Serverless API Deployment with AWS Lambda and API Gateway

This page summarizes the projects mentioned and recommended in the original post on dev.to

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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  • DummyJSON

    DummyJSON.com provides different types of REST Endpoints filled with JSON data which you can use in developing the frontend with your favorite framework and library without worrying about writing a backend.

  • import json import requests def lambda_handler(event, context): base_url = 'https://dummyjson.com/' product_id = '1' resp = requests.get(url=base_url+'products/'+product_id) if resp.status_code != 200: raise Exception('Failed to retrieve product: '+resp.text) return { 'statusCode': resp.status_code, 'body': resp.json() } Q. what this code does? 1.Imports the necessary modules (JSON and requests). 2.Defines a base URL and a product ID that will be used to construct the API URL. 3.Sends a GET request to the API using the requests library, passing in the full API URL. 4.Checks the response status code to make sure that the request was successful (status code 200). 5.If the response status code is not 200, raise an exception with an error message that includes the response text. 6.If the response status code is 200, return a dictionary containing the response status code and the parsed JSON response body. ●Test the function.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

    InfluxDB logo
NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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