The RDS interfaces are a way to access the RDS service we create. After the creation and configuration of the RDS service there is a need of accessing the data, uploading data to this database and running some other program which should be able to connect to the database. Such requirements of accessing and manipulating data by end users of the database and not necessarily the AWS account holder which created the database needs these interfaces.

There are three main such interfaces.

GUI Console

This is the simplest of the interfaces where the user can login through a web browser and start using the DB services. The down side of such access is , it needs a human to interact with the RDS services and we cannot run a database program to do some regular tasks like – backup or analysing the DB etc.

Command Line Interface

It is also called CLI access where you can execute DB command through the AWS command prompt screen which should have been installed in the client computer you are using. Below are the steps to install CLI in your local system using which you will access AWS services.

The steps to install AWS CLI are as below.

Step-1

Check for the version of python in your environment.

ubuntu@ubuntu:~$ python -V
ubuntu@ubuntu:~$ python3 -V

When we run the above program, we get the following output −

Python 2.7.12
Python 3.5.2

If the version is less than 2.6 or 3.3 , then you need to upgrade the version of python in your system.

Step -2

Check for availability of the python package named pip . It will be needed to install AWS CLI.

Pip -V

When we run the above program, we get the following output −

pip 10.0.1 from /home/ubuntu/.local/lib/python3.5/site-packages/pip (python 3.5)

Step -3

Issue the following command to install the AWS CLI.

pip install awscli –upgrade –user
aws --version

When we run the above program, we get the following output −

Aws-cli/1.11.84 Python/3.6.2 Linux/4.4.0

Step-4

Next we configure the aws CLI with credentials. We issue this command and then input the required values one by one.

aws configure

When we run the above program, we get the following output −

AWS Access Key ID [None]: ****PLE
AWS Secret Access Key [None]: ********8
Default region name [None]: us-west-2
Default output format [None]: json

With the above configuration in place you are now ready to use CLI for communicating with AWS environments for setting up and using amazon RDS. In the next chapters we will see how we can do that.

AWS API

Amazon Relational Database Service (Amazon RDS) also provides an application programming interface (API). APIs are used when the information is exchanged between the systems rather than a human issuing the commands and receiving the result. For example, if you want to automate the addition of database instances to a RDS service when the number of transactions reach certain threshold , then you use a AWS SDK to write a program which will monitor the number of database transactions and spin-off a RDS instance when the required condition is met.

Below is an example of API code that creates a copy of a DB snapshot. It is a python program which uses AWS sdk named boto3. The client library in boto3 has a method named copy_db_snapshot which is called by the python program to create a copy of the DB snapshot with the required parameters as shown.

import boto3

client = boto3.client(''rds'')

response = client.copy_db_snapshot(
    SourceDBSnapshotIdentifier=''mydbsnapshot'',
    TargetDBSnapshotIdentifier=''mydbsnapshot-copy'',
)

print(response)

When the above program is run we get the response which describes the various properties of the copy event. Here the term string represents the various names of parameters which is defined by the user for their environment. For example VpcID represents the ID of the vpc in which the copy action is happening.

{
    ''DBSnapshot'': {
        ''DBSnapshotIdentifier'': ''string'',
        ''DBInstanceIdentifier'': ''string'',
        ''SnapshotCreateTime'': datetime(2015, 1, 1),
        ''Engine'': ''string'',
        ''AllocatedStorage'': 123,
        ''Status'': ''string'',
        ''Port'': 123,
        ''AvailabilityZone'': ''string'',
        ''VpcId'': ''string'',
        ''InstanceCreateTime'': datetime(2015, 1, 1),
        ''MasterUsername'': ''string'',
        ''EngineVersion'': ''string'',
        ''LicenseModel'': ''string'',
        ''SnapshotType'': ''string'',
        ''Iops'': 123,
        ''OptionGroupName'': ''string'',
        ''PercentProgress'': 123,
        ''SourceRegion'': ''string'',
        ''SourceDBSnapshotIdentifier'': ''string'',
        ''StorageType'': ''string'',
        ''TdeCredentialArn'': ''string'',
        ''Encrypted'': True|False,
        ''KmsKeyId'': ''string'',
        ''DBSnapshotArn'': ''string'',
        ''Timezone'': ''string'',
        ''IAMDatabaseAuthenticationEnabled'': True|False,
        ''ProcessorFeatures'': [
            {
                ''Name'': ''string'',
                ''Value'': ''string''
            },
        ]
    }
}

As RDS is a managed service provided by AWS, we can expect that like other AWS services it will provide scalability, security and cost effectiveness to the various RDBMS it provides. The database products available through AWS RDS are as listed below.

• MySQL – Support versions for MySQL 5.5 to 5.7. Minor upgrades happen automatically without needing any involvement from the user.

• MariaDB – Support versions for MariaDB from 10.0 to 10.2.

• Oracle – Supports version 11g and 12c. You can use the oracle license provided by aws or bring your own license. The costing for these two are different.

• Microsoft SQL Server – Supports version 200t to 2017. Also AWS supports the various editions like – Enterprise, Standard, Web and Express.

• PostgreSQL – Supports version 9 to 11. Can be configured as a multi A-Z deployment with read replicas.

• Amazon Aurora – This is Amazon’s own RDBMS. We will be covering it in a separate tutorial.

Each of these Database software is offered as Software as a Service (saas) by providing following features.

• Customization of CPU capacity, Memory allocation and IOPS(Input Output per second) for a database instance.

• Manage software patching, failure and recovery of the RDBMS software without any user intervention.

• Allow manual or automated backup of the database using snapshots. Restore the database from these snapshots.

• Provide high availability by creating a primary and secondary instance which are synchronous. In case of a failure of primary AWS RDS automatically fails over to secondary.

• Put the databases in a virtual private cloud (VPC) and aslo use AWS IAM (Identity and Access management) service to control access to the databases.

• There are two purchase options for AWS RDS service. On-Demand Instances and Reserved Instances. For on-Demand instance you pay for every hour of usage while for Reserved instance you make a upfront payment for one year to three period time frame.

For using any Aws service you ned to set up an AWS account. We assume you have set up the AWS account by following the guide lines mentioned in the aws home page. Below are the preliminary steps to access the RDS services from the console.

Step-1

After logging in to the amazon console, to access the RDS services we need to navigate to the Amazon RDS home page by searching for RDS in the search box of under the services tag as shown in the diagram below.

Step-2

On clicking the link above we get the Amazon RDS home page. If it is the first time ever you are accessing RDS services, then it will show you a screen prompting for creating a database as shown below.

In case you have already created some RDS resources a summary of that will be available by scrolling down in the above page. A screen shot is shown below.

Step-3

The next screen gives us an option to select the DB engine we need and that is the start of our configuration steps for the database we need.

In the next chapter we will see the details on each of the industry’s popular database configuration and usage one by one.