AWS Simple Storage Service

Amazon’s Simple Storage Service (S3) is one of the more commonly used AWS services for storage purposes. The primary purpose of S3 is for object storage with the necessary flexibility to scale, availability across regions, and security while maintaining performance. Each S3 object gets a unique ID key and can be accessed over web requests. Anything stored in an S3 bucket will be safely retained for as long as a service needs it to be.
Above all else, S3 is advertised for its resilience and its stability with a very minimal chance of failure or data loss. S3 buckets can easily and quickly to whatever needs to be stored, and contents are kept safe from errors, corruption, and threats. S3’s storage class analysis interprets data access patterns and arranges tags accordingly for long-term data retention, visibility options, maintenance, workflows, and alerts. The integrated access management and encryption tools keep stored data safe from unauthorized access and meet various security standards. Even at high levels of performance, S3 is incredibly cost-effective for what it does.
Application
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- Big Data: One of S3’s base features is the generation of data lakes to dump large quantities of data into to be organized in bulk through the use of machine learning and analytics. Working with AWS Lake Formation, data is defined along with implementing governance and security policies.
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- Backup and Disaster Recovery: Especially when combined with some of AWS’ other services, constructing a robust restoration plan with S3 is easy. S3’s Cross-Region Replication helps to replicate data across numerous regions in a network to rapidly recover in the event of failures and outages whether manmade or natural.
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- Methodical Archiving: S3’s Glacier and Glacier Deep Dive solutions enable resilient archiving capabilities and gradually tune out physical storage. While lowering energy use, S3 has the capability for long-term storage of data that will see less frequent use. When a certain piece of data is then required for use, it can be brought back out of cold storage in minutes.
Amazon’s Simple Storage Service (S3) is one of the more commonly used AWS services for storage purposes. The primary purpose of S3 is for object storage with the necessary flexibility to scale, availability across regions, and security while maintaining performance. Each object gets a unique ID key and can be accessed over web requests. Anything stored in an S3 bucket will be safely retained for as long as a service needs it to be.
Above all else, S3 is advertised for its resilience and its stability with a very minimal chance of failure or data loss. Scaling easily and quickly to whatever needs to be stored, contents are kept safe from errors, corruption, and threats. S3’s storage class analysis interprets data access patterns and arranges tags accordingly for long-term data retention, visibility options, maintenance, workflows, and alerts. The integrated access management and encryption tools keep stored data safe from unauthorized access and meet various security standards. Even at high levels of performance, S3 is incredibly cost-effective for what it does.
Applicability
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- Big Data: One of S3’s base features is the generation of data lakes to dump large quantities of data into to be organized in bulk through the use of machine learning and analytics. Working with AWS Lake Formation, data is defined along with implementing governance and security policies.
- Backup and Disaster Recovery: Especially when combined with some of AWS’ other services, constructing a robust restoration plan with S3 is easy. S3’s Cross-Region Replication helps to replicate data across numerous regions in a network to rapidly recover in the event of failures and outages whether manmade or natural.
- Methodical Archiving: S3’s Glacier and Glacier Deep Dive solutions enable resilient archiving capabilities and gradually tune out physical storage. While lowering energy use, S3 has the capability for long-term storage of data that will see less frequent use. When a certain piece of data is then required for use, it can be brought back out of cold storage in minutes.
Amazon Elastic File System

Amazon’s Elastic File System (EFS) is directly tailored to handling high volume for long periods of time while still retaining the ability to scale automatically. With high throughput, EFS can easily match the necessary throughput to match sudden file growth and either add or remove files without interrupting the flow of work. EFS instances can be mounted onto any other service and be accessed by any virtual machine or EC2 instances that are in regions far off relative to where the EFS is located.
EFS also works well with AWS Lambda functions. Data can be easily shared from function to function, read large files, and write output back out to EFS. EFS instances are also self-managed, minimizing the need to repair and maintain. Security is also incredibly robust and can be managed through other services such as AWS Identity Access Management and AWS Virtual Private Cloud. Even without external services, files are kept encrypted by default.
Application
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- Easy to move: EFS can move entire applications surprisingly quickly and easily without needing to compromise architecture.
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- Big Data: EFS has tolerance for high node throughput and can provide low-latency file access. If the application requires the use of big data, EFS can support it. This works especially well for blogs and archives.
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- App development and tests: EFS makes it easy to move blocks of code between developers or share files across multiple computational resources.
Amazon’s Elastic File System (EFS) is directly tailored to handling high volume for long periods of time while still retaining the ability to scale automatically. With high throughput, EFS can easily match the necessary throughput to match sudden file growth and either add or remove files without interrupting the flow of work. EFS instances can be mounted onto any other service and be accessed by any virtual machine or EC2 instances that are in regions far off relative to where the EFS is located.
EFS also works well with AWS Lambda functions. Data can be easily shared from function to function, read large files, and write output back out to EFS. EFS instances are also self-managed, minimizing the need to repair and maintain. Security is also incredibly robust and can be managed through other services such as AWS Identity Access Management and AWS Virtual Private Cloud. Even without external services, files are kept encrypted by default.
Application
-
- Easy to move: EFS can move entire applications surprisingly quickly and easily without needing to compromise architecture.
- Big Data: EFS has tolerance for high node throughput and can provide low-latency file access. If the application requires the use of big data, EFS can support it. This works especially well for blogs and archives.
- App development and tests: EFS makes it easy to move blocks of code between developers or share files across multiple computational resources.
Amazon Elastic Block Store

Elastic Block Store (EBS) is specifically designed for virtual machines, placing chunks of data into blocks as the name implies. Additionally, it’s more balanced around having a better throughput and performance. With EBS-tailored SSDs, the I/O is reliable and scalable. The blocks are provisioned and then attached to an EC2 instance in the same way a physical disk drive would be to a physical machine, helping to increase overall throughput. The ease with which EBS instances can be duplicated and snapshots can be placed in multiple regions, makes EBS widely applicable to migrations, recovery, and expansion. Easy backups make data replication easy to manage in the case of data loss.
Application
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- Testing: Making duplicates of EBS blocks helps in making instances that can be experimented with without worrying about expending any crucial data.
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- Database Types: Depending on the need for either low latency, consistent performance, or various storage needs, there are plenty of databases that are compatible with ESB. Databases available for EBS include NoSQL, Microsoft SQL Server, PostgreSQL, and Oracle.
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- Multi-geographical Presence: Having multiple EBS blocks means being able to run multiple instances in several regions. This will require regular backups to all active blocks across each region.
Elastic Block Store (EBS) is specifically designed for virtual machines, placing chunks of data into blocks as the name implies. Additionally, it’s more balanced around having a better throughput and performance. With EBS-tailored SSDs, the I/O is reliable and scalable. The blocks are provisioned and then attached to an EC2 instance in the same way a physical disk drive would be to a physical machine, helping to increase overall throughput. The ease with which EBS instances can be duplicated and snapshots can be placed in multiple regions, makes EBS widely applicable to migrations, recovery, and expansion. Easy backups make data replication easy to manage in the case of data loss.
Application
-
- Testing: Making duplicates of EBS blocks helps in making instances that can be experimented with without worrying about expending any crucial data.
- Database Types: Depending on the need for either low latency, consistent performance, or various storage needs, there are plenty of databases that are compatible with ESB. Databases available for EBS include NoSQL, Microsoft SQL Server, PostgreSQL, and Oracle.
- Multi-geographical Presence: Having multiple EBS blocks means being able to run multiple instances in several regions. This will require regular backups to all active blocks across each region.