{"id":41229,"date":"2026-03-12T09:00:30","date_gmt":"2026-03-12T06:00:30","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/"},"modified":"2026-03-12T09:00:30","modified_gmt":"2026-03-12T06:00:30","slug":"bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/","title":{"rendered":"Bedrock Faturan\u0131z Zaman \u0130\u015fleyen Bir Saat Gibi \u2013 \u0130\u015fte Onu Durdurman\u0131n Yollar\u0131"},"content":{"rendered":"

Bedrock Faturan\u0131z Zaman \u0130\u015fleyen Bir Saat Gibi \u2013 \u0130\u015fte Onu Durdurman\u0131n Yollar\u0131<\/h2>\n

Amazon Bedrock, \u00fcretken yapay zeka uygulamalar\u0131 geli\u015ftirmek i\u00e7in g\u00fc\u00e7l\u00fc bir platform sunar. Ancak bu g\u00fcc\u00fcn beraberinde getirdi\u011fi maliyetler, dikkatli y\u00f6netilmedi\u011finde h\u0131zla birikerek i\u015fletmeler i\u00e7in beklenmedik faturalara d\u00f6n\u00fc\u015febilir. T\u0131pk\u0131 zaman i\u015fleyen bir saat gibi, Bedrock kullan\u0131m\u0131n\u0131z da s\u00fcrekli artan bir maliyet potansiyeli ta\u015f\u0131r. Bu makale, Bedrock faturan\u0131z\u0131 kontrol alt\u0131na alman\u0131n ve gereksiz harcamalar\u0131 durdurman\u0131n teknik stratejilerini detayland\u0131racakt\u0131r.<\/p>\n

1. Bedrock Maliyet Mekanizmas\u0131n\u0131 Anlamak<\/h3>\n

Bedrock maliyetleri, kulland\u0131\u011f\u0131n\u0131z temel modellere ve kullan\u0131m \u015feklinize g\u00f6re de\u011fi\u015fiklik g\u00f6sterir. Bu mekanizmay\u0131 anlamak, optimizasyonun ilk ad\u0131m\u0131d\u0131r.<\/p>\n

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1.1. Token Bazl\u0131 \u00dccretlendirme Modeli<\/h3>\n<\/h4>\n

Bedrock’taki \u00e7o\u011fu model, giri\u015f (input) ve \u00e7\u0131k\u0131\u015f (output) token’lar\u0131na g\u00f6re \u00fccretlendirilir. Token’lar, kelimelerin veya karakterlerin belirli par\u00e7alar\u0131d\u0131r. Daha uzun prompt’lar ve daha uzun yan\u0131tlar, daha fazla token ve dolay\u0131s\u0131yla daha y\u00fcksek maliyet anlam\u0131na gelir. Her modelin token ba\u015f\u0131na farkl\u0131 bir maliyeti oldu\u011funu unutmamak \u00f6nemlidir. \u00d6rne\u011fin, Anthropic Claude veya Amazon Titan modelleri farkl\u0131 fiyatland\u0131rma yap\u0131lar\u0131na sahiptir.<\/p>\n

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1.2. Model Se\u00e7imi ve \u00d6zelle\u015ftirme Maliyetleri<\/h3>\n<\/h4>\n

Kulland\u0131\u011f\u0131n\u0131z temel modelin karma\u015f\u0131kl\u0131\u011f\u0131 ve boyutu, maliyeti do\u011frudan etkiler. Daha b\u00fcy\u00fck ve yetenekli modeller genellikle daha pahal\u0131d\u0131r. Ayr\u0131ca, kendi verilerinizle modelleri \u00f6zelle\u015ftirmek (fine-tuning) ek e\u011fitim ve depolama maliyetleri yarat\u0131r. Bu \u00f6zelle\u015ftirilmi\u015f modellerin kullan\u0131m\u0131 da standart modellerden daha y\u00fcksek \u00fccretlere tabi olabilir.<\/p>\n

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1.3. Vekt\u00f6r Veritaban\u0131 ve Depolama \u00dccretleri<\/h3>\n<\/h4>\n

Bedrock ile birlikte kullan\u0131lan bilgi tabanlar\u0131 (Knowledge Bases) ve vekt\u00f6r veritabanlar\u0131 (\u00f6rne\u011fin Amazon OpenSearch Serverless veya Pinecone), depolad\u0131\u011f\u0131n\u0131z veri miktar\u0131na ve sorgu yo\u011funlu\u011funa g\u00f6re ek maliyetler olu\u015fturur. Bu bile\u015fenler, Bedrock’un RAG (Retrieval Augmented Generation) yeteneklerini kullan\u0131rken devreye girer ve ayr\u0131 ayr\u0131 izlenmesi gereken birer maliyet kalemidir.<\/p>\n

2. Ak\u0131ll\u0131 Model Se\u00e7imi ve Optimizasyonu<\/h3>\n

Do\u011fru modeli do\u011fru g\u00f6rev i\u00e7in se\u00e7mek, Bedrock maliyetlerini d\u00fc\u015f\u00fcrmenin en etkili yollar\u0131ndan biridir.<\/p>\n

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2.1. G\u00f6reve \u00d6zel En K\u00fc\u00e7\u00fck Modeli Kullanma<\/h3>\n<\/h4>\n

Her g\u00f6rev i\u00e7in en b\u00fcy\u00fck ve en yetenekli modeli kullanmak yerine, ihtiyac\u0131n\u0131z\u0131 kar\u015f\u0131layacak en k\u00fc\u00e7\u00fck ve en uygun maliyetli modeli se\u00e7in. \u00d6rne\u011fin, basit bir metin \u00f6zetleme veya s\u0131n\u0131fland\u0131rma g\u00f6revi i\u00e7in daha k\u00fc\u00e7\u00fck bir model yeterli olabilirken, karma\u015f\u0131k yarat\u0131c\u0131 yaz\u0131m veya kod \u00fcretimi i\u00e7in daha b\u00fcy\u00fck bir modele ihtiya\u00e7 duyulabilir. Farkl\u0131 modelleri test ederek performans\/maliyet dengesini bulun.<\/p>\n

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2.2. A\u00e7\u0131k Kaynak Modelleri De\u011ferlendirme (Bedrock \u00dczerinden)<\/h3>\n<\/h4>\n

Bedrock, baz\u0131 a\u00e7\u0131k kaynakl\u0131 modelleri (\u00f6rne\u011fin Meta Llama 2) de sunar. Bu modellerin token maliyetleri, tescilli modellere g\u00f6re daha uygun olabilir. Uygulaman\u0131z\u0131n gereksinimleri do\u011frultusunda a\u00e7\u0131k kaynak modellerinin yeteneklerini de\u011ferlendirmek, \u00f6nemli \u00f6l\u00e7\u00fcde maliyet tasarrufu sa\u011flayabilir. Ancak, a\u00e7\u0131k kaynak modellerin performans ve g\u00fcvenlik konular\u0131nda tescilli modellere g\u00f6re farkl\u0131l\u0131klar g\u00f6sterebilece\u011fini unutmay\u0131n.<\/p>\n

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2.3. Model \u00d6zelle\u015ftirme \u0130htiyac\u0131n\u0131 Sorgulama<\/h3>\n<\/h4>\n

Model \u00f6zelle\u015ftirme (fine-tuning) maliyetli bir s\u00fcre\u00e7tir. Uygulaman\u0131z\u0131n ger\u00e7ekten \u00f6zelle\u015ftirilmi\u015f bir modele ihtiyac\u0131 olup olmad\u0131\u011f\u0131n\u0131 de\u011ferlendirin. Bazen iyi tasarlanm\u0131\u015f prompt m\u00fchendisli\u011fi, \u00f6zelle\u015ftirmeye gerek kalmadan benzer sonu\u00e7lar verebilir. \u00d6zelle\u015ftirme yapmadan \u00f6nce prompt m\u00fchendisli\u011fi ve RAG yakla\u015f\u0131mlar\u0131n\u0131n t\u00fcm potansiyelini kulland\u0131\u011f\u0131n\u0131zdan emin olun.<\/p>\n

3. Etkin Prompt M\u00fchendisli\u011fi ve Token Y\u00f6netimi<\/h3>\n

Prompt’lar\u0131n\u0131z\u0131 ve yan\u0131tlar\u0131n\u0131z\u0131 optimize etmek, do\u011frudan token kullan\u0131m\u0131n\u0131 ve dolay\u0131s\u0131yla maliyetleri etkiler.<\/p>\n

