Forem: Gauthier Kwatatshey

kube prometheus stack with grafana

Gauthier Kwatatshey — Thu, 23 Jan 2025 13:17:21 +0000

Build a CRUD Serverless API from scratch using AWS Lambda (Python), API Gateway, and DynamoDB.

Gauthier Kwatatshey — Tue, 22 Aug 2023 00:28:07 +0000

1. Introduction

AWS Lambda is a serverless compute solution that allows you to run code without the need for server provisioning or management. You only pay for the compute time you use. This indicates that my own project, which will not receive a lot of traffic, is a great choice for AWS Lambda. This use case is ideal for applications with variable traffic or that can scale to zero.

2. Prerequisites
IAM Role/IAM User with the enough permissions.
AWS CLI installed
Python3
AWS CLI
GIT

3. AWS Resources

You'll need the AWS resources listed below.

AWS IAM Role
AWS Lambda
AWS API Gateway
AWS DynamoDB

4. Architecture

You can create the resources manually using the AWS Console, or you can leverage this using any IAC options like Terraform, AWS SAM/CloudFormation. In this Article you will use the AWS Console to things easier

5. Deployment Steps

Step -1 - Create a role (name it as you wish and add permissions)

Step -2 - Create a lambda function (name it as you wish, chose the latest python version as runtime)

Python codes can be found here:

git clone https://github.com/Assassin010/CRUD-Serverless-API-Python-G.git

git clone https://Assassin10@bitbucket.org/assassin10/crud-serverless-api-python-b.git

git clone https://gitlab.com/Assassin010/CRUD-Serverless-API-Python-L.git

Step -3 - Build the REST API

Create 3 resources
health with path /health
product path /product
products path /products

Step -4

Create Methods for each resources

On health resource, create "GET" method
On product resource, create "GET", "POST", "PATCH" and
"DELETE"
On products resource, create "GET"

check all boxes as followed for all Methods on each resource and chose your created lambda (Step -2)

Step -5 Deploy the API

Step -6 Create DynamoDB Table

6. TEST ALL APIs

POST: For a single product

{ "productId": "bag", "color": "black", "price": "100", "quantity": "1500" }

GET: For a single product

PATCH: For a single product

DELETE: For a single product

GET multiple products:

Notes: You will need POST few products before trying to GET all of them.

7. References

https://aws.amazon.com/lambda/
https://aws.amazon.com/api-gateway/
https://aws.amazon.com/dynamodb/
https://aws.amazon.com/cloudwatch/
https://boto3.amazonaws.com/v1/documentation/api/latest/index.html

Happy coding!
END - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

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Gauthier Kwatatshey__
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SpringBoot Serverless REST API - ApiGateway+Lambda, deployed using AWS SAM

Gauthier Kwatatshey — Fri, 11 Aug 2023 17:04:50 +0000

1. Introduction

Let's discuss the benefits of using AWS Lambda and Spring Boot 3 before we begin. You're probably accustomed to packaging your programmes as JAR files and distributing them to servers. You might even deploy the application to Kubernetes in a containerised form using Docker.

Scalability, security, and patching are all important considerations when managing your own server. You must take into account the volume of traffic your application will experience when you deploy it to a server. You might need to scale up to accommodate the traffic if your server is running at 100 percent of its capacity

If your server is only being used 10% utilization, you might consider scaling down to save money.

Most people are familiar with this concept when it comes to deploying functions as a service (FaaS), however in this article we will deploy a whole Spring Boot REST API. According to the AWS Pricing Page, the free tier of AWS Lambda includes one million free requests per month and 400,000 GB-seconds of computing time each month. This means that for the majority of the side projects I'm working on, I can deploy them to AWS Lambda for free.

