This Splunk AI Test Drive training is a 1-day course, targeted to Presales and Technical Sales audiences with minimum or no knowledge about Splunk.
In today's data-driven landscape, organizations are constantly seeking innovative solutions to extract actionable insights, enhance operational efficiency, and bolster security measures. Splunk AI emerges as a transformative tool that empowers companies to harness the power of artificial intelligence (AI) to optimize their operations and drive business success. By leveraging Splunk AI, organizations can unlock many benefits, including advanced data analysis, predictive capabilities, streamlined security operations, and improved decision-making processes. This integration of AI within the Splunk platform not only enhances the effectiveness of data analysis but also enables companies to proactively address challenges, mitigate risks, and deliver superior services to their customers. Through Splunk AI, companies can work smarter, faster, and more effectively, reducing operating costs and positioning themselves at the forefront of innovation and competitiveness in today's dynamic business environment.
The goal of this Test Drive is to provide participants with a high-level understanding of Splunk's AI Ops capabilities, the key benefits, and practical experience through hands-on activities. This condensed format allows prospective customers to quickly grasp the value proposition and potential impact of Splunk for their AI Ops initiatives.
Course Objectives:
By the end of this test drive, participants will be able to:
- Identify the basics of Splunk and its core capabilities
- Explore Splunk's AI Ops use cases and benefits
- Gain hands-on experience with Splunk's AI Ops features
- Discover how Splunk integrates with security and incident management
- Recognize the value of Splunk's AI Ops capabilities
Module 1: Introduction
- Overview of AI Operations and its importance in modern IT environments
- Introducing Splunk's capabilities in the AI Ops space
Module 2: Splunk Essentials Quick Review
- Getting started with Splunk: navigating the interface
- Ingesting and indexing data
- Performing basic searches and visualizations
Module 3: AIOps Use Cases
- Demonstrating Splunk's predictive analytics and anomaly detection
- Automated root cause analysis for incident response
- Intelligent alert management and incident intelligence
Module 4: Machine Learning with Splunk
- Introduction to key ML algorithms used in Splunk
- Building predictive models using the Splunk ML Toolkit
- Applying ML for classification, regression, and anomaly detection
Module 5: Operationalizing AIOps
- Integrating AIOps insights into incident management workflows
- Leveraging Splunk Security Essentials for threat detection
- Automating responses based on ML predictions
Module 6: Wrap-up and Next Steps
- Summary of key benefits and takeaways
- Resources for further learning and Splunk specialization/certification
- Q&A session
Lab Outline
Lab 1: Data Analysis Introduction
- Upload dataset to Splunk.
- Index sample data for analysis.
- Create visualizations.
Lab 2: Data Preparation
- Cleanse real-world data.
- Create relevant features for ML.
Lab 3: Building Your First AIOps Model using Splunk
- Train a model to predict incidents.
- Evaluate model performance.
Lab 4: Demo Real-World AIOps Scenarios
- Analyze live data streams.
- Implement automated actions based on ML recommendations.
The primary audience for this course is as follows:
- Systems Engineers
- Technical Solutions Architects
- Application Developers and Engineers
- Technical Decision Makers