Lesson 2: REST API Resources, Metric Ingestion, Metadata, Dashboards, Detectors, and Automation Workflows

Lesson Overview

This lesson develops practical capability in rest api resources, metric ingestion, metadata, dashboards, detectors, and automation workflows for the Automation Using the REST and SignalFlow APIs Training. Learners connect the topic to the wider course goal of automating observability data, detectors, dashboards, and analytics with REST and SignalFlow APIs.

Topics Covered

REST API Resources, Metric Ingestion, Metadata, Dashboards, Detectors, and Automation Workflows: purpose, terminology, architecture, roles, and expected business or operational outcomes
Core Splunk data, searches, configuration, objects, integrations, interfaces, and security controls relevant to the topic
Design decisions, dependencies, risks, permissions, performance considerations, and governance requirements
Guided practice focused on configuration, searches, integrations, security controls, and implementation patterns
Testing, validation, diagnostics, troubleshooting, documentation, and operational support

Practical Activity

Build or configure the core searches, objects, settings, integrations, or workflows covered in the lesson and record expected results.
Capture assumptions, configuration choices, expected results, test evidence, and remediation notes in a reusable worksheet.
Review the completed exercise against security, data quality, performance, maintainability, and support-readiness criteria.

Key Takeaways

Explain the purpose and architecture of rest api resources, metric ingestion, metadata, dashboards, detectors, and automation workflows.
Apply the principal Splunk features and workflows required for the lesson scenario.
Validate results, identify common failure points, document decisions, and support a controlled operational outcome.

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Automation Using the REST and SignalFlow APIs Training 1 Section4 Lessons16 Hours

Curriculum