notebooks

What problem does it solve? Manually building Datadog Notebooks for incident investigations, weekly reports, and runbooks is repetitive and slow, especially when combining documentation with live metric, log, and trace visualizations. ## Core Features & Use Cases - Notebook CRUD Operations: Create, list, get, update, and delete Datadog Notebooks through the pup CLI with author filtering and pagination. - Mixed Content Cells: Build notebooks combining markdown documentation with timeseries, toplist, heatmap, distribution, and log stream visualization cells. - Flexible Time Ranges: Set global notebook time spans (relative or absolute) and override time ranges per individual cell. - Use Case: During an incident, create an investigation notebook with a markdown timeline, a timeseries graph of request duration, a toplist of slowest queries, and an error log stream, all scoped to the last 4 hours. ## Quick Start Create a Datadog notebook named "Incident Investigation" with a markdown summary cell and a timeseries cell showing production error rates over the last 4 hours.