AWS Storage Blog

Data is the foundation of AWS Cloud migration, and choosing the right storage services is one of the earliest, most critical decisions enterprises face. Migrating to AWS storage is a chance to get right-size: you drop the wasted capacity you’ve been paying for and avoid the hardware refresh cycle that makes on-premises scaling so painful. […]

A completed storage assessment looks simple: an AWS Storage service recommended per workload, capacity and performance recommendations, and cost. This post walks through the analysis of how we go from analyzed data to right-sizing on AWS. In Part 1 of this series, we covered what an AWS Storage Assessment delivers: service recommendations, right-sized configurations, and […]

Data Protection and disaster recovery is an important part of any migration. Customers often only consider this once they have already migrated, which increases budgets beyond the initial estimate. The AWS Storage Assessment solves this: the same source telemetry that sizes your primary storage also produces your data protection costs. No additional data collection, no […]

Apache Kafka usually stores its logs on local disk, which fills up and forces teams to offload data and maintain custom tooling. With Amazon S3 Files, you can mount an S3 bucket as an NFS file system and point Kafka’s log directories to it, running diskless Kafka. This post shows how, with a multi-Region setup and performance benchmarks.

Customer Story | Amazon S3 Tables – Learn how Comcast redesigned their analytics layer with GraphQL and Amazon S3 Tables, scaling to 80x higher concurrent request volumes while cutting costs by 38% and reducing query latency by 28%. Comcast is building America’s largest and most intelligent broadband network with a simple purpose: connect everyone, everywhere […]

When running large language model (LLM) inference at scale on AWS, the GPU might not be the only thing that limits you. The GPU generates tokens fast, but what then contributes to performance is everything around it: memory, storage, and the network path that connects them. That’s the difference between a demo and production. Training […]

At Precisely, the team is reimagining the user experience for its Data Integrity Suite by adding a conversational interface powered by AI agents to the traditional UI. With this enhancement, users can interact with the platform more naturally and intuitively (asking questions, making requests, and exploring data assets through dialogue) while still benefiting from the […]

Organizations store vast amounts of data in Amazon S3 for machine learning, data analytics, media processing, and generative AI workloads. Many of the applications, agents, and teams that work with that data are file-based: they read and write on a mounted path using the file and directory operations and POSIX tools they already depend on. […]

Organizations that receive files from external partners through SFTP face a persistent operational challenge: routing each file to the correct downstream system. Invoices, contracts, images, CSVs, and reports all arrive in a single landing zone, and each requires a different destination. The traditional approach—pattern-matching on file names with regular expressions—is inherently fragile. It relies on […]

Semiconductor verification teams run thousands of simulation jobs every night using Electronic Design Automation (EDA) tools. A large verification environment can generate logs from 100,000 or more test executions per night. A single regression cycle produces simulation logs, compilation logs, and scheduler logs. For a regression with dozens of failures, manual triage typically takes 45–60 […]