AWS : S3 (Simple Storage Service)

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What's S3?

Amazon Simple Storage Service is storage for the Internet. It is designed to make web-scale computing easier for developers.

Image source : Getting Started with Amazon Simple Storage Service

Amazon S3 has a simple web services interface that we can use to store and retrieve any amount of data, at any time, from anywhere on the web. It gives any developer access to the same highly scalable, reliable, fast, inexpensive data storage infrastructure that Amazon uses to run its own global network of web sites. The service aims to maximize benefits of scale and to pass those benefits on to developers.

-What Is Amazon S3?

S3 stores arbitrary objects (computer files) up to 5 terabytes in size, each accompanied by up to 2 kilobytes of metadata. Objects are organized into buckets (each owned by an Amazon Web Services account), and identified within each bucket by a unique, user-assigned key. Amazon Machine Images (AMIs) which are used in the Elastic Compute Cloud (EC2) can be exported to S3 as bundles. - wiki

S3 concepts

Buckets:
A bucket is a container for objects stored in Amazon S3. Every object is contained in a bucket. For example, if the object named mypet/puppy.jpg is stored in the bogo bucket, then it is addressable using the URL http://bogo.s3.amazonaws.com/mypet/puppy.jpg
Buckets serve several purposes:
1. they organize the Amazon S3 namespace at the highest level
2. they identify the account responsible for storage and data transfer charges
3. they play a role in access control
4. they serve as the unit of aggregation for usage reporting
We can configure buckets so that they are created in a specific region. We can also configure a bucket so that every time an object is added to it, Amazon S3 generates a unique version ID and assigns it to the object.
Objects:
Objects are the fundamental entities stored in Amazon S3. Objects consist of object data and metadata. The data portion is opaque to Amazon S3. The metadata is a set of name-value pairs that describe the object. These include some default metadata, such as the date last modified, and standard HTTP metadata, such as Content-Type. We can also specify custom metadata at the time the object is stored.
An object is uniquely identified within a bucket by a key (name) and a version ID.
Keys:
A key is the unique identifier for an object within a bucket. Every object in a bucket has exactly one key. Because the combination of a bucket, key, and version ID uniquely identify each object, Amazon S3 can be thought of as a basic data map between bucket + key + version and the object itself. Every object in Amazon S3 can be uniquely addressed through the combination of the web service endpoint, bucket name, key, and optionally, a version. For example, in the URL http://doc.s3.amazonaws.com/2015-01-01/AmazonS3.wsdl, "doc" is the name of the bucket and "2015-01-01/AmazonS3.wsdl" is the key.
Regions:
We can choose the geographical region where Amazon S3 will store the buckets we create. We might choose a region to optimize latency, minimize costs, or address regulatory requirements. Objects stored in a region never leave the region unless you explicitly transfer them to another region. For example, objects stored in the EU (Ireland) region never leave it.
Amazon S3 Data Consistency Model:
Updates to a single key are atomic. For example, if we PUT to an existing key, a subsequent read might return the old data or the updated data, but it will never write corrupted or partial data.
Amazon S3 achieves high availability by replicating data across multiple servers within Amazon's data centers. If a PUT request is successful, our data is safely stored. However, information about the changes must replicate across Amazon S3, which can take some time, and so you might observe the following behaviors:
1. A process writes a new object to Amazon S3 and immediately attempts to read it. Until the change is fully propagated, Amazon S3 might report "key does not exist."
2. A process writes a new object to Amazon S3 and immediately lists keys within its bucket. Until the change is fully propagated, the object might not appear in the list.
3. A process replaces an existing object and immediately attempts to read it. Until the change is fully propagated, Amazon S3 might return the prior data.
4. A process deletes an existing object and immediately attempts to read it. Until the deletion is fully propagated, Amazon S3 might return the deleted data.
5. A process deletes an existing object and immediately lists keys within its bucket. Until the deletion is fully propagated, Amazon S3 might list the deleted object.
The US Standard region provides eventual consistency for all requests. All other regions provide read-after-write consistency for PUTS of new objects and eventual consistency for overwrite PUTS and DELETES.