AWS cloud practitioner notes - Storage and databases
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This module describes the AWS services for storage and databases. AWS has different services that go from file storage services to serverless databases.
Previous: AWS cloud practitioner notes - Networking
Module 5 - Instance stores and Amazon Elastic Block Store
Block storage levels are places to store files, EC2 has different types of storage as well.
- instance store volumes (physical attached to AWS host) - temporary type [1]
- EBS are virtual hard drives or EBS volumes - persistent type
Incremental snapshots (backup) can be taken from EBS volumes and restored later.
Module 5 - Amazon Simple Storage Service (Amazon S3)
Amazon S3 is a storage service that allows you to store and retrieve files at any scale and pay only for what you use.
- Store data as an object
- Storage objects in buckets
- Upload maximum object size of 5TB
- Version objects
- Create multiple buckets
S3 classes (or tiers)
- S3 standard 99,99999999999% of durability
- S3 standard infrequent access (backups, disaster recovery files)
- S3 One Zone-Infrequent access (S3 one Zone-IA)
- S3 intelligent-Tiering (unknown or changing access patterns)
- AWS Glacier to archive data (Able to retrieve objects in minutes)
- AWS Glacier deep archive (Able to retrieve objects within 12 hours)
It is possible to move objects between tiers through S3 lifecycle management. For example, from s3 standard to s3 infrequent access.
Comparing Amazon EBS and Amazon S3
EBS | S3 |
---|---|
up to 16TB | Unlimited storage |
Survive EC2 termination | Individual objects up to 5 TB |
Solid state by default | Write once/read many |
HDD options | 99,99999999999% durability |
Use case 1 - App to upload a photo file
S3 is the preferred approach here, for the following reasons:
- Web-enabled
- Regionally distributed
- Offers cost savings
- Serverless
Use case 2 - Video editing on a file
Object storage treats every file as a complete discrete object, perfect for files that are consumed as a whole.
Block storage breaks the files into smaller pieces (blocks), for a bunch of small changes, EBS is preferable. In short:
- Complete changes = S3
- Complex read, write, change functions = EBS
Module 5 - Amazon Elastic File System (EFS)
Multiple instances can access the data in EFS at the same time, it scales up and down as needed. The differences between EBS and EFS are:
EBS | EFS |
---|---|
Amazon EBS are attached to EC2 instances | Multiple instances reading and writing simultaneously |
Availability zone level resource | True file system/multiple availability zones |
Need to be in the same availability zone to the attached EC2 instance | Regional resource |
EBS volumes do not automatically scales | Automatically scales up and down |
Module 5 - Amazon Relational Database Service (RDS)
- Automated patching
- Backups
- Redundancy
- Failover
- Disaster recovery
Amazon Aurora
- MySQL or PostgreSQL support
- 1/10th cost of commercial databases
- Data replication
- Up to 15 read replicas
- Automated backup to S3
Module 5 - Amazon DynamoDB
DynamoDB is serverless in the sense that you don’t have to provision, install, maintain or operate the server that the database is in. DynamoDB scales automatically to adjust the changes in the database.
- Non-relational database
- Millisecond response time
- Fully managed
- Highly scalable
Comparing Amazon RDS and DynamoDB
RDS | DynamoDB |
---|---|
Automatic high availability | Key-value |
Customer ownership of data | Massive throughput capabilities |
Customer ownership of schema | PB size potential |
Customer control of network | Granular API access |
Use case 1 - sales supply chain application
RDS is the choice as its application is built for analytics and requires complex relationships between the data.
Use case 2 - Employee contact list application
Single table territory, is potentially relational, but not required as the relationship between data would create an overhead in maintaining the relationships.
Module 5 - Amazon Redshift
Amazon Redshift is a data warehouse service used for analytics. You can collect data from many sources and see the relationships across the data.
Module 5 - Amazon Database Migration Service (AWS DMS)
Amazon Database Migration Service helps you to migrate databases into AWS.
Homogenous databases
The first type of migration is: homogenous. Homogenous databases are migrations across the same database type. For example:
- MySQL to Amazon RDS for MySQL
- Microsoft SQL Server to Amazon RDS for SQL Server
- Oracle to Amazon RDS for Oracle
Heterogeneous databases
The second type of migration is heterogeneous databases. Which provides a migration for different database vendors. For this type of migration, there are two steps, the first is the conversion from the database source into the origin database. Then the last step is to migrate.
Module 5 - Additional database services
- Amazon DocumentDB - document database that supports MongoDB
- Amazon Neptune - Graph database service
- Amazon Quantum Ledger Database - Review a complete history of all the changes that have been made to your application data
- Amazon Managed Blockchain - A service used to create managed blockchain networks
- Amazon ElastiCache - A service that adds a caching layer to improve application response time
- Amazon DynamoDB accelerator - In-memory cache for DynamoDB
Resources
Up next
References
- [1]AWS, “Amazon EC2 instance store,” 2021 [Online]. Available at: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html. [Accessed: 07-Jan-2021]
Table of contents
- Introduction
- Module 5 - Instance stores and Amazon Elastic Block Store
- Module 5 - Amazon Simple Storae Service (Amazon S3)
- Module 5 - Amazon Elastic File System (EFS)
- Module 5 - Amazon Relational Database Service (RDS)
- Module 5 - Amazon DynamoDB
- Module 5 - Amazon Redshift
- Module 5 - Amazon Database Migration Service (AWS DMS)
- Module 5 - Additional database services
- Up next
- Reference
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