Storage: S3, EBS & EFS

Industry-leading object, block, and file storage.

5 sessions at the summit5 external resources

Overview

Amazon S3 is the foundational object store for the cloud — 11 nines of durability, virtually unlimited scale, and the basis for data lakes, backups, and content delivery. S3 Express One Zone delivers single-digit-millisecond latency for high-performance workloads. Amazon EBS provides block storage for EC2 (gp3 is the modern default). Amazon EFS provides shared NFS, and Amazon FSx covers Windows, Lustre (HPC/ML), NetApp ONTAP, and OpenZFS file systems.

Key concepts

  1. S3 storage classes: Standard, Intelligent-Tiering, Glacier tiers
  2. S3 Tables — Iceberg-native bucket type for analytics
  3. S3 Vectors — native vector storage for AI workloads
  4. EBS volume types: gp3, io2 Block Express, st1, sc1
  5. Backup, replication, and lifecycle policies

Key AWS services

  • Amazon S3
  • Amazon EBS
  • Amazon EFS
  • Amazon FSx
  • AWS Backup

Learn more — curated resources

Hand-picked official docs, foundational papers, and the best community guides for going deeper on this topic.

Sessions on this topic

5 sessions from the Summit covered this topic. Each is a self-contained mini-lesson.

  1. DEV207Intermediate

    Data Observability Without the Pain - Lessons from a Production System

    Modern IoT platforms are inherently data platforms. Events flow through APIs, queues, AWS Lambda Serverless functions, storage systems, and device networks before becoming meaningful data. When something goes wrong, tracing a single event across these distributed components quickly becomes painfuland the question shifts from _what happened_ to _where do I even start looking Ill walk through three practical observability patterns drawn from building and operating a production, event-driven IoT healthcare platform on AWS that processes tens of thousands of device events daily. Using OpenTelemetry, AWS X-Ray and Honeycomb, well explore techniques for gaining visibility into asynchronous event pipelines, correlating activity across services, and tracing events as they move through distributed systems. Youll leave with three concrete patterns you can apply immediately to your own event-driven data systems.

  2. STP208Intermediate

    NextAI's LegalScout: A Data Foundation for Private Legal AI

    LegalScout helps Australian SME law firms turn Generative AI into a competitive advantage by securely leveraging their own client data and confidential matters to work smarter, not harder. Built with Australian lawyers on AWS using Amazon Bedrock for inference and Amazon S3Vectors for secure document searches, it automates repetitive work, streamlines workflows, and improves drafting, contract review, and research to boost productivity, reduce costs, and lift accuracy while maintaining strict privacy and compliance.

  3. DAT401Expert

    Real-Time DataLakes with Apache Iceberg, Amazon MSK, and Amazon S3

    Learn how to optimize Apache Iceberg data lakes on Amazon S3 for cost-effectiveness while enabling real-time analytics. This session explores S3 Tables deployments, focusing on streaming data from Apache Kafka via Amazon MSK into Iceberg format. Discover practical approaches for real-time table maintenance, metadata optimization for high-velocity writes, and data compaction strategies. Implement cost-effective retention policies using S3 Lifecycle configurations while maintaining sub-minute data freshness. See how MSK's native Iceberg integration eliminates pipeline overhead, reducing latency and operational costs. Gain actionable insights for balancing streaming performance with cost optimization at scale.

  4. ISV206Intermediate

    Scaling RAG to Millions of Vectors: The Squiz Story

    Squiz, a global Digital Experience Platform provider, is transforming how organizations deliver conversational search experiences. By adopting Amazon S3 Vectors, Squiz reimagined its ingestion pipeline — increasing data processing speed by 50% and shifting from bespoke, always-on infrastructure to a scalable serverless model. This allows Squiz to seamlessly scale from 25,000 to millions of vectors per client, while significantly reducing costs. Hear how this shift freed engineering teams to focus on RAG innovation rather than infrastructure management, and how it powers smart video search capabilities across their platform.

  5. DEV310Advanced

    Zero-Downtime Migration from Sydney to Auckland (ap-southeast-6)

    With AWS ap-southeast-6 (Auckland) now open, New Zealand organizations can repatriate workloads from Sydney. This advanced session provides practical migration strategies minimizing downtime and eliminating data loss across every layer of your stack. You'll learn region-to-region migration patterns for: *Storage*: S3 replication, EBS snapshots, EFS cross-region transfers *Databases*: RDS read replicas, DynamoDB global tables, self-managed EC2 database replication *Applications*: Lambda, ECS/EKS workload migration, EC2 AMI copying Walk away with a prioritized migration playbook, realistic RTO/RPO targets, and battle-tested sequencing strategies for large-scale data transfers without extended application outages.

Non-obvious insights

From the Playbook

One sharp, contrarian insight per session — the things teams don't think of unprompted.

The biggest observability win is not tools — it's a *correlation ID standard* the team enforces. Pick one (the X-Ray trace ID is fine), enforce it everywhere, and stop debating. Tooling matters far less than you think once the IDs are consistent. ---DEV207 — Data Observability Without the Pain - Lessons from a…
NZ region opens up GovTech NZ in ways the Sydney region couldn't. The compliance change unlocks a market segment that wasn't accessible before. Sales conversations shift from "but our data" to "show me the integration." ---DEV310 — Zero-Downtime Migration from Sydney to Auckland (ap-…