[{"data":1,"prerenderedAt":1050},["ShallowReactive",2],{"blog-ja-kubernetes-cost-optimization-guide":3,"blog-ja-kubernetes-cost-optimization-guide-alt":1040},{"id":4,"title":5,"author":6,"body":7,"date":1035,"description":1036,"extension":1037,"image":263,"locale":1038,"meta":1039,"navigation":1040,"path":1041,"seo":1042,"stem":1043,"tags":1044,"__hash__":1049},"blog\u002Fblog\u002Fja\u002Fkubernetes-cost-optimization-guide.md","Kubernetes コスト最適化完全ガイド：EKS\u002FAKS\u002FGKE vs Kubo 徹底比較","Kubo Team",{"type":8,"value":9,"toc":1008},"minimark",[10,22,31,36,44,48,102,105,109,117,139,142,216,219,228,232,245,249,257,393,397,405,408,428,431,435,443,446,473,477,486,497,500,503,506,674,678,795,798,824,828,836,840,851,855,866,870,881,889,893,896,982,995,1004],[11,12,13,14,21],"p",{},"Kubernetes は現代のクラウドネイティブアーキテクチャの基盤ですが、適切に管理しなければコストが急速に膨張します。",[15,16,20],"a",{"href":17,"rel":18},"https:\u002F\u002Fwww.cncf.io\u002F",[19],"nofollow","CNCF の調査","によれば、FinOps を導入していない組織はクラウド費用の 32〜40% を無駄にしており、成熟した FinOps チームでもその割合は 15〜20% です。",[11,23,24,25,30],{},"本記事では、Kubernetes のコスト最適化戦略を体系的に解説し、EKS・AKS・GKE の料金を比較した上で、",[15,26,29],{"href":27,"rel":28},"https:\u002F\u002Fkubo.hexabase.io\u002F",[19],"Kubo"," が提供する月額48,000円〜というコスト優位性の根拠を明らかにします。",[32,33,35],"h2",{"id":34},"マネージド-kubernetes-の料金比較eks-vs-aks-vs-gke","マネージド Kubernetes の料金比較：EKS vs AKS vs GKE",[11,37,38,43],{},[15,39,42],{"href":40,"rel":41},"https:\u002F\u002Fsedai.io\u002Fblog\u002Fkubernetes-cost-eks-vs-aks-vs-gke",[19],"2026年のマネージド Kubernetes 料金比較","を基に、主要3プラットフォームのコストを整理します。",[45,46,47],"h3",{"id":47},"コントロールプレーン費用",[49,50,51,66],"table",{},[52,53,54],"thead",{},[55,56,57,61,63],"tr",{},[58,59,60],"th",{},"プラットフォーム",[58,62,47],{},[58,64,65],{},"月額概算",[67,68,69,81,92],"tbody",{},[55,70,71,75,78],{},[72,73,74],"td",{},"Amazon EKS",[72,76,77],{},"$0.10\u002F時間\u002Fクラスタ",[72,79,80],{},"約 $72（約10,800円）",[55,82,83,86,89],{},[72,84,85],{},"Azure AKS",[72,87,88],{},"無料",[72,90,91],{},"$0",[55,93,94,97,100],{},[72,95,96],{},"Google GKE",[72,98,99],{},"$0.10\u002F時間（リージョナル）",[72,101,80],{},[11,103,104],{},"AKS のコントロールプレーン無料は魅力的に見えますが、実際にはコントロールプレーン費用は総コストの5%未満に過ぎません。",[45,106,108],{"id":107},"真のコスト比較200ノード規模","真のコスト比較（200ノード規模）",[11,110,111,116],{},[15,112,115],{"href":113,"rel":114},"https:\u002F\u002Fleanopstech.com\u002Fblog\u002Feks-vs-gke-vs-aks-pricing-2026\u002F",[19],"LeanOps の分析","によれば、200ノード規模での月額コストは：",[118,119,120,128,134],"ul",{},[121,122,123,127],"li",{},[124,125,126],"strong",{},"amazon eks",": 約 $46,200-月（約693万円）",[121,129,130,133],{},[124,131,132],{},"GKE Autopilot",": 約 $51,700\u002F月（約775万円）",[121,135,136,138],{},[124,137,85],{},": 約 $43,000\u002F月（約645万円）",[45,140,141],{"id":141},"見落としがちな隠れコスト",[49,143,144,160],{},[52,145,146],{},[55,147,148,151,154,157],{},[58,149,150],{},"項目",[58,152,153],{},"EKS",[58,155,156],{},"AKS",[58,158,159],{},"GKE",[67,161,162,176,189,203],{},[55,163,164,167,170,173],{},[72,165,166],{},"データ転送（エグレス）",[72,168,169],{},"$0.09\u002FGB",[72,171,172],{},"$0.087\u002FGB",[72,174,175],{},"$0.085\u002FGB",[55,177,178,181,184,187],{},[72,179,180],{},"ロードバランサー",[72,182,183],{},"$0.025\u002F時間",[72,185,186],{},"$0.005\u002F時間",[72,188,183],{},[55,190,191,194,197,200],{},[72,192,193],{},"ストレージ",[72,195,196],{},"$0.10\u002FGB\u002F月（EBS）",[72,198,199],{},"可変（Managed Disks）",[72,201,202],{},"$0.04\u002FGB\u002F月（PD）",[55,204,205,208,211,214],{},[72,206,207],{},"NAT ゲートウェイ",[72,209,210],{},"$0.045\u002F時間 + $0.045\u002FGB",[72,212,213],{},"可変",[72,215,213],{},[11,217,218],{},"これらの隠れコストは月額数千ドルに達することがあり、特にデータ転送量の多いマイクロサービスアーキテクチャでは注意が必要です。",[11,220,221,227],{},[124,222,223,226],{},[15,224,29],{"href":27,"rel":225},[19]," なら、月額48,000円〜でコントロールプレーン・ストレージ・基本的なネットワーク転送が含まれた明瞭な料金体系です。"," EKS\u002FAKS\u002FGKE の隠れコストに悩む必要はありません。",[32,229,231],{"id":230},"リソースの適正化ライトサイジング","リソースの適正化（ライトサイジング）",[11,233,234,235,238,239,244],{},"Kubernetes のコスト無駄の最大の原因は ",[124,236,237],{},"リソースの過剰プロビジョニング"," です。",[15,240,243],{"href":241,"rel":242},"https:\u002F\u002Fwww.cloudzero.com\u002Fblog\u002Fkubernetes-cost-optimization\u002F",[19],"CloudZero のレポート","によれば、適切なライトサイジングで 30〜50% のコスト削減が可能です。",[45,246,248],{"id":247},"vpa-によるリソース推奨","VPA によるリソース推奨",[11,250,251,256],{},[15,252,255],{"href":253,"rel":254},"https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Fconcepts\u002Fworkloads\u002Fautoscaling\u002F",[19],"Vertical Pod Autoscaler（VPA）"," を「Off」モードで実行し、実際の使用状況に基づくリソース推奨値を取得します：",[258,259,264],"pre",{"className":260,"code":261,"language":262,"meta":263,"style":263},"language-yaml shiki shiki-themes tokyo-night","apiVersion: autoscaling.k8s.io\u002Fv1\nkind: VerticalPodAutoscaler\nmetadata:\n  name: my-app-vpa\nspec:\n  targetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: my-app\n  updatePolicy:\n    updateMode: \"Off\"  # 推奨値のみ取得、自動適用しない\n","yaml","",[265,266,267,284,295,304,315,323,331,342,353,364,372],"code",{"__ignoreMap":263},[268,269,272,276,280],"span",{"class":270,"line":271},"line",1,[268,273,275],{"class":274},"s0U2E","apiVersion",[268,277,279],{"class":278},"sAklC",":",[268,281,283],{"class":282},"sPY7s"," autoscaling.k8s.io\u002Fv1\n",[268,285,287,290,292],{"class":270,"line":286},2,[268,288,289],{"class":274},"kind",[268,291,279],{"class":278},[268,293,294],{"class":282}," VerticalPodAutoscaler\n",[268,296,298,301],{"class":270,"line":297},3,[268,299,300],{"class":274},"metadata",[268,302,303],{"class":278},":\n",[268,305,307,310,312],{"class":270,"line":306},4,[268,308,309],{"class":274},"  name",[268,311,279],{"class":278},[268,313,314],{"class":282}," my-app-vpa\n",[268,316,318,321],{"class":270,"line":317},5,[268,319,320],{"class":274},"spec",[268,322,303],{"class":278},[268,324,326,329],{"class":270,"line":325},6,[268,327,328],{"class":274},"  targetRef",[268,330,303],{"class":278},[268,332,334,337,339],{"class":270,"line":333},7,[268,335,336],{"class":274},"    apiVersion",[268,338,279],{"class":278},[268,340,341],{"class":282}," apps\u002Fv1\n",[268,343,345,348,350],{"class":270,"line":344},8,[268,346,347],{"class":274},"    kind",[268,349,279],{"class":278},[268,351,352],{"class":282}," Deployment\n",[268,354,356,359,361],{"class":270,"line":355},9,[268,357,358],{"class":274},"    name",[268,360,279],{"class":278},[268,362,363],{"class":282}," my-app\n",[268,365,367,370],{"class":270,"line":366},10,[268,368,369],{"class":274},"  updatePolicy",[268,371,303],{"class":278},[268,373,375,378,380,383,386,389],{"class":270,"line":374},11,[268,376,377],{"class":274},"    updateMode",[268,379,279],{"class":278},[268,381,382],{"class":278}," \"",[268,384,385],{"class":282},"Off",[268,387,388],{"class":278},"\"",[268,390,392],{"class":391},"sbD-w","  # 推奨値のみ取得、自動適用しない\n",[45,394,396],{"id":395},"goldilocks-アプローチ","Goldilocks アプローチ",[11,398,399,404],{},[15,400,403],{"href":401,"rel":402},"https:\u002F\u002Fgithub.com\u002FFairwindsOps\u002Fgoldilocks",[19],"Goldilocks"," は VPA の推奨値をダッシュボードで可視化するツールです。namespace 単位で全 Deployment のリソース推奨値を確認でき、過剰プロビジョニングの発見に役立ちます。",[45,406,407],{"id":407},"リソース設定のベストプラクティス",[118,409,410,416,422],{},[121,411,412,415],{},[124,413,414],{},"requests",": 平常時の使用量の P90（90パーセンタイル）に設定",[121,417,418,421],{},[124,419,420],{},"limits",": requests の 1.5〜2倍に設定（CPU は制限なしも検討）",[121,423,424,427],{},[124,425,426],{},"LimitRange",": namespace レベルでデフォルト値を設定し、設定漏れを防止",[32,429,430],{"id":430},"スポットインスタンスとオートスケーリングの活用",[45,432,434],{"id":433},"スポットインスタンスで-6075-削減","スポットインスタンスで 60〜75% 削減",[11,436,437,442],{},[15,438,441],{"href":439,"rel":440},"https:\u002F\u002Faws.amazon.com\u002Fec2\u002Fspot\u002F",[19],"スポットインスタンス","（AWS）、Preemptible VM（GCP）、Spot VM（Azure）は、オンデマンド価格から最大 90% の割引を提供します。",[11,444,445],{},"安全に活用するためのポイント：",[118,447,448,454,464,470],{},[121,449,450,453],{},[124,451,452],{},"Pod Disruption Budget（PDB）"," で最小レプリカ数を保証",[121,455,456,459,460,463],{},[124,457,458],{},"5種類以上のインスタンスタイプ"," と ",[124,461,462],{},"3つ以上の AZ"," に分散",[121,465,466,469],{},[124,467,468],{},"ステートフルワークロード","（DB、永続キュー）はオンデマンドに配置",[121,471,472],{},"分散スポットフリートの中断率は通常 5% 未満",[45,474,476],{"id":475},"karpenter-による次世代ノードプロビジョニング","Karpenter による次世代ノードプロビジョニング",[11,478,479,480,485],{},"EKS を使用している場合、",[15,481,484],{"href":482,"rel":483},"https:\u002F\u002Fkarpenter.sh\u002F",[19],"Karpenter"," は Cluster Autoscaler より 20〜35% 高い節約率を実現します。