • Internal developer platform AI agents
  • DevOps training and certification preparation

Quality Notes

All responses include working code examples, production-ready configurations, and best practice guidance. YAML, shell commands, and Terraform examples are copy-paste ready.