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3.1. Prompt’lar\u0131 K\u0131sa ve Net Tutma<\/h3>\n<\/h4>\n

Gereksiz kelimelerden, tekrarlardan ve a\u015f\u0131r\u0131 ba\u011flamdan ka\u00e7\u0131narak prompt’lar\u0131n\u0131z\u0131 olabildi\u011fince k\u0131sa ve net tutun. Modelin ihtiyac\u0131 olan bilgiyi en \u00f6zl\u00fc \u015fekilde sa\u011flay\u0131n. Her ek token, faturan\u0131za yans\u0131yan bir maliyettir. Prompt’lar\u0131n\u0131z\u0131 tasarlarken “token ekonomisi” bak\u0131\u015f a\u00e7\u0131s\u0131yla hareket edin.<\/p>\n

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3.2. \u00c7\u0131kt\u0131 Token’lar\u0131n\u0131 S\u0131n\u0131rlama<\/h3>\n<\/h4>\n

Modelden bekledi\u011finiz yan\u0131t\u0131n maksimum uzunlu\u011funu max_tokens_to_sample<\/code> veya benzeri parametrelerle s\u0131n\u0131rlay\u0131n. Bu, modelin gereksiz yere uzun yan\u0131tlar \u00fcretmesini engeller ve maliyetleri kontrol alt\u0131nda tutar. \u00d6rne\u011fin, bir \u00f6zetleme g\u00f6revi i\u00e7in 50 token yeterliyse, 500 token’l\u0131k bir limit belirlemek israft\u0131r.<\/p>\n

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3.3. Batch \u0130\u015fleme ve Asenkron Kullan\u0131m<\/h3>\n<\/h4>\n

Benzer veya ayn\u0131 anda i\u015flenebilecek birden fazla iste\u011fi tek bir \u00e7a\u011fr\u0131da birle\u015ftirerek (batch processing) API \u00e7a\u011fr\u0131s\u0131 overhead’ini ve dolay\u0131s\u0131yla maliyetleri azaltabilirsiniz. Ayr\u0131ca, ger\u00e7ek zamanl\u0131 yan\u0131t gerektirmeyen durumlar i\u00e7in asenkron API \u00e7a\u011fr\u0131lar\u0131n\u0131 tercih ederek sistem kaynaklar\u0131n\u0131 daha verimli kullanabilir ve potansiyel olarak daha uygun maliyetli i\u015flem katmanlar\u0131ndan faydalanabilirsiniz.<\/p>\n

4. Kapsaml\u0131 Kullan\u0131m \u0130zleme ve B\u00fct\u00e7eleme<\/h3>\n

Maliyetleri kontrol alt\u0131nda tutman\u0131n anahtar\u0131, ne kadar harcad\u0131\u011f\u0131n\u0131z\u0131 bilmek ve proaktif \u00f6nlemler almakt\u0131r.<\/p>\n

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4.1. AWS Cost Explorer ve B\u00fct\u00e7eler ile \u0130zleme<\/h3>\n<\/h4>\n

AWS Cost Explorer’\u0131 kullanarak Bedrock harcamalar\u0131n\u0131z\u0131 detayl\u0131 bir \u015fekilde inceleyin. Hangi modellerin, hangi uygulamalar\u0131n veya hangi zaman dilimlerinde en \u00e7ok maliyet olu\u015fturdu\u011funu belirleyin. AWS Budgets hizmetini kullanarak belirli bir Bedrock kullan\u0131m e\u015fi\u011fine ula\u015ft\u0131\u011f\u0131n\u0131zda bildirimler ayarlay\u0131n. Bu, s\u00fcrpriz faturalar\u0131n \u00f6n\u00fcne ge\u00e7menizi sa\u011flar.<\/p>\n

