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Introduction to AWS Simple Storage Service (AWS S3)

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AWS offers a wide range of storage services that can be provisioned depending on your project requirements and use case. AWS storage services have different provisions for highly confidential data, frequently accessed data, and the not so frequently accessed data. You can choose from various storage types namely, object storage, file storage, block storage services, backups, and data migration options. All of which fall under the AWS Storage Services list. 

What is Amazon S3?

From the aforementioned list, S3 is the object storage service provided by AWS. It is probably the most commonly used, go-to storage service for AWS users given the features like extremely high availability, security, and simple connection to other AWS Services. AWS S3 can be used by people with all kinds of use cases like mobile/web applications, big data, machine learning, and many more.

How To Use an S3 Bucket?

You can use the Amazon S3 buckets by following the simple steps which are mentioned below. To know more how to configure about Amazon S3 refer to the Amazon S3 – Creating a S3 Bucket.

Step 1: Login into the Amazon account with your credentials and search form S3 and click on the S3. Now click on the option which is “Create bucket” and configure all the options which are shown while configuring.

Step 2: After configuring the AWS bucket now upload the objects into the buckets based upon your requirement. By using the AWS console or by using AWS CLI following is the command to upload the object into the AWS S3 bucket.

aws s3 cp <local-file-path> s3://<bucket-name>/

Step 3: You can control the permissions of the objects which was uploaded into the S3 buckets and also who can access the bucket. You can make the bucket public or private by default the S3 buckets will be in private mode.

Step 4: You can manage the S3 bucket lifecycle management by transitioning. Based upon the rules that you defined S3 bucket will be transitioning into different storage classes based on the age of the object which is uploaded into the S3 bucket.

Step 5: You need to turn to enable the services to monitor and analyze S3. You need to enable the S3 access logging to record who was requesting the objects which are in the S3 buckets.

Bucket Permission Options

You can manage the permission of S3 buckets by using several methods following are a few of them.

  1. Bucket Policies: Bucket policies can be attached directly to the S3 bucket and they are in JSON format which can perform the bucket level operations. With the help of bucket policies, you can grant permissions to the users who can access the objects present in the bucket. If you grant permissions to any user he can download, and upload the objects to the bucket. You can create the bucket policy by using Python.
  2. Access Control Lists (ACLs): ACLs are legacy access control mechanisms for S3 buckets instead of ACLs we are using the bucket policies to control the permissions of the S3 bucket. By using ACL you can grant the read, and access to the S3 bucket or you can make the objects public based on the requirements.
  3. IAM Policies: IAM policies are mostly used to manage the permissions to the users and groups and resources available in the AWS by using the IAM roles options. You can attach an IAM policy to an IAM entity (user, group, or role) granting them access to specific S3 buckets and operations.

The most effective way to control the permissions to the S3 buckets is by using bucket policies.

How Amazon S3 works?

Bucket

Data, in S3, is stored in containers called buckets. Each bucket will have its own set of policies and configurations. This enables users to have more control over their data. Bucket Names must be unique. Can be thought of as a parent folder of data. There is a limit of 100 buckets per AWS account. But it can be increased if requested by AWS support.

Objects

Fundamental entity type stored in AWS S3.You can store as many objects as you want to store. The maximum size of an AWS S3 bucket is 5TB. It consists of the following:

  1. Key.
  2. Version ID.
  3. Value.
  4. Metadata.
  5. Subresources.
  6. Access control information.
  7. Tags.

S3 Versioning

Versioning means always keeping a record of previously uploaded files in S3. Points to Versioning are not enabled by default. Once enabled, it is enabled for all objects in a bucket. Versioning keeps all the copies of your file, so, it adds cost for storing multiple copies of your data. For example, 10 copies of a file of size 1GB will have you charged for using 10GBs for S3 space. Versioning is helpful to prevent unintended overwrites and deletions. Objects with the same key can be stored in a bucket if versioning is enabled (since they have a unique version ID).

Bucket policy

A document for verifying the access to S3 buckets from within your AWS account, controls which services and users have what kind of access to your S3 bucket. Each bucket has its own Bucket Policies.

Access control lists (ACLs)

A document for verifying access to S3 buckets from outside your AWS account. An ACL is specific to each bucket. You can utilize S3 Object Ownership, an Amazon S3 bucket-level feature, to manage who owns the objects you upload to your bucket and to enable or disable ACLs.