2. Prerequisites

Read the Quick Start here: https://github.com/awslabs/aws-serverless-java-container/wiki/Quick-start---Spring-Boot3
Thanks to Mark Sailes for all of his help with this tuto
Java 17
Spring Boot 3.1
AWS CLI
AWS SAM CLI
GIT

You clone my repository because I have everything ready for you.

git clone https://github.com/Assassin010/SpringBoot-Serverless-Api-G.git

git clone https://Assassin10@bitbucket.org/assassin10/springboot-serverless-api-b.git

git clone https://gitlab.com/Assassin010/springboot-serverless-api-l.git

3. Agenda

In this article, you will build a new Spring Boot 3 application, as well as a CRUD REST API, which you will package and deploy to AWS Lambda.

start.spring.io
spring boot 3.1.0
maven / java
web, webflux
Build CRUD REST API
post package
Post Record
PostNotFoundException
PostController
Blog Posts Loader
JsonPlaceholderService
Test locally using http client before packaging for production

4. Maven Model

The Maven Archetype is a project template that you can use to create new projects. The AWS Serverless Spring Boot 3 Archetype is a Maven project that you can use to create a new Spring Boot 3 project that includes an AWS Serverless container for Spring Boot 3. This will also create the exact Maven configuration needed. needed to create an AWS Lambda deployment package. If you are using IntelliJ IDEA, you can use the Maven Archetype to generate a new project but you can also use Spring Initializr. aws-serverless-springboot3-archetype

If Maven is already installed, you can use the following command to create a new project:

mvn archetype:generate -DgroupId=my.service -DartifactId=my-service -Dversion=1.0-SNAPSHOT \
       -DarchetypeGroupId=com.amazonaws.serverless.archetypes \
       -DarchetypeArtifactId=aws-serverless-springboot3-archetype \
       -DarchetypeVersion=2.0.0-M1

5. AWS Resources

To deploy your application to AWS Lambda, you must first create the AWS resources listed below.

AWS Lambda
API Gateway

You can create the resources manually using the AWS Console, or you can use code. In this Article you will use the AWS Console, but I have included some resources if you want to learn more about SAM and CDK.

AWS SAM

SAM stands for Serverless Application Model. It's an open-source framework for creating serverless applications on AWS. It simplifies the definition of AWS resources (infrastructure as code) required to run your application. It also includes a command line interface (CLI) for packaging and deploying your application to AWS.

SAM defines your application using a template file (template.yaml). The AWS resources required to run your application are defined in the template file. You should go over that template file and review it before deploying your application.

mvn clean package sam deploy --guided
https://aws.amazon.com/serverless/sam/

AWS CDK

CDK stands for Cloud Development Kit
AWS CDK is an open source software development framework that allows you to define the resources of your cloud application using familiar programming languages. Because the AWS CDK allows you to define your infrastructure in standard programming languages, you can write automated unit tests for your infrastructure code in the same way that you do for your application code.

Manual steps

run this command to generate zip file mvn clean package

If you want to use SAM CLI, I created for you a template called template.yaml.

What you require is to run the following commands:

mvn clean package

sam build

sam deploy --guided

5. References

https://aws.amazon.com/lambda/
https://aws.amazon.com/api-gateway/
https://aws.amazon.com/serverless/sam/
https://aws.amazon.com/cloudformation/
https://aws.amazon.com/s3/
https://spring.io/projects/spring-boot
https://start.spring.io

Happy coding!
END - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

If you like my work and want to support me…
The BEST way is following me on dev.to here

Feel free to give likes, or writing comments so I know how helpful this post was for you.

Gauthier Kwatatshey__
Connect with me on LinkdIn

Medium

How to cut down the Costs of Running AWS servers (Elastic Compute)

Gauthier Kwatatshey — Sun, 04 Jun 2023 11:18:44 +0000

Let's save some money by optimizing the use of any applications hosted in ec2

1. Introduction

It is painful to start and stop instances manually on a daily basis. Let's create Lambda functions leavraging python boto3 with the CloudWatch rule and event (EventBridge) which automatically starts and stops servers based on the predefined time in EventBridge rule

2. Resources

2.1. AWS LamBda Function

AWS Lambda is a serverless, event-driven computing solution that allows you to run code for almost any form of application or backend service without the need for server provisioning or management.

You may call Lambda from more than 200 AWS services and software-as-a-service (SaaS) applications, and you only pay for what you use.

When you deploy your code to AWS Lambda, an executable package is created that is executed whenever the Lambda function is called.

In our scenario, we will import the Boto3 Library to activate the Step Function.

2.2. Elastic Compute (EC2)

Amazon Elastic Compute Cloud (EC2) is a cloud computing platform provided by Amazon.com that allows users to rent virtual computers on which to run their own computer applications.

EC2 promotes scalable application deployment by providing a web service through which a user can boot an Amazon Machine Image (AMI) to configure a virtual machine, referred to as a "instance" by Amazon, containing any software desired.