インスタンス選択の最適化と未使用ノードの積極的な統合により、リソース効率を最大化します。",[11,487,488,459,493,496],{},[15,489,492],{"href":490,"rel":491},"https:\u002F\u002Fwww.hexabase.com\u002Fproduct\u002Fcaptain-ai\u002F",[19],"Captain.AI",[15,494,29],{"href":27,"rel":495},[19]," の組み合わせでは、AI ワークロードのスケーリングが自動化され、手動でのスポットインスタンス管理が不要になります。",[32,498,499],{"id":499},"非本番環境のコスト削減",[45,501,502],{"id":502},"スケジュールベースのスケーリング",[11,504,505],{},"開発・ステージング環境は、業務時間外にスケールダウンまたは停止することで大幅にコストを削減できます：",[258,507,509],{"className":260,"code":508,"language":262,"meta":263,"style":263},"# KEDA の Cron スケーラーを使用した例\napiVersion: keda.sh\u002Fv1alpha1\nkind: ScaledObject\nmetadata:\n  name: business-hours-scaler\nspec:\n  scaleTargetRef:\n    name: dev-api\n  minReplicaCount: 0\n  triggers:\n  - type: cron\n    metadata:\n      timezone: Asia\u002FTokyo\n      start: \"0 9 * * 1-5\"   # 平日9時に起動\n      end: \"0 22 * * 1-5\"    # 平日22時に停止\n      desiredReplicas: \"2\"\n",[265,510,511,516,525,534,540,549,555,562,571,582,589,603,611,622,640,658],{"__ignoreMap":263},[268,512,513],{"class":270,"line":271},[268,514,515],{"class":391},"# KEDA の Cron スケーラーを使用した例\n",[268,517,518,520,522],{"class":270,"line":286},[268,519,275],{"class":274},[268,521,279],{"class":278},[268,523,524],{"class":282}," keda.sh\u002Fv1alpha1\n",[268,526,527,529,531],{"class":270,"line":297},[268,528,289],{"class":274},[268,530,279],{"class":278},[268,532,533],{"class":282}," ScaledObject\n",[268,535,536,538],{"class":270,"line":306},[268,537,300],{"class":274},[268,539,303],{"class":278},[268,541,542,544,546],{"class":270,"line":317},[268,543,309],{"class":274},[268,545,279],{"class":278},[268,547,548],{"class":282}," business-hours-scaler\n",[268,550,551,553],{"class":270,"line":325},[268,552,320],{"class":274},[268,554,303],{"class":278},[268,556,557,560],{"class":270,"line":333},[268,558,559],{"class":274},"  scaleTargetRef",[268,561,303],{"class":278},[268,563,564,566,568],{"class":270,"line":344},[268,565,358],{"class":274},[268,567,279],{"class":278},[268,569,570],{"class":282}," dev-api\n",[268,572,573,576,578],{"class":270,"line":355},[268,574,575],{"class":274},"  minReplicaCount",[268,577,279],{"class":278},[268,579,581],{"class":580},"sOJ5S"," 0\n",[268,583,584,587],{"class":270,"line":366},[268,585,586],{"class":274},"  triggers",[268,588,303],{"class":278},[268,590,591,595,598,600],{"class":270,"line":374},[268,592,594],{"class":593},"sgJMe","  -",[268,596,597],{"class":274}," type",[268,599,279],{"class":278},[268,601,602],{"class":282}," cron\n",[268,604,606,609],{"class":270,"line":605},12,[268,607,608],{"class":274},"    