Building Modern Python Applications on AWS - week one

This is week one course notes of Building Modern Python Applications on AWS on Coursera.

AWS APIs

Everything in AWS is an API call and every AWS Service has it’s own set of APIs that you interact with. When you send HTTP requests to AWS, you sign the requests so that AWS can identify who sent them. You sign requests with your AWS access key, which consists of an access key ID and secret access key. You need to sign HTTP requests only when you manually create them. When you use the AWS Command Line Interface (AWS CLI) or one of the AWS SDKs to send requests to AWS, these tools automatically sign the requests for you with the access key that you specify when you configure the tools. When you use these tools, you don’t need to learn how to sign requests yourself.

To read about how requests need to be signed click here: https://docs.aws.amazon.com/general/latest/gr/signing_aws_api_requests.html

AWS Command Line Interface

The AWS Command Line Interface (AWS CLI) is an open source tool that enables you to interact with AWS services using commands in your command-line shell.

Installation of the AWS Command Line Interface is fairly straightforward, and if you’re using Amazon EC2 instances or AWS Cloud9, the tools are already installed for you.

After configuration, the AWS CLI enables you to start running commands that implement functionality equivalent to that provided by the browser-based AWS Management Console from the command prompt in your favorite terminal program:

Linux shells – Use common shell programs such as bash, zsh, and tcsh to run commands in Linux or macOS.
Windows command line – On Windows, run commands at the Windows command prompt or in PowerShell.
Remotely – Run commands on Amazon Elastic Compute Cloud (Amazon EC2) instances through a remote terminal program such as PuTTY or SSH, or with AWS Systems Manager.

Read information about the AWS CLI at: https://aws.amazon.com/cli/

Read information about installing the AWS CLI at: https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-install.html

Read information about configuring the AWS CLI at: https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.html

AWS Cloud9

AWS Cloud9 operates as a cloud-based IDE, and has a wide variety of functionality already built in to help you with the development of and collaboration of your projects. A particular area where Cloud9 can assist is when working with the AWS Command Line Interface. Because the CLI tools are already installed in your environment, all you need to do is configure them to get started.

You access the AWS Cloud9 IDE through a web browser. You can configure the IDE to your preferences. You can switch color themes, bind shortcut keys, enable programming language-specific syntax coloring and code formatting, and more.

AWS Cloud9 managed temporary credentials have permission restrictions on their own which may restrict some API calls you are using. You can find the list of those restrictions at:

https://docs.aws.amazon.com/cloud9/latest/user-guide/how-cloud9-with-iam.html#sec-auth-and-access-control-temporary-managed-credentials

AWS Credentials and Programmatic Access

Read about best practices with AWS Credentials here: https://docs.aws.amazon.com/general/latest/gr/aws-access-keys-best-practices.html

Read about creating your first IAM admin user and user grouphttps://docs.aws.amazon.com/IAM/latest/UserGuide/getting-started_create-admin-group.html

Cloud9 Managed Credentials

Throughout this course we will be calling AWS APIs from programs or commands running in Cloud9 Instances. It is recommended that you do not hard code your AWS credentials into your code for any reason, and you should rely on IAM Role Based Access as much as possible. To read more about Role Based Access in AWS please click here: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles.html

In Cloud9, by default, Roles are not being used for permissions, instead Cloud9 uses managed credentials. To read more about Cloud9 Managed Credentials click here:

https://docs.aws.amazon.com/cloud9/latest/user-guide/how-cloud9-with-iam.html#sec-auth-and-access-control-temporary-managed-credentials

AWS SDK for Python

To install the AWS SDK for Python please read the following instructions: https://aws.amazon.com/sdk-for-python/

What is Boto3?

Boto3 is the AWS SDK for Python. It enables Python developers to create, configure, and manage AWS services, such as EC2 and S3. Boto3 provides an easy to use, object-oriented API through the resource, as well as low-level access to AWS services through the client.

Please ensure you get familiar with the boto3 documentation to get a better idea of how the SDK works, and what API calls can be made using the SDK.

Boto3 Documentation: https://boto3.amazonaws.com/v1/documentation/api/latest/index.html

Client: Clients provide a low-level interface to AWS whose methods map close to 1:1 with service APIs. All service operations are supported by clients. Clients are generated from a JSON service definition file.

Resource: Resources represent an object-oriented interface to AWS. They provide a higher-level abstraction than the raw, low-level calls made by service clients.

Session: A session manages state about a particular configuration. By default, a session is created for you when needed. However, it’s possible and recommended that in some scenarios you maintain your own session. Sessions typically store the following:

Credentials
AWS Region
Other configurations related to your profile

Credentials: Boto3 credentials can be configured in multiple ways. Regardless of the source or sources that you choose, you must have both AWS credentials and an AWS Region set in order to make requests.

If you want to learn more about how boto3 got its name and how it came to be, read this blog post: https://aws.amazon.com/blogs/aws/now-available-aws-sdk-for-python-3-boto3/)

The AWS Systems Manager Parameter Store API will be used throughout the course demos.

Parameter Store is a service that provides secure, hierarchical storage for configuration data management and secrets management. You can store data such as passwords, database strings, Amazon Machine Image (AMI) IDs, and license codes as parameter values.

Below you can find information about the two AWS APIs we used in the demo code in the Boto3 Documentation:

Parameter Store Boto3 Documentation: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/ssm.html
S3 Select Boto3 Documentation: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html

AWS Toolkit and AWS Serverless Application Model

The AWS Toolkit for PyCharm is an open source plug-in for the PyCharm IDE that makes it easier to create, debug, and deploy Python applications on Amazon Web Services. With the AWS Toolkit for PyCharm, you can get started faster and be more productive when building applications with PyCharm on AWS. The toolkit provides an integrated experience for developing serverless applications, including assistance for getting started, step-through debugging, and deploying from the IDE.

The AWS Toolkit uses the AWS Serverless Application Model (AWS SAM) to create and manage AWS resources like AWS Lambda Functions.

AWS SAM is an open-source framework that you can use to build serverless applications on AWS.

The AWS Serverless Application Model provides a great way to codify your distributed application build, providing many of the benefits you find directly with Amazon CloudFormation.

A serverless application is a combination of Lambda functions, event sources, and other resources that work together to perform tasks. Note that a serverless application is more than just a Lambda function—it can include additional resources such as APIs, databases, and more.

You can use AWS SAM to define your serverless applications in a declarative way. AWS SAM consists of the following components:

AWS SAM template specification. You use this specification to define your serverless application. It provides you with a simple and clean syntax to describe the functions, APIs, permissions, configurations, and events that make up a serverless application. You use an AWS SAM template file to operate on a single, deployable, versioned entity that’s your serverless application.
AWS SAM command line interface (AWS SAM CLI). You use this tool to build serverless applications that are defined by AWS SAM templates. The CLI provides commands that enable you to verify that AWS SAM template files are written according to the specification, invoke Lambda functions locally, step-through debug Lambda functions, package and deploy serverless applications to the AWS Cloud, and so on.

For more information on AWS SAM read here: https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/what-is-sam.html

For more information on the AWS ToolKit for PyCharm read here: https://docs.aws.amazon.com/toolkit-for-jetbrains/latest/userguide/welcome.html

For information on installing Docker read here: https://docs.docker.com/get-docker/

For information on installing SAM for Windows, Linux, Mac read here: https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-sam-cli-install.html