Amazon Web Services (AWS) – Simple Storage Service (S3)
The low down on S3
The What –
Amazon Web Services (AWS) S3, or Simple Storage Service, is a scalable object storage service provided by Amazon Web Services. It is designed to store and retrieve data from anywhere on the web. AWS S3 is widely used by developers, startups, enterprises, and other customers to store data for various use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics.
The Why –
AWS S3 can be beneficial across different use cases, including web application hosting, backup and restore strategies, data archiving, and many more. Here are some reasons why you might choose to use AWS S3:
1. Scalability
2. Durability and Availability
High Durability: S3 provides 99.999999999% (11 9’s) durability over a given year, ensuring that your data is reliably stored.
High Availability: It also provides 99.99% availability, ensuring that your data is accessible when you need it.
3. Security
Access Control: You can control who can access your data using AWS Identity and Access Management (IAM) policies, bucket policies, and Access Control Lists (ACLs).
Data Protection: S3 offers features like versioning to protect against unintended deletes or overwrites and also provides various encryption options for data at rest and in transit.
4. Cost-Effective
Pay-as-you-go: With S3, you pay only for the storage you use, without any minimum commitments or upfront fees.
Optimized Costs: Various storage classes, like S3 Intelligent-Tiering and S3 Glacier, allow you to optimize costs based on access patterns and retrieval times.
5. Data Management
Lifecycle Management: Automate moving your objects between different storage classes and archive objects with S3 Lifecycle policies.
Storage Class Analysis: Understand and visualize your storage usage to optimize costs using S3 Storage Class Analysis.
6. Integration with AWS Services
7. Global Reach
Global Infrastructure: AWS has a vast global infrastructure, allowing you to store data near your end users and ensuring low-latency access.
8. Compliance and Audit
9. Developer Friendly
SDKs and APIs: AWS provides Software Development Kits (SDKs) in various programming languages and a RESTful API to interact with S3, making it developer-friendly.
The When –
Example Use Cases (not an exhaustive list)
Content Distribution: Easily distribute content to end users using S3 with Amazon CloudFront.
Data Lakes: Build data lakes for big data analytics.
Backup and Restore: Implement backup and restore solutions.
Data Archiving: Archive data for compliance or other purposes using cost-effective storage classes.
Machine Learning: Store and retrieve large datasets for machine learning.
Big Data Analytics: Use S3 as a foundational component for big data analytics applications.
Example Reference Architectures –
Reduce archive cost with serverless data archiving1
Figure 1. Serverless data archiving and retrieval
Improving medical imaging workflows with AWS HealthImaging and SageMaker2
Figure 1: X-ray images are sent to AWS HealthImaging, and an Amazon SageMaker endpoint extracts insights.
https://aws.amazon.com/blogs/architecture/reduce-archive-cost-with-serverless-data-archiving/ ↩
https://aws.amazon.com/blogs/architecture/improving-medical-imaging-workflows-with-aws-healthimaging-and-sagemaker/ ↩
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