AWS Certified Security - Specialty (SCS-C02) Cert Prep: 2 Security Logging and Monitoring

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Noah Gift

1:02:34

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01 - Introduction

01 - Domain 2 overview.mp4

01:00

02 - 1. Domain 2 Security Logging and Monitoring

01 - Designing and implementing monitoring and alerting.mp4

01:47

02 - Troubleshooting systems with five whys.mp4

04:06

03 - Using grep, cut, sort, and uniq.mp4

08:22

04 - Popular Linux tools and how to use them.mp4

14:27

05 - Designing log analysis solutions.mp4

02:51

06 - Configuring AWS CloudTrail for logging.mp4

03:14

07 - Analyzing logs with Amazon Athena.mp4

02:50

08 - Configuring AWS CloudShell for Bash.mp4

11:57

09 - Logging and monitoring with CloudWatch.mp4

05:47

10 - Optimizing log storage lifecycles.mp4

02:53

11 - Third-party log analysis tools.mp4

02:34

03 - Conclusion

01 - Security logging and monitoring summary.mp4

00:46

Description

The AWS Certified Security - Specialty (SCS-C02) exam is intended for individuals who currently work in or hope to someday land a cybersecurity role. The exam validates your ability to effectively demonstrate knowledge related to securing the AWS platform. This course, the second in a six-part learning path designed to help you prepare for the exam, focuses on the fundamentals of security logging and monitoring. Join MLOps expert, author, and adjunct professor Noah Gift as he guides you through the second domain of the exam. Learn how to design and implement monitoring and alerting procedures, troubleshoot systems, use popular Linux tools, design log analysis solutions, and configure AWS CloudTrail for logging. Along the way, Noah shows you how to analyze logs with Amazon Athena, set up AWS CloudShell for Bash, log and monitor with CloudWatch, optimize lifecycles, and leverage third-party tools.

This course was created by Noah Gift. We are pleased to host this training in our library.

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Amazon AWS

Cloud Computing

Noah Gift

Instructor's Courses

Author of Practical MLOps, Enterprise MLOps, Developing on AWS with C#, Pragmatic AI, and Python for DevOps. Certified on Multiple MLOps certifications including Google-Professional Machine Learning Engineer and AWS Certified Machine Learning - Specialty. Adjunct Professor at Duke MIDS & Northwestern Graduate Data Science & AI. Held business roles including CTO, general manager, consulting CTO, and cloud architect. Consults with start-ups and other companies on machine learning and cloud architecture. AWS ML Hero, Python Software Foundation Fellow, AWS Subject Matter on Machine Learning, AWS Certified Solutions Architect, AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, Google Certified Professional Architect, and AWS Academy Accredited Instructor. Published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Big Data and AI. ★ Specialties ★ ° Cloud-native Machine Learning and AI ° Directly teaching cutting edge skills to students that lead to jobs ° Creating world-class content in all forms ° Building Companies ° Shipping new Products ° Leading and growing engineering teams ° Production Machine Learning, Deep Learning, Big Data, and AI ° Serverless Data Engineering ° Advising Early Stage Startups/Consulting CTO services ° Distributed Systems and Scalability

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