metadata",[268,610,303],{"class":278},[268,612,614,617,619],{"class":270,"line":613},13,[268,615,616],{"class":274},"      timezone",[268,618,279],{"class":278},[268,620,621],{"class":282}," Asia\u002FTokyo\n",[268,623,625,628,630,632,635,637],{"class":270,"line":624},14,[268,626,627],{"class":274},"      start",[268,629,279],{"class":278},[268,631,382],{"class":278},[268,633,634],{"class":282},"0 9 * * 1-5",[268,636,388],{"class":278},[268,638,639],{"class":391},"   # 平日9時に起動\n",[268,641,643,646,648,650,653,655],{"class":270,"line":642},15,[268,644,645],{"class":274},"      end",[268,647,279],{"class":278},[268,649,382],{"class":278},[268,651,652],{"class":282},"0 22 * * 1-5",[268,654,388],{"class":278},[268,656,657],{"class":391},"    # 平日22時に停止\n",[268,659,661,664,666,668,671],{"class":270,"line":660},16,[268,662,663],{"class":274},"      desiredReplicas",[268,665,279],{"class":278},[268,667,382],{"class":278},[268,669,670],{"class":282},"2",[268,672,673],{"class":278},"\"\n",[45,675,677],{"id":676},"namespace-レベルのリソースクォータ","namespace レベルのリソースクォータ",[258,679,681],{"className":260,"code":680,"language":262,"meta":263,"style":263},"apiVersion: v1\nkind: ResourceQuota\nmetadata:\n  name: dev-quota\n  namespace: development\nspec:\n  hard:\n    requests.cpu: \"8\"\n    requests.memory: \"16Gi\"\n    limits.cpu: \"16\"\n    limits.memory: \"32Gi\"\n",[265,682,683,692,701,707,716,726,732,739,753,767,781],{"__ignoreMap":263},[268,684,685,687,689],{"class":270,"line":271},[268,686,275],{"class":274},[268,688,279],{"class":278},[268,690,691],{"class":282}," v1\n",[268,693,694,696,698],{"class":270,"line":286},[268,695,289],{"class":274},[268,697,279],{"class":278},[268,699,700],{"class":282}," ResourceQuota\n",[268,702,703,705],{"class":270,"line":297},[268,704,300],{"class":274},[268,706,303],{"class":278},[268,708,709,711,713],{"class":270,"line":306},[268,710,309],{"class":274},[268,712,279],{"class":278},[268,714,715],{"class":282}," dev-quota\n",[268,717,718,721,723],{"class":270,"line":317},[268,719,720],{"class":274},"  namespace",[268,722,279],{"class":278},[268,724,725],{"class":282}," development\n",[268,727,728,730],{"class":270,"line":325},[268,729,320],{"class":274},[268,731,303],{"class":278},[268,733,734,737],{"class":270,"line":333},[268,735,736],{"class":274},"  hard",[268,738,303],{"class":278},[268,740,741,744,746,748,751],{"class":270,"line":344},[268,742,743],{"class":274},"    requests.cpu",[268,745,279],{"class":278},[268,747,382],{"class":278},[268,749,750],{"class":282},"8",[268,752,673],{"class":278},[268,754,755,758,760,762,765],{"class":270,"line":355},[268,756,757],{"class":274},"    