All skills
aws avatar

/aws-storage

@4666f4e

Selects, investigates, and compares AWS object, file, and block storage services, and answers cost, performance, configuration, security, and troubleshooting questions about storage services. Applies when a user asks where to store or archive data based on their usage patterns; which storage service to choose or how two compare; how to migrate data from on-premises or between AWS services; how to protect, replicate, or recover data; how to optimize storage costs; where to deploy shared NFS, SMB, or POSIX file systems; where to store vector embeddings or tabular data; what storage backs enterprise file shares, self-managed databases on EC2, VMware, or stateful containers; or asks what an AWS storage service can do or how it works. Relevant for storage needs for workloads such as AI/ML, analytics, EDA, HPC, media, genomics, or financial trading. Not applicable for SQL query engines (Athena, Spark, Redshift, EMR), ETL (Glue), streaming (Kafka, MSK, Kinesis), or managed database services (RDS, Aurora, DynamoDB).

Use this Skill: https://skilld.dev/gh/aws/agent-toolkit-for-aws/aws-storage

This session only. Nothing lands on disk.

referencess3-tables-knowledge.md

≈1.8k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Amazon S3 Tables

This reference captures information addressing common gotchas and frequently asked questions for Amazon S3 Tables to support accurate model responses. It is not a complete specification. The authoritative source for current specifications, limits, quotas, and API behavior is the Amazon S3 User Guide, Amazon S3 Tables API Reference, Amazon S3 Tables feature page, and Amazon S3 FAQs. Retrieve current specifications, limits, and quotas from those pages before citing specifics; cite figures only from those pages.

1. Overview

What it is: Amazon S3 Tables delivers fully managed Apache Iceberg tables in purpose-built table buckets, with S3 running compaction, snapshot management, and unreferenced-file removal automatically. It reduces operational overhead and can deliver higher transactions per second and better query throughput than self-managing Iceberg on general purpose buckets, plus table-native features, like defining tables as resources with Amazon Resource Names (ARNs), Tables replication, and S3 Intelligent-Tiering for tabular datasets. Tables are exposed through the Iceberg REST Catalog API, so any Iceberg-compatible engine (Amazon Athena, Amazon Redshift, Amazon EMR, AWS Glue ETL, Apache Spark, and others) can read and write to S3 Tables.

Well-suited for: new Iceberg analytics projects, data lake tables and structured analytics data, ETL pipeline outputs, streaming into tables for SQL analysis, and migrating open table format data outside of S3 or self-managed Iceberg on S3.

2. Service Information

You MUST retrieve information from the linked documentation in the below table before answering any user question on the related topic.

Topic Example service characteristics, features, and actions Documentation
Access and protocols Iceberg REST Catalog API; concurrent writers; Apache Iceberg supported versions Accessing table data
Iceberg support Apache Iceberg table format and spec versions, including Apache Iceberg v3 Working with Apache Iceberg V3 tables
Deployment and availability supported Regions; table buckets; per-Region quotas Getting started with S3 Tables, S3 Tables AWS Regions, endpoints, and service quotas
Data protection and management automatic maintenance; no manual object overwrite or delete; MaximumSnapshotAge and MinimumSnapshots; cross-Region and cross-account replication; noncurrent-version retention S3 Tables maintenance; Replicating S3 tables
Performance Auto; Binpack; Sort; Z-order compaction S3 Tables maintenance
Security s3tables namespace; table-bucket, namespace, and table access control; Block Public Access; SSE-S3 and SSE-KMS; maintenance-principal key permissions; condition keys; VPC endpoints Security for S3 Tables
Health and monitoring CloudWatch metrics; alarms; CloudTrail Logging and monitoring for S3 Tables
Pricing table storage; per-object monitoring; API requests; automated compaction; cross-Region replication; Intelligent-Tiering (not exhaustive, review pricing page for the full list of pricing dimensions) Amazon S3 pricing, Cost optimization for tables with Intelligent-Tiering

Related services and integrations

You MUST retrieve information from the linked documentation in the below table before answering any user question on the related service.

Example services Example characteristics and common workloads Documentation
Amazon Athena, Amazon Redshift, Amazon EMR, AWS Glue ETL, Apache Spark, and other Iceberg-compatible engines query and process S3 Tables, with AWS Glue Data Catalog integration for AWS analytics services, or access tables directly using the Amazon S3 Tables Iceberg REST endpoint or the Amazon S3 Tables Catalog for Apache Iceberg Accessing table data, Integrating with AWS analytics services
AWS Glue Data Catalog catalog federation; IAM authentication Integrating with Amazon S3 Tables
AWS Lake Formation optional fine-grained access control (IAM is the default access model) Creating an S3 Tables catalog in Lake Formation

3. Troubleshooting

You MUST retrieve information from the linked documentation in the below table before providing the user with any guidance on the related area.

Example area Example errors Example fixes Documentation
Access and permissions AccessDenied despite broad S3 permissions; IAM vs Lake Formation confusion grant s3tables actions specifically Security for S3 Tables, Integrating with Amazon S3 Tables, Integrating Amazon S3 Tables with AWS analytics services
Capacity and scaling quota reached; throttling during ingestion request a quota increase through Support; back off and spread writes S3 Tables AWS Regions, endpoints, and service quotas
Data protection and recovery replicas reject writes; deleted noncurrent objects unrecoverable write to the source; enable noncurrent-version retention Replicating S3 tables
Maintenance table name rejected; Sort or Z-order not applied; manual overwrite blocked define a sort order; rely on automatic maintenance Maintenance for tables, Naming rules

Source: SKILL.md on GitHub

No alerts1mo3 checks · Risk SAFE
  • Gen Agent Trust Hub1mo

    This skill provides domain expertise for AWS storage services, offering architectural and operational guidance. It emphasizes security best practices, such as encryption and least-privileged access, and relies on official AWS documentation and repositories. No malicious patterns were detected.

  • Socket1mo

    No alerts

  • Snyk1mo

    Risk: LOW · No issues

Signed by skilld at 4666f4e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated last month
metadata
{
  "version": "1"
}

README badge

README badge for aws/agent-toolkit-for-aws/aws-storage