Detailed Course Outline
Module 1 – Splunk Data Processing Introduction
- Review and discuss the classic Splunk GDI architecture
- Highlight the benefits and the implementation parameters
- Explain how Splunk ingestion pipeline scales
- Understand the role of Splunk data ingestion processing solutions
- List the data flow attributes in inputs.conf and outputs.conf
Module 2 – Data Processing with Intermediate Forwarders
- List the benefits and challenges of processing data at the edge
- Deploy and manage intermediate forwarders
- Use classic parsing techniques to transform events
- Explore strategies for optimizing data flow
Module 3 – Data Processing with Ingest Actions
- Set up Ingest Actions in your environment
- Create pipeline rulesets with Ingest Actions
- Understand the underlying conf file attributes
- Manage and deploy ingest Actions rulesets
Module 4 – Data Processing with Edge Processor
- Describe what Edge Processor is and how it works
- Configure the Edge Processor control plane
- Set up data sources and destinations
- Deploy and manage Edge Processor instances
- Use SPL2 for ingest pipeline authoring and deployment
- Masking, filtering, enriching and routing of data
- Monitor data plane health using the control plane UI
Module 5 – Data Processing with Ingest Processor
- Describe what Ingest Processor is and how it works
- List the differences between Edge Processor and Ingest Processor
- Use SPL2 for ingest pipeline authoring and deployment
- Convert a log source into metrics and route them to Splunk Observability Cloud
- Monitor data plane health of Ingest processor pipelines
Module 6 – Data Management Solution Integration
- Identify the best practices for using Splunk ingestion solutions
- Understand how different pipelines work together in Splunk
- Identify critical events in the logs for troubleshooting
- List the steps to decommission Data Management Experience pipelines