Announcing New Custom Analysis Features for AWS IoT Analytics with Custom Container Execution for Continuous Analysis
You can now containerize your custom analysis code, automate its execution on a set schedule, and analyze only the incremental data you need when you need it.
You can now containerize your custom analysis code, automate its execution on a set schedule, and analyze only the incremental data you need when you need it.
With AWS IoT Analytics, you can now bring your own containers built with custom authored code, built using third-party tools, such as in Matlab, Octave, R, Python, etc., or IoT Analytics Jupyter Notebooks, and execute them on your schedule to generate operational insights. Once those containers are built, you can automate execution to run on the recurring schedule that best meets the need of your business. If you are using Jupyter Notebooks, simply create an executable container image of your Jupyter Notebook code with just a click of a button and schedule its execution on AWS IoT Analytics.
AWS IoT Analytics now allows you to customize time windows to capture only the incremental data you need. You can create a series of non-overlapping and contiguous time windows to perform analysis on new incremental data. By scanning the incremental data instead of your entire data store, you can improve analysis efficiency and lower costs.
For more information, please check out the service documentation.