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Monitoring AWS Workloads

Learn how apps run in AWS and what you should know to effectively monitor them.

Task 1: Introduction

Task 2: Monitoring EC2

Task 3: Falco for EC2

Task 4: Monitoring Containers

Task 5: Falco for Containers

Task 6: AWS Lambda Theory

Task 7: AWS Lambda Practice

Task 8: Conclusion

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Monitoring AWS Workloads

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Learn how apps run in AWS and what you should know to effectively monitor them.

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60 min

2,099

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There are many ways to run applications and tasks in the cloud. Lab machines on , containers, and serverless functions are among the most common workload types. Although they can all run the same code, each introduces its own monitoring challenges. In this room, you will explore the features of common workloads, how attackers target them, and how to monitor them using Falco and .

Learning Objectives

  • Learn about EC2 Systems Manager and EC2 Auto Scaling
  • Explore the challenges when monitoring containers in AWS
  • Discover Falco as a tool for -aware runtime monitoring
  • Dive into less common attacks involving AWS Lambda functions
  • Practice the material in via CloudTrail and Falco datasets

Prerequisites

Lab Access

Start the lab by clicking the Start Lab Machine button below. You will then have access to the Splunk Web Interface. Please wait 4-5 minutes for the Splunk instance to launch. To access Splunk, follow this link:

Set up your virtual environment

To successfully complete this room, you'll need to set up your virtual environment. This involves starting the Lab Machine, ensuring you're equipped with the necessary tools and access to tackle the challenges ahead.
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Let's begin!