Can this skill help reduce cloud storage costs?

Yes, by enforcing efficient listing patterns using prefixes and metadata caching, it reduces the number of expensive LIST and HEAD operations performed against your bucket.

How does it handle large file uploads?

It identifies when files exceed 100MB and recommends switching from standard put() operations to put_multipart() for better reliability and lower memory overhead.

Which cloud providers does this skill support?

It supports all providers compatible with the Rust object_store crate, primarily Amazon S3, Google Cloud Storage (GCS), and Microsoft Azure Blob Storage.

How does this skill handle S3 503 SlowDown errors?

The skill suggests specific RetryConfig patterns including max_retries and retry_timeout settings designed to handle S3 rate limiting and transient network failures.

Does it provide security advice for credentials?

Absolutely. It detects hardcoded credentials and suggests environment-based configuration or IAM role integration using the AmazonS3Builder::from_env() patterns.

Object Store Best Practices

Name: Object Store Best Practices
Author: EmilLindfors

byEmilLindfors

Cloud Infrastructure

Optimizes cloud storage operations in Rust using the object_store crate with robust retry logic, streaming, and efficient I/O patterns.

About

This skill acts as an expert consultant for developers using the Rust object_store crate to interact with AWS S3, Google Cloud Storage, and Azure Blob Storage. It proactively guides you through implementing high-performance and resilient data engineering patterns, covering critical areas such as automatic retry configurations for transient 503 errors, memory-efficient streaming for large datasets, multipart uploads, and atomic write patterns to ensure data integrity in production cloud environments.

Key Features

Enforces atomic writes via temporary file and rename patterns to protect data integrity
Optimizes object listing using prefix filtering to reduce API costs and latency
Configures robust retry logic for transient cloud storage failures and 503 SlowDown errors
0 GitHub stars
Implements memory-efficient streaming for large objects to prevent OOM issues
Automates multipart upload strategies for improved transfer reliability

Use Cases

Optimizing high-concurrency cloud storage access for Rust-based backend services
Migrating legacy local file-handling code to production-grade cloud storage implementations
Building resilient data pipelines that process petabyte-scale data in AWS S3 or Azure Blob Storage

About

Key Features

Enforces atomic writes via temporary file and rename patterns to protect data integrity
Optimizes object listing using prefix filtering to reduce API costs and latency
Configures robust retry logic for transient cloud storage failures and 503 SlowDown errors
0 GitHub stars
Implements memory-efficient streaming for large objects to prevent OOM issues
Automates multipart upload strategies for improved transfer reliability

Use Cases

Optimizing high-concurrency cloud storage access for Rust-based backend services
Migrating legacy local file-handling code to production-grade cloud storage implementations
Building resilient data pipelines that process petabyte-scale data in AWS S3 or Azure Blob Storage