Amazon Bedrock Security and Privacy
This lesson explores the security, privacy, and governance facets of Amazon Bedrock for creating responsible generative AI applications. It covers encryption for data privacy, AWS' pledge to refrain from using customer data for model training, access control through IAM, auditing via AWS CloudTrail and CloudWatch, compliance with diverse standards, and the implementation of Guardrails for responsible AI interactions.
Learning Objectives
Obtain a greater understanding of Amazon Bedrock’s security and privacy features, including:
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Security and encryption
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Privacy and data protection
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Identity and access management
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Auditing, compliance, and governance
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Guardrails that help provide safeguards against undesirable and harmful content
Intended Audience
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Application developers who are looking to build responsible AI applications using Amazon Bedrock
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Administrators responsible for ensuring that an organization’s generative AI applications are safe, secure, and conform with compliance standards such as ISO, HIPAA, and GDPR
Prerequisites
To get the most out of this lesson, you should have a basic understanding of AWS as well as a high-level understanding of generative AI.
Danny has over 20 years of IT experience as a software developer, cloud engineer, and technical trainer. After attending a conference on cloud computing in 2009, he knew he wanted to build his career around what was still a very new, emerging technology at the time — and share this transformational knowledge with others. He has spoken to IT professional audiences at local, regional, and national user groups and conferences. He has delivered in-person classroom and virtual training, interactive webinars, and authored video training courses covering many different technologies, including Amazon Web Services. He currently has nine active AWS certifications, including certifications at the Professional and Specialty level.