{\n  \"BudgetLimit\": {\n    \"Amount\": \"50.0\",\n    \"Unit\": \"USD\"\n  },\n  \"BudgetName\": \"BedrockMonthlyBudget\",\n  \"BudgetType\": \"COST\",\n  \"TimeUnit\": \"MONTHLY\",\n  \"CostFilters\": {\n    \"Service\": [\"Amazon Bedrock\"]\n  },\n  \"NotificationsWithSubscribers\": [\n    {\n      \"Notification\": {\n        \"NotificationType\": \"ACTUAL\",\n        \"ComparisonOperator\": \"GREATER_THAN\",\n        \"Threshold\": 80,\n        \"ThresholdType\": \"PERCENTAGE\"\n      },\n      \"Subscribers\": [\n        {\n          \"SubscriptionType\": \"EMAIL\",\n          \"Address\": \"your_email@example.com\"\n        }\n      ]\n    }\n  ]\n}<\/pre>\n
<\/code>
\n*Yukar\u0131daki JSON, AWS Budgets i\u00e7in Bedrock hizmetine \u00f6zel ayl\u0131k 50 USD b\u00fct\u00e7e ve %80 e\u015fi\u011finde e-posta bildirimi ayarlamak i\u00e7in kullan\u0131labilir.*<\/p>\n
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4.2. CloudWatch Metrikleri ve Alarmlar\u0131<\/h3>\n<\/h4>\n
Amazon CloudWatch, Bedrock kullan\u0131m\u0131n\u0131zla ilgili metrikleri (\u00f6rne\u011fin, \u00e7a\u011fr\u0131 say\u0131s\u0131, token say\u0131s\u0131) izlemenize olanak tan\u0131r. Bu metrikler \u00fczerinden alarmlar kurarak beklenmedik kullan\u0131m art\u0131\u015flar\u0131nda an\u0131nda haberdar olabilirsiniz. \u00d6rne\u011fin, belirli bir modelin saatlik token kullan\u0131m\u0131n\u0131n anormal seviyelere \u00e7\u0131kmas\u0131 durumunda bir alarm tetiklenebilir.<\/p>\n
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4.3. Kaynak Etiketleme (Tagging)<\/h3>\n<\/h4>\n
Bedrock ile ili\u015fkili t\u00fcm kaynaklar\u0131n\u0131z\u0131 (\u00f6rne\u011fin, Lambda fonksiyonlar\u0131, S3 kovalar\u0131, vekt\u00f6r veritabanlar\u0131) tutarl\u0131 bir \u015fekilde etiketleyin. Uygulama ad\u0131, departman veya proje gibi etiketler kullanarak maliyetlerinizi daha gran\u00fcler bir \u015fekilde analiz edebilir ve hangi ekibin veya projenin Bedrock maliyetlerine ne kadar katk\u0131da bulundu\u011funu kolayca g\u00f6rebilirsiniz.<\/p>\n
5. \u00d6nbellekleme (Caching) ve Tekrarl\u0131 \u0130stekleri Azaltma<\/h3>\n
Tekrarlayan sorgular i\u00e7in her seferinde LLM'ye ba\u015fvurmak yerine \u00f6nbellekleme stratejileri uygulamak, maliyetleri \u00f6nemli \u00f6l\u00e7\u00fcde d\u00fc\u015f\u00fcrebilir.<\/p>\n
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5.1. S\u0131k Tekrarlayan Sorgular \u0130\u00e7in \u00d6nbellek Kullan\u0131m\u0131<\/h3>\n<\/h4>\n
Uygulaman\u0131zda s\u0131k\u00e7a tekrarlayan ve ayn\u0131 yan\u0131t\u0131 veren sorgular i\u00e7in bir \u00f6nbellek mekanizmas\u0131 (\u00f6rne\u011fin, Amazon ElastiCache for Redis veya bir yerel bellek \u00f6nbelle\u011fi) kullan\u0131n. Bu sayede, modelden daha \u00f6nce al\u0131nm\u0131\u015f bir yan\u0131t\u0131 tekrar sormak yerine \u00f6nbellekten servis edebilirsiniz. Bu, \u00f6zellikle sabit veya nadiren de\u011fi\u015fen bilgiler i\u00e7in \u00e7ok etkilidir.<\/p>\n
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5.2. Yan\u0131tlar\u0131n Ge\u00e7erlilik S\u00fcresi (TTL) Y\u00f6netimi<\/h3>\n<\/h4>\n
\u00d6nbellekteki verilerin ne kadar s\u00fcreyle ge\u00e7erli olaca\u011f\u0131n\u0131 (Time-To-Live - TTL) dikkatlice belirleyin. \u00c7ok k\u0131sa bir TTL, \u00f6nbelle\u011fin etkinli\u011fini azalt\u0131rken, \u00e7ok uzun bir TTL eski verilerin sunulmas\u0131na neden olabilir. Uygulaman\u0131z\u0131n veri tazeli\u011fi gereksinimlerine g\u00f6re uygun bir TTL ayarlay\u0131n.<\/p>\n
