Do you know what the world’s broadly adopted cloud platform is? It is nothing but Amazon Web Services (AWS) that has purpose-built functionalities to offer reliable, scalable, and cost-effective cloud computing solutions. In this article, we are going to all about What is Amazon S3?.
In this Amazon S3 tutorial, We have given an in-depth analysis for the below concepts:
Amazon S3 is a web service that is used to store and retrieve unlimited data anywhere over the internet. It is similar to Google Drive and is probably the best storage option under AWS. It is mostly used for-
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The need for storage is increasing day by day. To fulfill that need Amazon offers a total of five main storage option; they are:
Amazon S3 has two basic entities called Object and Bucket, where objects are stored inside buckets. By default, one can create 100 buckets per account. In case of more bucket demands, one can submit the request to increase the limit. Bucket names should be globally unique irrespective of the region. Every bucket has its data and descriptive metadata.
Let’s have a look at the basic concepts of Amazon S3.
Amazon S3 offers an object storage service where each object is stored as a file name With a given ID number and metadata. Unlike file and block cloud storage, Amazon S3 allows a developer to access an object via a REST API.
There are two types of metadata in S3 - System Defined and User Defined. The system defined is used for maintaining things such as creation date, size, last modified, etc. whereas the user-defined system is used to assign key values to the data that the user uploads. Key-value helps users to organize objects and allow easy retrieval. S3 allows users to upload, store and download files having sizes up to five terabytes.
Write, read, and delete unlimited objects containing from 1 byte to 5 terabytes of data.
S3 in Amazon provides high availability and durability solutions by replicating the data of one bucket in multiple data centers. As told earlier, the Amazon S3 bucket never leaves its positions until a user moves it or deletes it. Consistency is an important part of data storage; it ensures that every change committed to a system should be visible to all the participants. S3 has two types of consistency models-
1) Read-after-write consistency: It enables the visibility of a newly created object to all clients without any delays. Similarly, there are read-after-delete and read-after-update. In read-after-update, the user can edit or make changes to an already existing object whereas read-after-delete guarantees that reading a deleted file or object will fail for all clients.
2) Eventual consistency: there is a time lag between the changes made in the data to the point where all participants can see it. It might not be visible immediately, but eventually, it appears.
Standard storage class is a default storage class in S3 that stores the user’s data across multiple devices. It provides 99.99% availability and 99.999999999% durability. It can save the loss of two facilities concurrently and provide low latency and high throughput performance.
This class is used when data is not accessed frequently but demands rapid access when needed. It is also designed to sustain the loss of two facilities concurrently and provide low latency and high throughput performance.
This storage class is used by the user when data is accessed less frequently, but when it requires fast access when needed. It cost 20% less than the standard IA storage class because it stores data in a single availability zone, unlike all other storage classes. It is cost-effective storage and a good choice for storing backup data.
It is the cheapest storage class in Amazon S3 where you can store immense data at a lower rate as compared to other storage classes but can be used for archive only. Let us see what the three types of models offered by S3 Glacier are
Every user has to pay a monthly monitoring and automation fee for storing objects in the S3 buckets. The rate charged for that depends on the object's size, storage class, and duration of storage. Proper object lifecycle management and configuration are very necessary if you want to get a cost-effective deal. With lifecycle configuration rules, users can tell Amazon S3 to place data in a less expensive storage class, or archive or delete them permanently. Let us find out when one should use a lifecycle configuration.
If a user uploads periodic logs to a bucket, the application might require that data for a week or a month. After that, a user might want to delete them.
Some data is accessed frequently for a specific period of time. After that, they are rarely needed. At that point, the user would like to archive it for some particular time and then delete it permanently. Amazon S3 provides a set of API operations to manage lifecycle configuration on a bucket. Check out the operations below-
Object Versioning is one of the most salient features of Amazon S3 and is used to keep multiple versions of data at the same time in the bucket. It is used to avoid accidental or unplanned overwrite and deletion of data. Object versioning is not a defaulted feature, but the user has to enable it.
Once it is enabled, a user cannot delete any object directly. All versions of the data reside in the bucket, and a delete marker is introduced in the bucket which becomes the current version. Now, to delete the object, the user needs to remove that delete marker also. Note that existing objects in your bucket are not affected by this operation; only future requests behavior will change.
A user cannot afford to lose his/her data stored on the cloud. S3 is enriched with great features, and one of them is default encryption. Protecting data while in transition mode (as it travels to or from Amazon S3) or stored on disks in Amazon S3, a user needs to set default encryption on a bucket. There are two ways in which you can encrypt the data - client-side encryption and server-side encryption.
In client-side encryption, a user encrypts the data using the KMS (key management service) and then transfers it to the S3. In this case, S3 cannot see the raw data. In server-side encryption, the user transfers the data to S3 where it is encrypted. When the user retrieves data, AWS decrypts the data and sends the raw data back.
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STEP-1: Create an S3 Bucket
A bucket can be created using AWS Command Line Interface or logging into the AWS Management Console. By default, 100 buckets can be created but can be extended with a request. Go to the Amazon S3 console and click "Create bucket". Follow the bucket naming rule to give the globally unique name to the bucket and click and "create". Also, choose the configure option and set permission as per your need.
STEP-2: Configure Options
Here, you will be given various configure options that you can select to enable a particular set of features on a bucket such as
STEP- 3: Set Permissions
By default, permission is private, which can be changed through AWS Management Console Permission or bucket policy. While granting permissions to read, write and delete, be selective and avoid keeping buckets open to the public.
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Amazon S3 Transfer acceleration promotes fast and secure data transfer from client to S3 bucket. You may need to use this for various possible reasons such as-
If you are facing such needs, you should definitely start using Amazon S3 transfer acceleration. Let us find out how can you enable this feature and make the most out of it. Enable transfer acceleration on a bucket by
After enabling it, you can transfer the data from the bucket through the names of the S3 accelerate endpoint domain.
It is the best and cost-effective cloud storage platform that handles the fluctuating storage demands of the user. It is enriched with amazing features and offers data durability along with scalability, availability, and industry-leading performance.
Its encryption feature ensures data protection from unauthorized access. It is the only object storage service that gives a block option to public access at the bucket or at the account level. AWS also has various auditing capabilities to handle and maintain access requests for S3 resources.
AWS gives you several options to store and move your data to a lower-cost storage class as per access patterns. Preferring this platform will help save costs without sacrificing the performance of operation done on data as per the requirement.
With Amazon S3, you can easily manage access, cost, and data protection. AWS lambda helps you to log activities, automate workflows without any additional infrastructure. Use this cloud storage platform to manage data operations with specific permissions for your application.
Analyze data stored in AWS data warehouse and S3 resources through standard SQL expressions. Also, improve query performance by retrieving the needed set of data instead of the entire object. Do use this data storage platform to manage your data properly and perform effective operations on data.
Amazon S3 is one of the most popular services available under AWS. It offers scalability, high performance, and data security to cloud-based businesses. You can store immeasurable data using Amazon S3 and can access it anywhere, anytime.
Hope you loved reading What is Amazon S3 article and found it informative.
Still, If you have any query? Do let us know in the comment section.
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