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Data Ingestion with Python Cookbook

Data Ingestion with Python Cookbook

By : Gláucia Esppenchutz
4.5 (4)
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Data Ingestion with Python Cookbook

Data Ingestion with Python Cookbook

4.5 (4)
By: Gláucia Esppenchutz

Overview of this book

Data Ingestion with Python Cookbook offers a practical approach to designing and implementing data ingestion pipelines. It presents real-world examples with the most widely recognized open source tools on the market to answer commonly asked questions and overcome challenges. You’ll be introduced to designing and working with or without data schemas, as well as creating monitored pipelines with Airflow and data observability principles, all while following industry best practices. The book also addresses challenges associated with reading different data sources and data formats. As you progress through the book, you’ll gain a broader understanding of error logging best practices, troubleshooting techniques, data orchestration, monitoring, and storing logs for further consultation. By the end of the book, you’ll have a fully automated set that enables you to start ingesting and monitoring your data pipeline effortlessly, facilitating seamless integration with subsequent stages of the ETL process.
Table of Contents (17 chapters)
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1
Part 1: Fundamentals of Data Ingestion
9
Part 2: Structuring the Ingestion Pipeline

Setting custom alerts or notifications

After configuring our first dashboard to be aware of the Airflow application, we must ensure our monitoring is never left without observation. With teams busy with other tasks, creating alerts is the best way to guarantee we still have oversight over the application.

There are many ways to create alerts and notifications, and previously we implemented something similar to monitor our DAG by sending an email notification when an error occurs. Now, we will try a different approach, using an integration with Telegram.

In this recipe, we will integrate Grafana alerts with Telegram. Using a different tool to provide system alerts can help us understand the best approach to advise our teams and break the cycle of always using email.

Getting ready

Refer to the Technical requirements section for this recipe since we will handle it with the same technology.

To accomplish this exercise, ensure that StatsD, Prometheus, and Grafana are...

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