requests.memory",[268,759,279],{"class":278},[268,761,382],{"class":278},[268,763,764],{"class":282},"16Gi",[268,766,673],{"class":278},[268,768,769,772,774,776,779],{"class":270,"line":366},[268,770,771],{"class":274},"    limits.cpu",[268,773,279],{"class":278},[268,775,382],{"class":278},[268,777,778],{"class":282},"16",[268,780,673],{"class":278},[268,782,783,786,788,790,793],{"class":270,"line":374},[268,784,785],{"class":274},"    limits.memory",[268,787,279],{"class":278},[268,789,382],{"class":278},[268,791,792],{"class":282},"32Gi",[268,794,673],{"class":278},[45,796,797],{"id":797},"コスト可視化ツール",[118,799,800,808,816],{},[121,801,802,807],{},[15,803,806],{"href":804,"rel":805},"https:--www.opencost.io-",[19],"opencost","（cncf プロジェクト）：kubernetes コストのリアルタイム可視化",[121,809,810,815],{},[15,811,814],{"href":812,"rel":813},"https:\u002F\u002Fwww.kubecost.com\u002F",[19],"Kubecost","：namespace\u002Fラベル別のコスト配分",[121,817,818,823],{},[15,819,822],{"href":820,"rel":821},"https:\u002F\u002Fscaleops.com\u002F",[19],"ScaleOps","：自律的なリソース最適化",[32,825,827],{"id":826},"finops-の実践継続的なコスト最適化サイクル","FinOps の実践：継続的なコスト最適化サイクル",[11,829,830,835],{},[15,831,834],{"href":832,"rel":833},"https:\u002F\u002Fwww.finops.org\u002F",[19],"FinOps Foundation"," が推奨する3つのフェーズで継続的にコストを最適化します：",[45,837,839],{"id":838},"_1-inform可視化","1. Inform（可視化）",[118,841,842,845,848],{},[121,843,844],{},"チーム\u002Fプロジェクト別のコスト配分を確立",[121,846,847],{},"Kubernetes ラベルによるコスト追跡の徹底",[121,849,850],{},"月次コストレポートの自動化",[45,852,854],{"id":853},"_2-optimize最適化","2. Optimize（最適化）",[118,856,857,860,863],{},[121,858,859],{},"VPA 推奨値に基づくリソースのライトサイジング",[121,861,862],{},"スポットインスタンスの活用率向上",[121,864,865],{},"未使用リソース（放置 PV、未使用 LB）の棚卸し",[45,867,869],{"id":868},"_3-operate運用","3. Operate（運用）",[118,871,872,875,878],{},[121,873,874],{},"コスト異常の自動アラート設定",[121,876,877],{},"チーム横断のコストレビュー会議（月次）",[121,879,880],{},"予算超過時の自動スケーリング制限",[11,882,883,888],{},[15,884,887],{"href":885,"rel":886},"https:\u002F\u002Fsoftjourn.com\u002Finsights\u002Fkubernetes-cost-optimization",[19],"Softjourn のガイド","によれば、これら15の最適化戦略を5日間で実装することで、Kubernetes 費用の 30〜50% を回収できます。",[32,890,892],{"id":891},"まとめkubo-で実現するコスト最適化","まとめ：Kubo で実現するコスト最適化",[11,894,895],{},"マネージド Kubernetes の料金は、コントロールプレーンだけでなくコンピュート・ストレージ・ネットワーク・サポートを含めて総合的に評価する必要があります。",[49,897,898,916],{},[52,899,900],{},[55,901,902,905,908,911,914],{},[58,903,904],{},"比較項目",[58,906,907],{},"EKS（小規模）",[58,909,910],{},"AKS（小規模）",[58,912,913],{},"GKE（小規模）",[58,915,29],{},[67,917,918,934,950,966],{},[55,919,920,922,925,928,931],{},[72,921,65],{},[72,923,924],{},"$100〜",[72,926,927],{},"$80〜",[72,929,930],{},"$85〜",[72,932,933],{},"48,000円〜",[55,935,936,939,942,944,947],{},[72,937,938],