The term "elastic" refers to the ability of a user to build, launch, and terminate server instances as needed, paying by the second for active servers. EC2 gives users flexibility over the geographical location of instances, allowing them to optimize latency and achieve high levels of redundancy.

2.3. Amazon EventBridge

Amazon EventBridge is a serverless, fully managed, and scalable event bus that allows you to integrate AWS services, SaaS, and your applications.

EventBridge was previously known as Amazon CloudWatch Events. The core service and API for Amazon CloudWatch Events and EventBridge are the same; however, EventBridge has many more features.

2.3. Additional resources

2.3.1. CloudTrail

Your new AWS account comes with CloudTrail enabled by default. An event on CloudTrail is created whenever something happens in your AWS account. Within the CloudTrail console, by selecting Event history, you may quickly view recent occurrences. Create a trail or an event data store to keep a running log of all activity and events in your AWS account.

2.3.2. DynamoDB

Terraform state locking using DynamoDB

2.3.3. S3

Amazon S3 store the state as a specified key in a specified bucket (Bakend store terraform remote state). The dynamodb_table parameter can be set to the name of an existing DynamoDB table to enable state locking and consistency checking using Dynamo DB, which is another feature supported by this backend. Multiple remote state files can be locked using a single DynamoDB database. The values of the bucket and important variables are included in the key names that Terraform creates.

3. Implementation

AWS Lambda Functions, AWS EventBridge, Python boto3 . Using this method, You can schedule the start and stop of your EC2 instances by using tags on target instances.

The following are some advantages of utilizing scheduler on EC2:

Access the instance as per the working hours.
Reduce costs.
Stop instance from loading up on weekends.
The time limit for employees for working on the instance.

4. Architecture

5. Logic of the Python Code

Returning All EC2 instances(InstanceID) tagged with the tag Auto-Start-Stop will be started each working day from Monday to Friday at 8:00 am UTC Which is 9:00 and will stopped each working day from Monday to Friday evening at 6:00 pm UTC

6. File Structure

.
├── README.md
├── backend.tf
├── cloudtrail.tf
├── dynamodb.tf
├── eventbridge.tf
├── iam.tf
├── images
│   └── Auto-Start-Stop-Architecture.drawio.png
├── lambda.tf
├── lambda_start
│   ├── lambda_handler.zip
│   └── src
│   └── main_lambda.py
├── lambda_stop
│   ├── lambda_handler_1.zip
│   └── src
│   └── main_lambda_1.py
├── providers.tf
├── tags.tf
├── terraform.tfstate
├── terraform.tfstate.backup
├── terraform.tfvars
└── variables.tf

6 directories, 18 files

6.1. Lambda Python preview

7. Adjustment

Since the solution is deployed using Terraform, the schedule time adjustment should also be carried out using Terraform. However, you can also adjust the schedule time directly on the AWS console, however this is not really advised. To avoid any inconsistency or and duplicate resources, it is recommended that Terraform be used to apply the changes.

8. Remediation

Simply remove the tag "Auto-Start-Stop" from the target EC2 instances manually.

9. Deployment pre-requisites

Terraform CLI installed
IAM Role/IAM User with the enough permissions.
AWS CLI installed
Git Installed

10. Deployment Steps

git clone https://github.com/Assassin010/auto-start-stop-instances.git

git clone git@github.com:Assassin010/auto-start-stop-instances.git

Switch to the following directory => auto-start-stop

terraform init

terraform plan

terraform apply --auto-approve

To completely decommission the solution

terraform destroy --auto-approve

11. Summary

So far, we've seen the utility of Event-Driven infrastructure, how services respond to events, and a use case in which a serverless compute service runs based on storage events and notifies a user via email. In addition, we used Infrastructure as a Code (IaaC) by using terragrunt + terraform to create and destroy all resources.

12. References

https://aws.amazon.com/ec2/
https://aws.amazon.com/lambda/
https://www.terraform.io
https://aws.amazon.com/cloudtrail/
https://aws.amazon.com/s3/
https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-what-is.html

Happy coding!
END - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

If you like my work and want to support me…
The BEST way is following me on dev.to here

Feel free to give likes, or writing comments so I know how helpful this post was for you.

Gauthier Kwatatshey__
Connect with me on LinkdIn

Medium