In this approach you create a separate bucket for each user. In this approach, you put all of your users' data into a single bucket in InfluxDB and you use a different tag for each user to enable fast querying. Depending on the scale of your application and other needs, there are 3 general approaches to consider. You will generally want to only display to each user the data that they wrote into the application. Most likely, your application will have many users. This section is fairly conceptual, so you can feel free to skip it. Overview Data segmentation strategiesīefore we start off bootstrapping the development environment, here is a bit of food for thought regarding if and how to segment your user data. If you want to see the completed project, that is in the demo-done branch.If you want to see just the starting point, that is in the demo-start branch.The code for this tutorial is available on GitHub. How to use the many powerful visualization libraries for the different platforms.
User authorization for your own web app.Creating your device and sending data from it.This tutorial is meant to focus on InfluxDB, not IoT applications in general, so I will not be focused on things like: How to use InfluxDB Cloud's powerful "Checks and Notifications" system to help you provide custom alerting to your users.How to install a downsampling task in InfluxDB that will both save you money in storage costs as well as optimize the user experience for your users.
How to bootstrap your development environment to get developing on InfluxDB Cloud.I happen to be using Python and Flask for this tutorial, but all of the concepts should apply equally to any language or web development framework. This tutorial is written very much with the application developer in mind. (In Part 4, Barbara Nelson provides a sequel to this article in which she shows how to use the UI, not the CLI, for the same functionality.) Objectives (building on InfluxDB Cloud) If you want some background, you can check out Part 1, where I design the basics of the device and teach it to communicate and add some notifications, and Part 2, where I start some downsampling and a dashboard. This app will allow users to visualize and create alerts from their uploaded Plant Buddy device data in a custom user experience. Now I am taking that concept a step further and writing the app for. This project entailed soldering some sensors to an Arduino, and teaching that device how to communicate directly with InfluxDB Cloud so that I could monitor those plants. Last year I started an IoT project, Plant Buddy. InfluxDB, Community, InfluxDB Cloud, Developer, Tutorial Building an IoT App with InfluxDB Cloud, Python and Flask (Part 3)
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