Book Image

Data Ingestion with Python Cookbook

By : Gláucia Esppenchutz
Book Image

Data Ingestion with Python Cookbook

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)
1
Part 1: Fundamentals of Data Ingestion
9
Part 2: Structuring the Ingestion Pipeline

Setting up Prometheus for storing metrics

Although it is generally called a database, Prometheus is not a traditional database like MySQL. Instead, its structure is more similar to a time-series database designed for monitoring and observability purposes.

Due to its flexibility and power, this tool is widely used by DevOps and Site Reliability Engineers (SREs) to store metrics and other relevant information about systems and applications. Together with Grafana (which we will explore in later recipes), it is one of the most used monitoring tools in projects and by teams.

This recipe will configure a Docker image to run a Prometheus application. We will also connect it to StatsD to store all the metrics generated.

Getting ready

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

How to do it…

Here are the steps to perform this recipe:

  1. Let’s begin by adding the following lines to our docker...