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IntroductionCo-author: @Jan Inge Bergseth Cognite Functions provide a run-time environment for hosting and running Python code, similar to Azure Functions, Google Cloud Functions, or Amazon Lambda. One of the benefits of utilizing the built in Functions capability of CDF is that it is tightly coupled with CDF and gives you, as a developer, an implicit Cognite client allowing you to seamlessly interact with your CDF data and data pipeline. CDF Extraction Pipelines allow you to monitor the data flow and gain visibility into the run history and receive notifications from data integration events that need to be paid attention to, all of which is an important part of the resulting data quality. CDF Extraction Pipelines offer a great feature for storing extractor configuration settings, allowing you to remotely configure the extractor. This can be extremely helpful as it avoids having to locally manage extractor configuration. This article will explore the combination of Extraction Pipelines
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