Category: Amazon Simple Storage Service (S3)

At Snap Inc., the company behind Snapchat, cost is an important factor in every infrastructure decision. With research scientists and machine learning (ML) engineers working across a wide gamut of projects, from large language models to computer vision to video generation, the AI/ML platform team faces a constant balancing act: deliver the high-performance storage that […]

MIXI, Inc. operates FamilyAlbum, a service that approximately 30 million registered users rely on to share photos and videos with the people closest to them. As of January 2026, families have shared more than 20 billion photos and videos through the service. They can rediscover a specific precious moment — a baby’s first swim, an […]

S3 Files is a shared file system that connects any AWS compute directly with your data in Amazon S3. It provides fast, direct access to all of your S3 data as files with full file system semantics and low-latency performance, without your data ever leaving S3. That means file-based applications, agents, and teams can now access and work with S3 data as a file system using the tools they already depend on.

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 […]

Immutability is a foundational data protection control, protecting data in place against unintended changes and deletions by authorized users, and changes by unauthorized users. In many cases, however, it isn’t clear at the time data is written how long it needs to stay immutable, or when that period should begin. A signed contract might need […]