New Training: Managing Amazon Timestream Databases with Python and Boto3
In this 6-video skill, CBT Nuggets trainer Trevor Sullivan explores how to use Python and the Boto3 module to interact with Timestream! Watch this new DevOps training.
Learn DevOps with one of these courses:
AWS Cloud Automation
This training includes:
1.4 hours of training
You’ll learn these topics in this skill:
Introduction to Amazon Timestream and Python Boto3
Configure Python Development Tools for Amazon Timestream
Create Amazon Timestream Database and Tables with Python
Ingest Data into Amazon Timestream with Telegraf Agent
Visualize Data from Amazon Timestream in Grafana
Write Custom Data Into Amazon Timestream with Python
How To Create A TimeStream Database With Python
IoT is becoming big in the enterprise world. It makes sense. IoT devices are revolutionizing industries like manufacturing. IoT devices are being utilized for operations like just-in-time maintenance services to help increase the uptime of machinery while reducing operational costs. These devices collect a lot of data, though, so businesses turn to services like Amazon's TimeStream for collecting and storing that information.
Because much of the IT environment in industries like manufacturing are becoming more automated, developers are turning to scripting languages, like Python, to perform certain tasks. Thankfully, Python can be fully integrated with the AWS SDK for working with services like TimeStream.
Getting started with the AWS SDK within Python is as easy as installing the Boto3 library. The Boto3 library was created to integrate the AWS SDK directly into Python. Use Python's Pip package manager to install it.
Once Boto3 is installed, instantiate a new object in Python with it. Then configure an AMI policy with TimeStream privileges with that object. From there, developers can use that object to work directly with TimeStream to create, manage, and delete TimeStream resources.
For example, creating a new database in TimeStream with Boto3 is easy. Use the create_database function with the instantiated AWS object. That function takes a data array for configuration that adds information such as the database name, the key ID, and tags.
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