Full Observability Pipeline with Splunk OpenTelemetry (FOPSOT)

Module 1: Splunk Observability Cloud

• Differentiate between monitoring and observability
• Describe the telemetry data for observability
• Describe Splunk Observability Cloud architecture
• Navigate Splunk Observability cloud
• Use built-in content to Interpret system health and activity

Module 2: Introduction to the OpenTelemetry Collector

• Describe OpenTelemetry and available distributions
• Describe OpenTelemetry Collector packaging options, deployment models and ingestion modes
• Visualize the flow of telemetry data through the Collector pipeline, from ingestion to export
• Deploy and configure the OpenTelemetry Collector using guided steps
• Use best practices and advanced configuration techniques

Module 3 – Traces Pipeline

• Use the `otlphttp` exporter to send traces to Splunk Observability Cloud
• Compare auto and manual instrumentation approaches
• Auto-instrument a Node.js Express application using the Splunk
• OpenTelemetry JavaScript agent
• Enrich traces with additional metadata using processors
• Explore trace data and errors using the APM Service Map

Module 4 – Metrics Pipeline

• Define processors to rename, aggregate, and scale metrics
• Configure the signalfx exporter
• Explain the importance of metric normalization
• Apply best practices when editing the otelcol-config.yml file

Module 5 – Logs Pipeline

• Describe log ingestion into Splunk via splunk_hec and how logs become viewable in Splunk Observability Cloud.
• Use Log Observer to search and explore logs
• Filter noisy logs with the filter processor to reduce telemetry volume and control data costs.
• Redact, or modify log data to meet privacy and compliance needs

Module 6 – Putting it all Together

• Create custom charts, dashboards, and alerts for telemetry data
• Use telemetry signals and related content to find issues and troubleshoot root cause of problems