Category: Advanced (300)

Customers expect database solutions to be both scalable and equipped with robust recovery mechanisms to address unexpected data disruptions. Unintentional transactions or system failures can impact the business. Recovering to a specific point-in-time with point-in-time-recovery (PITR) is indispensable for some customers with critical workloads or compliance requirements AWS Backup simplifies protecting Amazon Aurora databases with […]

Faced with increasing amounts of data and a tightening economic climate, enterprises are looking to save money on their storage costs by moving rarely needed data to archival storage options. The least costly options require your internal systems to support receiving data back in hours or days, often called asynchronous retrievals. With this time delay, […]

Enterprises may want to customize their data sets for different requesting applications. For example, if you run an e-commerce website, you may want to mask Personally Identifiable Information (PII) when querying your data for analytics. Although you can create and store multiple customized copies of your data, that can increase your storage cost. You can […]

With ransomware a top concern for customers, backups are essential to data recovery and business continuity. Customers want a simple method, preferably in a user console, for enabling immutability for backup vaults holding the encrypted data copy. The write-once, read-many (WORM) model applied to backup data provides immutability to recover from accidental or malicious deletions. […]

For many stateful containerized applications, such as those using Kubernetes orchestration, each stateful pod (the smallest deployable container object) may require dedicated persistent storage. A block storage solution is a good fit due to its high performance, low latency, and persistence attributes. If a compute instance has more compute resources to spare, you can only […]

This post is Part 2 of a two-part blog post series that will take you, an application developer, through the process of configuring and developing a data application that authenticates users with Microsoft Entra ID and then uses S3 Access Grants to access data on those users’ behalf. Part 1 of this series gave an […]

This is Part 1 of a two-part blog series: Configuring the application. Here is Part 2: Developing the application. When we at AWS talk to our customers about their data lakes, they usually describe a desired access pattern in which users and groups from a corporate directory are granted access to datasets in Amazon Simple […]

Data is at the center of every machine learning pipeline. Whether pre-training foundation models (FMs), fine-tuning FMs with business-specific data, or serving inference queries, every step of the machine learning lifecycle needs low-cost, high-performance data storage to keep compute resources busy and performing useful work. Customers use Amazon Simple Storage Service (Amazon S3) to store training data […]

To adhere to the principle of least privilege, users define granular access to their Amazon Simple Storage Service (Amazon S3) data based on applications, personas, groups or organization units (OUs). This practice helps customers to mitigate the risk of unauthorized access, limiting potential damage in case of a security breach as employees only have access […]

As enterprises evolve their cloud governance practices, multiple teams working in separate accounts may need to share data. One team may oversee an enterprise data lake in one account, while a data science team develops a high-performance computing (HPC) use case in another account. Customers want to take advantage of low-cost object storage and be […]