Amazon S3 Encryption, Access Points & Secure Data Delivery | AWS ML Engineer |

In Week 2 Part 3 of my AWS Machine Learning Engineer – Associate learning journey, I focused on Amazon S3 security, especially how data can be protected while it is stored and while it is moving between a client and Amazon S3. In this video, I explain the main S3 encryption approaches: SSE-S3, SSE-KMS, SSE-C, and client-side encryption. I compare these options based on who manages the encryption keys, how much control the customer has, and the level of responsibility involved. I also cover SSE-KMS key control and auditing, KMS request quotas, and why HTTPS/TLS is important for protecting data in transit. Another important concept is the difference between S3 default encryption and bucket policies. Default encryption protects stored objects, while bucket policies can be used to enforce security requirements. Toward the end, I discuss S3 Access Points and how they can simplify access when multiple applications or teams use the same S3 bucket. I also introduce S3 Object Lambda, which can transform data as it is retrieved. A special thank you to Professor Victor Govindaswamy for his continuous guidance and dedication to our learning. I truly appreciate how he encourages us to explore these AWS concepts in detail and understand the reasoning behind them. His support is helping me strengthen my technical knowledge and become more confident as I continue preparing for the AWS Machine Learning Engineer – Associate certification. #AWS #AmazonWebServices #AmazonS3 #S3Security #Encryption #SSEKMS #AWSSecurity #AWSKMS #CloudSecurity #CloudComputing #AWSMachineLearning #MachineLearning #AWSCertification #S3AccessPoints #ObjectLambda #AWSLearning #MachineLearningEngineer #CertificationJourney