Lifecycle Rules

This is a cost-saving practice that can move your files to AWS Glacier (The AWS Data Archive Service) or to some other S3 storage class for cheaper storage of old data or completely delete the data after the specified time.

Key

The key, in S3, is a unique identifier for an object in a bucket. For example in a bucket ‘ABC’ your GFG.java file is stored at javaPrograms/GFG.java then ‘javaPrograms/GFG.java’ is your object key for GFG.java.

Null Object

Version ID for objects in a bucket where versioning is suspended is null. Such objects may be referred to as null objects.

Features of Amazon S3

  • Durability: AWS claims Amazon S3 to have a 99.999999999% of durability (11 9’s). This means the possibility of losing your data stored on S3 is one in a billion.
  • Availability: AWS ensures that the up-time of AWS S3 is 99.99% for standard access.
    • Note that availability is related to being able to access data and durability is related to losing data altogether.
  • Server-Side-Encryption (SSE): AWS S3 supports three types of SSE models:
    • SSE-S3: AWS S3 manages encryption keys.
    • SSE-C: The customer manages encryption keys.
    •  SSE-KMS: The AWS Key Management Service (KMS) manages the encryption keys.
  • File Size support: AWS S3 can hold files of size ranging from 0 bytes to 5 terabytes. A 5TB limit on file size should not be a blocker for most of the applications in the world.
  • Infinite storage space: Theoretically AWS S3 is supposed to have infinite storage space. This makes S3 infinitely scalable for all kinds of use cases.
  • Pay as you use: The users are charged according to the S3 storage they hold.

What are the S3 Storage Classes?

AWS S3 provides multiple storage types that offer different performance and features and different cost structures. 

  • Standard: Suitable for frequently accessed data, that needs to be highly available and durable.
  • Standard Infrequent Access (Standard IA): This is a cheaper data-storage class and as the name suggests, this class is best suited for storing infrequently accessed data like log files or data archives. Note that there may be a per GB data retrieval fee associated with the Standard IA class.
  • Intelligent Tiering: This service class classifies your files automatically into frequently accessed and infrequently accessed and stores the infrequently accessed data in infrequent access storage to save costs. This is useful for unpredictable data access to an S3 bucket.
  • One Zone Infrequent Access (One Zone IA): All the files on your S3 have their copies stored in a minimum of 3 Availability Zones. One Zone IA stores this data in a single availability zone. It is only recommended to use this storage class for infrequently accessed, non-essential data. There may be a per GB cost for data retrieval.
  • Reduced Redundancy Storage (RRS): All the other S3 classes ensure the durability of 99.999999999%. RRS only ensures 99.99% durability. AWS no longer recommends RRS due to its less durability. However, it can be used to store non-essential data.

Advantages of S3 Bucket

  1. Scalability: Amazon S3 can be scalable horizontally which makes it handle a large amount of data. It can be scaled automatically without human intervention.
  2. High availability: S3 bucket is famous for its high availability nature you can access the data whenever you required it from any region. It offers a Service Level Agreement (SLA) guaranteeing 99.9% uptime.
  3. Data Lifecycle Management: You can manage the data which is stored in the S3 bucket by automating the transition and expiration of objects based on predefined rules. You can automatically move the data to the Standard-IA or Glacier, after a specified period.
  4. Integration with Other AWS Services: You can integrate the S3 bucket service with different services in the AWS like you can integrate with the AWS lambda function where the lambda will be triggered based upon the files or objects added to the S3 bucket.

Accessing Amazon S3

You can work with an AWS S3 bucket by using any one of the following methods

  1. AWS Management Console
  2. AWS Command Line Interface

AWS Management Console

You can access the AWS S3 bucket using the AWS management console which is a web-based user interface. You need to create an AWS account and login to the console and from there you can choose the S3 bucket option.

AWS Command Line Interface

You can configure the S3 bucker by using the AWS CLI by using scripts that can perform the AWS S3 tasks. to know more about How to Launch an EC2 instance using AWS CLI

FAQs On Amazon S3

Q.1: What is the use of an AWS S3 bucket?

To store large amount ofdata can access the data when ever you required.

Q.2: What are the buckets in S3?

Buckets are refered to the containrs where you can store your file and retrieve when ever you required.


Last Updated : 26 Jul, 2023
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