Tag: Amazon Bedrock
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Amazon Bedrock Converse API vs InvokeModel, and When to Use Each (AWS Gen AI Series, Part 11)
InvokeModel hands you each model’s native JSON. The Converse API gives one request and one response shape for every chat model on Bedrock. Here is when to use each, and where InvokeModel is still the only door.
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Amazon Bedrock Private Access with PrivateLink and VPC Endpoints (AWS Gen AI Series, Part 9)
Bedrock traffic leaves your VPC by default. Here is how I wire it shut with PrivateLink interface endpoints, private DNS, and a scoped endpoint policy, plus what it costs per month.
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Amazon Bedrock Regions, Quotas, and Cross-Region Inference (AWS Gen AI Series, Part 8)
Regions decide which models you can call and how much throughput you get. Here is how Bedrock quotas, token burndown, and cross-Region inference profiles fit together, and how to size a quota request that gets approved.
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Amazon Bedrock Pricing Across On-Demand, Provisioned, and Batch (AWS Gen AI Series, Part 6)
The five ways Amazon Bedrock charges for the same model, from on-demand tokens to reserved model units, and the break-even math that tells you which mode your workload actually belongs on.
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Amazon Bedrock vs SageMaker AI, and When to Use Each (AWS Gen AI Series, Part 5)
Bedrock gives you models behind an API; SageMaker AI gives you the whole ML platform. Here is how I decide between them, with the cost math that usually settles it.
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Amazon Nova Models and Where Each One Fits (AWS Gen AI Series, Part 4)
A working tour of Amazon Nova on Bedrock: Micro, Lite, Pro and Premier, the creative and speech models, and what Nova 2 changes. With model IDs, context sizes, real cost math and the inference-profile trap that breaks first calls.
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Amazon Bedrock Model Catalog and Choosing a Model (AWS Gen AI Series, Part 3)
Bedrock ships more than a hundred models across fifteen providers, and the price gap between the cheapest and the priciest is over 400x. Here is how I read the catalog and pick a model without overpaying.
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Amazon Bedrock and the Shared Responsibility Model (AWS Gen AI Series, Part 2)
Bedrock is a managed service, but security is still split between AWS and you. Here is exactly which half is yours, the defaults that catch teams out, and the baseline I deploy before any prompt goes live.
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AWS Generative AI Stack, End to End (AWS Gen AI Series, Part 1)
AWS generative AI is really three layers: Amazon Bedrock for managed models, SageMaker AI to build your own, and Trainium and Inferentia underneath. Here is the whole map, with a real cost example and a first call that works.
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About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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