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Datadog Metrics Extraction and Analysis

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2022

This feature thread tracks the development and enhancement of Shopify's capabilities for extracting and analyzing metrics from Datadog. Initial efforts focused on addressing the limitations of Datadog's built-in visualization and analysis tools, as well as the granularity issues with long-term metric data. This post details a step-by-step guide for extracting Datadog metrics using its REST API and performing in-depth analysis locally in Jupyter notebooks using Python. The process involves obtaining API credentials, defining metric queries, handling API rate limits, and processing the extracted data into a more granular format for advanced visualization and statistical modeling.

2022

How to Export Datadog Metrics for Exploration in Jupyter Notebooks - Shopify

11/29/2022

This post details a method for extracting Datadog metrics using its REST API and Python. It outlines the steps for obtaining API credentials, defining metric queries, handling API rate limits by adjusting time deltas and bucketing requests, and processing the extracted data into a pandas DataFrame for local analysis in Jupyter notebooks. The post also demonstrates visualizing the extracted data using seaborn for deeper insights into system performance, such as CPU utilization distribution.