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This is the repo of the Weather app from my YouTube video

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weather-app

This is the repo of the Weather app from my YouTube video

Project structure

In this project you build a end-to-end pipeline from requesting weather data from an API to visualizing the results on a Dashboard. As tools we use the weather api, Docker, AWS Elastic container registry, AWS Lambda, AWS EventBridge and Grafana as the dashboard solution. Here's an overview of the pipeline: Project setup image

What to do in the right order

  • Create account on weatherapi.com and generate a token
  • Clone repository to local and replace the token
  • Setup the TDengine cloud database on tdengine.com
  • Create the weather database, stable and tables berlin and sanfrancisco
  • Install TDengine connector for python with pip install taospy
  • Run the code in your VSCode or other dev env and check TDengine if the data is there
  • Build the docker container docker build -f dockerfile-user -t weather-data .
  • If not done already install the AWS cli (see helpful links below)
  • Create a development user and role in IAM with full rights to ecr, create keys for that user
  • Do a aws configure and enter key and secret key
  • Create ECR, tag the image and push the image up to ECR (find the commands in ECR, top right corner)
  • Create Lambda that uses the image
  • Create EventBridge schedule that triggers the Lambda function
  • Pull the Grafana image from docker hub docker pull grafana/grafana
  • Start grafana with docker run --name=grafana -p 3000:3000 grafana/grafana
  • Go to localhost:3000 to access Grafana, connect the TDengine datasource and create yourself a Dashboard

Helpful links

More about TDengine

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This is the repo of the Weather app from my YouTube video

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