poor man cloud-native pastebin3

this project is about using AWS Free tier resources to host yourown pastebin

A pastebin or text storage site is a type of online content-hosting service where users can store plain text (e.g. source code snippets for code review via Internet Relay Chat (IRC))

swagger UI

swagger UI pastebin http endpoints

Authors

• @socraticDevBlog

Run Locally

install pipenv for your user only

pip install --user pipenv

binarylocation=$(python -m site --user-base)/bin
# retrieve pipenv binary location in order to add it to PATH (suggested: add it to your .bashrc file)

export PATH=$PATH:"$binarylocation"

1. running app

Clone the project

  git clone git@github.com:socraticDevBlog/pastebin.git

Go to the project directory

  cd pastebin

Install dependencies

pipenv install --deploy --dev

2. Start DynamoDB local instance

you want to start a local database (DynamoDB) install locally and provision it with a table named paste

 cd local

 docker compose up

got errors or want to start with a fresh database

remove running dynamodb container and start a fresh one

docker compose down -v

docker compose up

3. Run Lambda locally

Using SAM (Serverless Application Model) CLI, you can easily execute the lambda locally

We are using only one (1) lambda entrypoint to cover all http requests since our use case is pretty simple.

Lambda code is located at src/app.py

Stubbed lambda event input arguments are located at local/events/. There is one file per http verb.

simulate a POST request locally

pipenv run sam build && pipenv run sam local invoke -e local/events/post.json

# > Invoking app.lambda_handler (python3.9)
# Local image is up-to-date
# Using local image: public.ecr.aws/lambda/python:3.9-rapid-x86_64.

# Mounting /Users/me/git/pastebin/.aws-sam/build/PastebinFunction as /var/task:ro,delegated, inside runtime container
# START RequestId: 378e46ab-dd9b-4a31-bec7-1cc1b4a06ae8 Version: $LATEST
# END RequestId: 378e46ab-dd9b-4a31-bec7-1cc1b4a06ae8
# REPORT RequestId: 378e46ab-dd9b-4a31-bec7-1cc1b4a06ae8  Init Duration: 1.52 ms  Duration: 1021.66 ms    Billed Duration: 1022 ms        Memory Size: 128 MB     Max Memory Used: 128 MB

simulate a GET request locally

⚠️ make sure you have successfully inserted at least one(1) Paste in your local database. Make sure id value in local/events/get.json file reflects this inserted Paste's Id.

pipenv run sam build && pipenv run sam local invoke -e local/events/get.json

4. run API Gateway locally

sam CLI will detect the API Gateway and its available methods automatically (GET, POST, etc.)

developer will use Postman app or VS Code Thunder Client to issue http request toward localhost:3000/paste endpoint

pipenv run sam build && pipenv run sam local start-api

# Initializing the lambda functions containers.
# Local image is up-to-date
# Using local image: public.ecr.aws/lambda/python:3.9-rapid-x86_64.

# Mounting /Users/user/Documents/git/pastebin/.aws-sam/build/PastebinFunction as /var/task:ro,delegated, inside runtime container
# Containers Initialization is done.
# Mounting PastebinFunction at http://127.0.0.1:3000/paste [GET]
# You can now browse to the above endpoints to invoke your functions. You do not need to restart/reload SAM CLI while working on your functions, changes will be reflected instantly/automatically. If
# you used sam build before running local commands, you will need to re-run sam build for the changes to be picked up. You only need to restart SAM CLI if you update your AWS SAM template
# 2023-08-09 17:19:04 WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
#  * Running on http://127.0.0.1:3000
# 2023-08-09 17:19:04 Press CTRL+C to quit

Running Tests

To run tests, run the following command

pipenv run test

deploying

We chose Terraform to deploy this app to AWS

layers (installed python dependancies)

Python serverless functions often requires external dependencies as listed in Pipfile

In AWS Lambda, we will add those dependencies as a layer. Our Terraform code (see terraform/main.tf and analyse resource "null_resource" "lambda_layer" to understand how we compress project's dependencies installed on local machine by pipenv). There might be simpler ways to install Python dependencies to aws lambda, but as of now(2023-12-23) we don't know better.

Make sure to package your dependancies in a zip file to add it as a layer to our lambda -> https://spak.no/blog/article/63f47f130faeadeeeb968ae9

use your pastebin on the public internet

retrieve the endpoint URI

assuming you have successfully deployed the app on aws using terraform apply on your aws account

1. retrieve api gateway endpoint using terraform command terraform output from key api_gateway_endpoint. it should look like an long URL (ex.: https://abc1234.execute-api.ca-central-1.amasonaws.com)
2. perform POST request to insert a new paste

curl -i  -X POST -H "Content-Type: application/json" -d '{"content":"one two tree testing my new api gateway/lambda integration"}' https://exj5m66tib.execute-api.ca-central-1.amazonaws.com/paste

3. perform a GET query over previous paste

 curl -i https://exj5m66tib.execute-api.ca-central-1.amazonaws.com/paste?id=<previous POST request response value>

Roadmap

• implement a DynamoDB CRUD client

• safe-guard CI by automated unit tests suite (GitHub Action)

• implement CI 'better practices' automated safe-guards

• develop a lambda that will Create and Read pastes

• implement an API Gateway that exposes Lamba's functions via http endpoint

• deploy required infrastructure using Terraform in AWS

Tech Stack

dependencies management pipenv

database: aws DynamoDB

computing: aws Lambda, python, boto3

publicly available endpoint: aws API Gateway

CI/CD: GitHub, GitHub Actions, pyenv, pytest

local dev environment

• Docker
• DynamoDB local
• SAM (Lambda), awscli