AWS CEO Adam Selipsky's keynote at re:Invent 2023 included announcements like S3 Express one zone offering fast cloud object storage with low latency. Other highlights include new features and integrations on AWS, continued pre-training in bedrock, and the introduction of fully managed agents for generative AI applications. Guardrails for filtering harmful content and the introduction of Amazon Q, a generative AI-powered assistant, were also discussed.
AWS announces S3 Express one zone, a new storage class in S3, designed for performance-critical applications with improved data access speeds and reduced costs.
Amazon Athena now supports querying data stored in S3 Express one zone, enabling faster query performance and accelerating data processing for latency-sensitive use cases.
Deep dives
New S3 Storage Class: S3 Express one zone
AWS announces the availability of the new storage class for S3 called S3 Express one zone. It is purpose-built for performance-critical applications that require fast data access speeds and low latency. S3 Express one zone significantly improves data access speeds by 10X, reduces request costs by 50%, and supports workload types like machine learning training, interactive analytics, and media content creation. This new storage class uses a new bucket type, S3 directory buckets, which allows for high request volumes and is available in several AWS regions.
Improved Data Querying with Amazon Athena
Amazon Athena now supports querying data stored in the S3 Express one zone storage class. This integration enables up to 2.1X faster query performance compared to S3 standard. By using Athena with S3 Express one zone, customers can accelerate data processing and analysis, particularly for latency-sensitive use cases like business intelligence analytics, financial risk monitoring, and sensor data processing. This improvement allows for faster query results, enhancing data discoverability, and reducing the time required for data analysis.
Enhancements to Amazon Bedrock
Amazon Bedrock introduces several new capabilities, including the ability to fine-tune models for specific tasks, fully managed knowledge bases for retrieving contextual and relevant company data, and guardrails for implementing responsible AI policies. The fine-tuning capability allows organizations to adapt foundation models with domain-specific knowledge, improving model accuracy. The knowledge bases feature connects foundation models to internal company data sources, enhancing model responses with up-to-date and proprietary information. Guardrails offer the ability to create customized protections and content filters to align with specific application requirements and adhere to responsible AI policies.
Our re:Invent 2023 coverage continues! In this episode, Jillian Forde shares highlights from Day 2 of re:Invent, including some big announcements from AWS CEO Adam Selipsky’s keynote.
Get the Snipd podcast app
Unlock the knowledge in podcasts with the podcast player of the future.
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
Share & Export
Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode