Скачать с ютуб AWS S3 Tutorial (Part 6) - AWS Hands on Lab Amazon S3 - Object Lock в хорошем качестве

AWS S3 Tutorial (Part 6) - AWS Hands on Lab Amazon S3 - Object Lock

Versioning Video -    • AWS S3 Tutorial (Part 4) -  Amazon S3...   Bucket Policies Video -    • AWS S3 Tutorial (Part 3) - How  to se...   In this Video, We are learning about S3 Object Lock. Object locking in Amazon S3 is a feature that allows you to enforce a write-once-read-many (WORM) model for your S3 objects. This means that once you lock an object, it cannot be modified or deleted for a specified retention period, ensuring that the data is tamper-proof and compliant with regulatory requirements. To use object locking in S3, you can enable the feature on a per-bucket basis, and then specify a retention period for the objects in that bucket. You can also choose between two modes of object locking: Governance mode and Compliance mode. In Governance mode, bucket owners and users with specific permissions can still overwrite or delete locked objects, but only after they pass a specified object lock retention period. This mode is useful when you need to retain objects for a specific duration, but still want the flexibility to modify or delete them if necessary. In Compliance mode, locked objects cannot be overwritten or deleted by anyone, including the root user or bucket owner, until the retention period expires. This mode is ideal for meeting regulatory requirements or enforcing strict data retention policies. Object locking in S3 is useful in a variety of scenarios, such as financial and healthcare data management, legal document retention, and long-term data archiving. It provides an additional layer of protection and compliance, ensuring that your data is secure and tamper-proof. #AWSCertifiedDataAnalyticsSpecialty #AWS #AWSDAS-C01 #AWSDataEngineer #AWSDataAnalytics #DataAnalyticsSpecialty #AWSBigData #amazons3 AWS S3 Amazon S3 AWS Certified Data Analytics Specialty AWS Certified Data Analytics – Specialty (DAS-C01) Exam Guide AWS Big Data AWS Data Engineer AWS Data Analytics AWS Email: [email protected]