Implementing Splunk IT Service Intelligence (ISITSI) – Outline

Detailed Course Outline

Module 1- Key Concepts

  • Basic ITSI User Interface
  • Key App Organizational Concepts
  • Useful Add-ons and Apps
  • Install ITSI Support Software
  • Identify Add-on and App Dependencies

Module 2 – About Entities and Types

  • Entity basics
  • Entity Type basics
  • Explore existing types
  • Edit and create Entity Types

Module 3 – Creating and Importing Entities

  • Manually creating entities
  • Importing entities by search
  • Entity management and retirement policies
  • Delete or retire entities
  • Monitoring entities

Module 4 – Service Plan

  • Understanding service health scores
  • Defining service dependencies
  • Finding and using data for a service
  • Compile a service plan

Module 5 – Key Performance Indicator Design

  • Understanding KPIs
  • KPI criteria and sources
  • Defining KPI thresholds
  • Designing a service's KPIs

Module 6 – KPI Base Searches

  • Analyze a data environment
  • Identify entity-oriented KPIs
  • Creating Base Searches
  • Understanding and using pseudo entities

Module 7 – Implementing Services

  • Creating the ITSI service from the plan
  • Create KPIs using base searches
  • Configure KPI lag and backfill
  • Set KPI importance
  • Calculate service health score

Module 8 – Service Templates

  • About Service Templates
  • Create a template from a service
  • Create a service from a template
  • Create dependencies between services

Module 9 – Service Sandbox

  • Understanding the Service Sandbox
  • Creating a file for Sandbox import
  • Import a Service Sandbox
  • Create dependencies between services
  • Perform a Service Health Score simulation

Module 10 – Using Thresholds and Time Policies

  • Understanding static thresholds
  • Configure KPI thresholds
  • Use aggregate and entity-level thresholds
  • Apply time policies to thresholds
  • Create custom threshold templates

Module – 11 Machine Learning and AI in ITSI

  • Understanding ML/AI-assisted threshold types and algorithms
  • Configure adaptive thresholds
  • Configure AI Recommended thresholds
  • Create a custom adaptive threshold template

Module 12 – Predictive Analytics

  • Define predictive analytics
  • Train a predictive model
  • Configure predictive analytics for services
  • Configure alerting for predicted Service Health Scores

Module 13 – Anomaly Detection

  • Understanding anomaly detection
  • Configure anomaly detection for KPIs
  • Alerts for Deep Dives and Notable Event Episodes

Module 14 – Multi-KPI Alerts and Correlation Searches

  • Define Multi-KPI alerts
  • Create Multi-KPI alerts
  • Understanding Correlation Searches
  • Describing existing Correlation Searches
  • Defining a Correlation Search

Module 15 – Notable Event Aggregation Policies

  • Define aggregation policy capabilities
  • Modify the default aggregation policy
  • Create a custom aggregation policy
  • Describe Action Rules
  • Understand third-party integration