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5.3. Yanl\u0131\u015f Kullan\u0131m ve Yetkisiz Eri\u015fim Kontrol\u00fc<\/h3>\n<\/h4>\n
AWS IAM politikalar\u0131 ile Bedrock API'lerine eri\u015fimi s\u0131k\u0131 bir \u015fekilde kontrol edin. Sadece belirli rollerin veya kullan\u0131c\u0131lar\u0131n belirli modelleri kullanmas\u0131na izin verin. Bu, yanl\u0131\u015fl\u0131kla veya k\u00f6t\u00fc niyetli a\u015f\u0131r\u0131 kullan\u0131mdan kaynaklanan maliyetleri \u00f6nlemeye yard\u0131mc\u0131 olur. Minimum ayr\u0131cal\u0131k ilkesini uygulayarak sadece gerekli izinleri verin.<\/p>\n
Sonu\u00e7<\/h3>\n
AWS Bedrock, \u00fcretken yapay zekan\u0131n g\u00fcc\u00fcn\u00fc parmaklar\u0131n\u0131z\u0131n ucuna getirirken, bu g\u00fcc\u00fcn maliyetlerini y\u00f6netmek kritik \u00f6neme sahiptir. Bedrock faturan\u0131z\u0131n zaman i\u015fleyen bir saat gibi kontrolden \u00e7\u0131kmas\u0131n\u0131 engellemek i\u00e7in model se\u00e7imi, prompt m\u00fchendisli\u011fi, detayl\u0131 izleme, b\u00fct\u00e7eleme ve \u00f6nbellekleme gibi stratejileri bir arada kullanmak esast\u0131r. Bu teknik yakla\u015f\u0131mlar\u0131 uygulayarak, Bedrock'un sundu\u011fu yenilik\u00e7i yeteneklerden tam anlam\u0131yla faydalan\u0131rken, ayn\u0131 zamanda maliyetlerinizi optimize edebilir ve s\u00fcrd\u00fcr\u00fclebilir bir yapay zeka operasyonu y\u00fcr\u00fctebilirsiniz.<\/p>\n
SSS (S\u0131k Sorulan Sorular)<\/h3>\n
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Bedrock maliyetleri en \u00e7ok neyden kaynaklan\u0131r?<\/h3>\n<\/h4>\n
Bedrock maliyetleri genellikle en \u00e7ok kullan\u0131lan temel modelin token ba\u015f\u0131na \u00fccretinden ve g\u00f6nderilen\/al\u0131nan token say\u0131s\u0131ndan kaynaklan\u0131r. Model se\u00e7imi, prompt uzunlu\u011fu ve yan\u0131t boyutu en b\u00fcy\u00fck etkenlerdir.<\/p>\n
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Daha ucuz bir Bedrock modeli se\u00e7mek performans\u0131 d\u00fc\u015f\u00fcr\u00fcr m\u00fc?<\/h3>\n<\/h4>\n
Her zaman de\u011fil. Daha k\u00fc\u00e7\u00fck veya daha uygun maliyetli bir model, belirli bir g\u00f6rev i\u00e7in yeterince iyi performans g\u00f6sterebilir. \u00d6nemli olan, uygulaman\u0131z\u0131n gereksinimlerini kar\u015f\u0131layacak en verimli modeli bulmakt\u0131r. Kapsaml\u0131 testler yapmak \u00f6nemlidir.<\/p>\n
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Prompt m\u00fchendisli\u011fi maliyetleri nas\u0131l etkiler?<\/h3>\n<\/h4>\n
\u0130yi prompt m\u00fchendisli\u011fi, modelden daha az token kullanarak daha do\u011fru ve hedefe y\u00f6nelik yan\u0131tlar alman\u0131z\u0131 sa\u011flar. Gereksiz kelimelerden ar\u0131nd\u0131r\u0131lm\u0131\u015f, net ve k\u0131sa prompt'lar, giri\u015f token maliyetlerini d\u00fc\u015f\u00fcr\u00fcrken, max_tokens_to_sample<\/code> ile yan\u0131tlar\u0131 s\u0131n\u0131rlamak \u00e7\u0131k\u0131\u015f token maliyetlerini kontrol eder.<\/p>\n
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Bedrock kullan\u0131m\u0131m\u0131 nas\u0131l izleyebilirim?<\/h3>\n<\/h4>\n