{},"コントロールプレーン",[72,940,941],{},"有料",[72,943,88],{},[72,945,946],{},"条件付き無料",[72,948,949],{},"込み",[55,951,952,955,958,961,963],{},[72,953,954],{},"隠れコスト",[72,956,957],{},"多い",[72,959,960],{},"やや多い",[72,962,960],{},[72,964,965],{},"明瞭",[55,967,968,971,974,977,979],{},[72,969,970],{},"運用負荷",[72,972,973],{},"高い",[72,975,976],{},"中程度",[72,978,976],{},[72,980,981],{},"低い",[11,983,984,990,991,994],{},[124,985,986,989],{},[15,987,29],{"href":27,"rel":988},[19]," は月額48,000円〜の明瞭な料金体系で、K3s ベースの本番グレード Kubernetes を提供します。"," マネージドサービスならではの運用コスト削減と、",[15,992,492],{"href":490,"rel":993},[19]," による AI ワークロード最適化を組み合わせることで、総所有コスト（TCO）を大幅に削減できます。",[11,996,997,998,1003],{},"コスト最適化のご相談は ",[15,999,1002],{"href":1000,"rel":1001},"https:\u002F\u002Fwww.hexabase.com\u002Fcontact-us\u002F",[19],"お問い合わせ"," まで。",[1005,1006,1007],"style",{},"html pre.shiki code .s0U2E, html code.shiki .s0U2E{--shiki-default:#F7768E}html pre.shiki code .sAklC, html code.shiki .sAklC{--shiki-default:#89DDFF}html pre.shiki code .sPY7s, html code.shiki .sPY7s{--shiki-default:#9ECE6A}html pre.shiki code .sbD-w, html code.shiki .sbD-w{--shiki-default:#51597D;--shiki-default-font-style:italic}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html pre.shiki code .sOJ5S, html code.shiki .sOJ5S{--shiki-default:#FF9E64}html pre.shiki code .sgJMe, html code.shiki .sgJMe{--shiki-default:#9ABDF5}",{"title":263,"searchDepth":286,"depth":286,"links":1009},[1010,1015,1020,1024,1029,1034],{"id":34,"depth":286,"text":35,"children":1011},[1012,1013,1014],{"id":47,"depth":297,"text":47},{"id":107,"depth":297,"text":108},{"id":141,"depth":297,"text":141},{"id":230,"depth":286,"text":231,"children":1016},[1017,1018,1019],{"id":247,"depth":297,"text":248},{"id":395,"depth":297,"text":396},{"id":407,"depth":297,"text":407},{"id":430,"depth":286,"text":430,"children":1021},[1022,1023],{"id":433,"depth":297,"text":434},{"id":475,"depth":297,"text":476},{"id":499,"depth":286,"text":499,"children":1025},[1026,1027,1028],{"id":502,"depth":297,"text":502},{"id":676,"depth":297,"text":677},{"id":797,"depth":297,"text":797},{"id":826,"depth":286,"text":827,"children":1030},[1031,1032,1033],{"id":838,"depth":297,"text":839},{"id":853,"depth":297,"text":854},{"id":868,"depth":297,"text":869},{"id":891,"depth":286,"text":892},"2026-05-27","Kubernetes のクラウドコストを30〜50%削減する実践的な最適化戦略を解説。EKS・AKS・GKE の料金比較と Kubo の圧倒的コスト優位性を検証します。","md","ja",{},true,"\u002Fblog\u002Fja\u002Fkubernetes-cost-optimization-guide",{"title":5,"description":1036},"blog\u002Fja\u002Fkubernetes-cost-optimization-guide",[1045,1046,153,156,159,1047,1048,29],"Kubernetes","コスト最適化","FinOps","クラウドコスト","gtDge53ApRgllaMAtK1Y5ZLY2J75xKGY5CyTqdpX2HA",1779964617053]