What problem does it solve? Managing log pipelines across diverse sources, processors, and destinations requires deep knowledge of the Datadog Observability Pipelines API and its component schemas. This Skill provides the operational instructions and configuration patterns needed to design, validate, deploy, and maintain pipelines without memorizing the API surface. ## Core Features & Use Cases - Full Pipeline Lifecycle: List, create, update, validate, and delete pipelines via the Datadog API v2 remote config endpoints. - Component Library: Covers 15+ sources (Kafka, S3, Splunk, Pub/Sub), 17+ processors (filter, grok parsing, PII scanning, quota, sampling), and 17+ destinations (Datadog Logs, S3, Splunk HEC, Microsoft Sentinel, Elasticsearch). - Use Case: Build a compliance pipeline that ingests logs from the Datadog Agent, redacts credit card numbers with the sensitive_data_scanner processor, and routes sanitized logs to both Datadog and an S3 archive. ## Quick Start Ask the agent to create a pipeline that collects logs from the Datadog Agent, filters for errors, and sends them to Datadog Logs.
