AWS Storage Types
Understanding the Different Options for Storing Your Data on Amazon Web Services
When it comes to storing data in the cloud, Amazon Web Services (AWS) offers a range of options to suit the different needs of businesses and organizations. AWS storage types can be divided into four main categories: block storage, object storage, file storage, and archive storage. In this article, we’ll take a closer look at each of these storage types and the benefits they offer.
Block storage, also known as block-level storage, is the most common type of storage used for traditional storage arrays. Block storage is typically used for applications that require fast, low-latency access to data, such as databases and virtual machines (VMs). AWS provides two options for block storage: Elastic Block Store (EBS) and Instance Store.
Elastic Block Store (EBS) is a network-attached storage (NAS) solution that provides raw block-level storage to Amazon Elastic Compute Cloud (EC2) instances. EBS volumes can be used as a primary storage device for data that requires frequent and fast access, such as a database. EBS provides a variety of options for backup and recovery, including snapshots, which are point-in-time copies of an EBS volume that can be used to restore data in the event of a failure.
Instance Store, on the other hand, is a local storage option that is directly attached to an EC2 instance. Instance Store is ideal for temporary storage of data that is generated and processed by an application, but that does not need to be persisted beyond the lifespan of the instance.
Object storage is a type of data storage that is designed for scalable and flexible data storage, typically for unstructured data such as images, videos, and documents. AWS’s object storage solution is Amazon Simple Storage Service (S3).
S3 provides unlimited storage capacity and is designed to be highly available and scalable, with automatic failover to ensure that data is always accessible. S3 provides several options for managing access to objects, including versioning, lifecycle policies, and access controls, making it a good choice for organizations that need to store large amounts of data.
File storage, also known as file-level storage, is a type of data storage that is designed for file-based data, such as documents, spreadsheets, and multimedia files. AWS’s file storage solution is Amazon Elastic File System (EFS).
EFS is a scalable and highly available file system that is designed to be used with EC2 instances. EFS provides a standard file system interface and supports a wide range of operating systems, making it easy to use with existing applications. EFS also provides options for data backup and recovery, including snapshots, which can be used to recover data in the event of a failure.
Archive storage is a type of data storage that is designed for infrequently accessed data that needs to be retained for long periods of time. AWS’s archive storage solution is Amazon Glacier.
Amazon Glacier is a low-cost, long-term storage solution that provides secure and durable storage for data that is infrequently accessed. Glacier provides several options for data retrieval, including expedited retrieval, standard retrieval, and bulk retrieval, making it a good choice for organizations that need to store large amounts of data for compliance or regulatory reasons.
Demonstration of AWS S3
Here is a demonstration of the AWS S3 in action:
Amazon Simple Storage Service (S3):
To demonstrate the use of S3, we’ll create an S3 bucket and upload an object to it.
Step 1: Log in to the AWS Management Console and navigate to the S3 dashboard.
Step 2: Create a new S3 bucket by clicking the “Create Bucket” button.
Step 3: Give the bucket a name and choose the desired region.
Step 4: Upload an object to the bucket by clicking the “Upload” button.
Step 5: Verify that the object has been successfully uploaded by navigating to the S3 bucket and checking the contents.
Amazon Web Services (AWS) provides several different types of storage options to meet different needs, and each type of storage has its own set of problems and solutions.
Here are some common problems and solutions for S3AWS storage types:
Problem: Slow read performance
Solution: Use Amazon S3 Transfer Acceleration to speed up read performance by routing traffic through optimized AWS edge locations.
Here’s an example of how to enable Amazon S3 Transfer Acceleration:
- Open the AWS Management Console and navigate to the Amazon S3 service.
- Choose the bucket you want to enable Transfer Acceleration for.
- Choose the “Properties” tab, and then choose “Transfer Acceleration”.
- Choose “Enable Transfer Acceleration”, and then choose “Save”.
This will enable Transfer Acceleration for the selected bucket, and incoming data will be routed through an optimized network path to AWS edge locations, providing faster transfer speeds.
You can also use the AWS CLI to enable Transfer Acceleration.
Here’s an example command:
aws s3api put-bucket-accelerate-configuration — bucket my-bucket — accelerate-configuration Status=Enabled
This command will enable Transfer Acceleration for the “my-bucket” bucket.
By using Amazon S3 Transfer Acceleration, you can improve read performance and provide faster data transfer for your applications and users, especially for remote or international users.
Problem: High costs
Solution: Use Amazon S3 lifecycle policies to automatically transition data to lower-cost storage classes or delete it when it is no longer needed.
Here’s an example of how to set up an Amazon S3 lifecycle policy to transition objects to lower-cost storage classes:
- Open the Amazon S3 console and select the bucket you want to apply the lifecycle policy to.
- Click on the “Management” tab and then click on “Lifecycle” in the left-hand menu.
- Click on the “Create rule” button.
- Enter a name for the rule, and then select the prefix of the objects you want to apply the rule to. Under “Transitions”, select the object’s current storage class, and then select the target storage class that you want to transition the object to.
- Set the number of days after which the transition should take place, and click “Create rule”.
Once you have set up the lifecycle policy, Amazon S3 will automatically transition objects to the lower-cost storage class based on the criteria you have specified.
You can also use Amazon S3 lifecycle policies to delete objects that are no longer needed, which can help reduce costs even further. To do this, you can add a “Expiration” rule to your lifecycle policy and specify the number of days after which objects should be deleted.
About the Author:
Ramvasanth Mahendran is a Software Development Engineer with 2 years of experience, focused on delivering clean, error-free code for scalable, user friendly designs.
About KBX Digital:
At KBX Digital we use server-less technology to auto scale micro-services to serve millions of customers.