What is S3?

S3 is a popular choice for a wide variety of use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics. Your interviewer will expect you to understand the core concepts of S3 and when to use it in a system design.

Storage Classes

S3 offers a range of storage classes designed for different use cases. Your interviewer will be impressed if you can discuss the trade-offs between them.

• S3 Standard: The default storage class. It's designed for frequently accessed data and provides low latency and high throughput.
• S3 Intelligent-Tiering: This storage class is designed for data with unknown or changing access patterns. It automatically moves your data to the most cost-effective access tier based on how frequently you access it.
• S3 Standard-Infrequent Access (S3 Standard-IA): This storage class is for data that is accessed less frequently, but requires rapid access when needed. It has a lower storage price than S3 Standard, but you are charged a per-GB retrieval fee.
• S3 Glacier: This is a low-cost storage class for data archiving. It's designed for data that is accessed infrequently and can tolerate retrieval times of several minutes to several hours.

Security and Access Control

S3 provides a variety of features for securing your data. Your interviewer will expect you to be able to discuss how you would secure the data in your S3 buckets.

• Encryption: S3 encrypts all new objects by default. You can choose to use server-side encryption with S3-managed keys (SSE-S3), server-side encryption with AWS Key Management Service (KMS) keys (SSE-KMS), or client-side encryption.
• Access Control Lists (ACLs): ACLs are a legacy access control mechanism that allows you to grant basic read/write permissions to other AWS accounts.
• Bucket Policies: Bucket policies are JSON-based policies that allow you to grant more fine-grained permissions to your S3 resources. You can use them to grant access to specific users, IP addresses, or VPC endpoints.
• Presigned URLs: You can generate a presigned URL for an object to grant temporary access to it. This is a common pattern for allowing users to upload or download files directly to/from S3 without having to give them AWS credentials.

How to Use S3 in a System Design Interview

When you're in a system design interview, you should be able to articulate why you would choose S3 over other storage solutions and how you would use it in your architecture.

Here are some key points to mention:

• Scalability: S3 is designed for massive scale. You can store a virtually unlimited amount of data in S3.
• Durability: S3 is highly durable. You can be confident that your data will not be lost.
• Integration with other AWS Services: S3 is tightly integrated with other AWS services. You can use it as a data source for services like Amazon EMR, Amazon Athena, and AWS Lambda.
• Static Website Hosting: You can use S3 to host a static website.
• Trade-offs: While S3 is a powerful tool, it's not a good choice for data that requires low-latency access or for data that needs to be updated frequently. For these use cases, a database like DynamoDB or a file system like Amazon EFS would be a better choice.

By discussing these points, you'll demonstrate to your interviewer that you have a solid understanding of S3 and how to use it to build scalable, durable, and secure systems.

Example System Design Problems

Here are a few examples of system design problems where you might use S3:

• Design Dropbox: S3 is the perfect choice for storing the files that users upload to Dropbox. Its durability and scalability are exactly what's needed for a file hosting service.
• Design Instagram: The photos and videos that users upload to Instagram would be stored in S3. The application servers would store the metadata about the media (e.g., the user who posted it, the caption), but the actual media files would be served from S3.
• Design YouTube: Similar to Instagram, the video files that users upload to YouTube would be stored in S3. The transcoding pipeline would read the original video from S3, create multiple versions of it, and then store those versions back in S3.