Amazon Bedrock is currently offered exclusively as a managed cloud service by AWS and is not available for private or on-premises deployments. It operates within AWS’s public cloud infrastructure, meaning all compute, storage, and model hosting are managed by AWS. Users interact with Bedrock via APIs to access pre-trained foundational models (e.g., Anthropic Claude, Stability AI) or fine-tune them using AWS-hosted resources. This design prioritizes scalability, ease of integration with other AWS services (like S3 or Lambda), and seamless updates to models and infrastructure handled by AWS.
AWS does not provide a self-hosted or isolated version of Bedrock for on-premises data centers or private clouds. However, organizations with strict data residency or compliance requirements can use AWS’s existing hybrid solutions, such as AWS Outposts or AWS PrivateLink, to create secure connections between on-premises infrastructure and Bedrock’s cloud-based APIs. For example, PrivateLink allows traffic to stay within the AWS network, reducing exposure to the public internet. While this doesn’t move Bedrock on-premises, it provides a layer of network isolation for regulated industries like healthcare or finance that need controlled access to cloud services.
If full on-premises AI/ML capabilities are required, developers might consider alternatives like deploying open-source models (e.g., Llama 2) via Amazon SageMaker on Outposts, which allows model training and inference in hybrid environments. Bedrock’s value lies in its managed service model, which simplifies access to cutting-edge AI without infrastructure overhead. For teams needing complete control over hardware or air-gapped environments, AWS’s current Bedrock offering does not meet those needs, and alternative solutions would be necessary.