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Root Cause Analysis (RCA) With GenAI
2 Courses
1 Hours
Skill IQ
The "Root Cause Analysis (RCA) With GenAI" learning path aims to equip Site Reliability Engineers (SREs) and cloud engineers with the ability to leverage Generative AI and Large Language Models (LLMs) for efficient incident log analysis, root cause identification, and report generation, thereby enhancing incident management and system reliability.
Content in this path
Getting Started
This path is designed for beginner cloud engineers and IT professionals seeking to understand the foundational concepts and strategic applications of Generative AI and Large Language Models (LLMs) in enhancing cloud operations.
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What You'll Learn
- 1. Leveraging LLMs for Incident Analysis: Learners will understand how to employ Large Language Models to efficiently ingest and analyze incident logs, transforming large volumes of unstructured data into actionable insights.
- 2. Automating Root Cause Analysis: The path will enable learners to automate the root cause analysis process using GenAI, improving accuracy and reducing the time spent on manual investigation.
- 3. Generating Effective RCA Summaries: Participants will gain the skills to create clear and concise RCA summaries using GenAI tools, enhancing communication and decision-making during incident management.
Prerequisites
- The prerequisites for the "Root Cause Analysis (RCA) With GenAI" learning path include a basic understanding of cloud computing and infrastructure, particularly platforms like AWS, Azure, or Google Cloud. Learners should also have foundational knowledge of incident management principles, as well as introductory familiarity with AI and machine learning concepts, including Large Language Models. Basic programming skills in languages like Python will be beneficial for engaging with hands-on labs and implementing AI solutions effectively.
Related topics
- Generative AI
- Log Analysis
- Cloud Operations
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