AWS Cost Explorer ile genel maliyetleri, AWS Budgets ile harcama e\u015fiklerini ve Amazon CloudWatch ile Bedrock API \u00e7a\u011fr\u0131lar\u0131 ve token kullan\u0131m\u0131 gibi detayl\u0131 metrikleri izleyebilirsiniz.<\/p>\n
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\u00d6nbellekleme Bedrock maliyetlerini ne kadar d\u00fc\u015f\u00fcrebilir?<\/h3>\n<\/h4>\n
Uygulaman\u0131z\u0131n do\u011fas\u0131na ba\u011fl\u0131 olarak \u00f6nbellekleme, tekrarlayan sorgular i\u00e7in Bedrock API \u00e7a\u011fr\u0131lar\u0131n\u0131 tamamen ortadan kald\u0131rarak \u00f6nemli \u00f6l\u00e7\u00fcde maliyet tasarrufu sa\u011flayabilir. \u00d6zellikle s\u0131k\u00e7a sorulan ve yan\u0131t\u0131 de\u011fi\u015fmeyen sorular i\u00e7in \u00e7ok etkilidir.<\/p>\n
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Kendi modelimi Bedrock'ta \u00f6zelle\u015ftirmek ne kadar maliyetli?<\/h3>\n<\/h4>\n
Model \u00f6zelle\u015ftirme (fine-tuning) i\u00e7in veri haz\u0131rl\u0131\u011f\u0131, e\u011fitim s\u00fcresi ve \u00f6zelle\u015ftirilmi\u015f modelin depolanmas\u0131 gibi ek maliyetler olu\u015fur. Ayr\u0131ca, \u00f6zelle\u015ftirilmi\u015f modellerin kullan\u0131m \u00fccretleri standart modellere g\u00f6re daha y\u00fcksek olabilir. \u00d6zelle\u015ftirme yapmadan \u00f6nce fayda\/maliyet analizini dikkatlice yapmal\u0131s\u0131n\u0131z.<\/p>\n","protected":false},"excerpt":{"rendered":"{ “BudgetLimit”: { “Amount”: “50.","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_subscribe_form":"","csco_page_contact_form":"","footnotes":""},"categories":[1],"tags":[],"class_list":{"0":"post-41229","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-genel","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"\nBedrock Faturan\u0131z Zaman \u0130\u015fleyen Bir Saat Gibi \u2013 \u0130\u015fte Onu Durdurman\u0131n Yollar\u0131 - Kodlar\u0131n Gizemli D\u00fcnyas\u0131<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Bedrock Faturan\u0131z Zaman \u0130\u015fleyen Bir Saat Gibi \u2013 \u0130\u015fte Onu Durdurman\u0131n Yollar\u0131\" \/>\n<meta property=\"og:description\" content=\"{ "BudgetLimit": { "Amount": "50.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/\" \/>\n<meta property=\"og:site_name\" content=\"Kodlar\u0131n Gizemli D\u00fcnyas\u0131\" \/>\n<meta property=\"article:published_time\" content=\"2026-03-12T06:00:30+00:00\" \/>\n<meta name=\"author\" content=\"Fatih Soysal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Fatih Soysal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tahmini okuma s\u00fcresi\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/\"},\"author\":{\"name\":\"Fatih Soysal\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"headline\":\"Bedrock Faturan\u0131z Zaman \u0130\u015fleyen Bir Saat Gibi \u2013 \u0130\u015fte Onu Durdurman\u0131n Yollar\u0131\",\"datePublished\":\"2026-03-12T06:00:30+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/\"},\"wordCount\":1690,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/#respond\"]}],\"copyrightYear\":\"2026\",\"copyrightHolder\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/bedrock-faturaniz-zaman-isleyen-bir-saat-gibi-iste-onu-durdurmanin-yollari\/\",\"name\":\"Bedrock Faturan\u0131z Zaman \u0130\u015fleyen Bir Saat Gibi \u2013 \u0130\u015fte Onu Durdurman\u0131n Yollar\u0131 - 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