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This lesson introduces AWS CloudTrail as the foundational service for auditing and governance. We will cover its core function of recording all user activity and API usage across an AWS account. The session will differentiate between the two main types of logged events: Management Events (control plane operations like creating an EC2 instance) and Data Events (high-volume, data-plane operations like S3 object access). We will explore the default 90-day Event History and then explain the necessity of creating a "Trail" to deliver immutable, long-term log files to an S3 bucket for security analysis and compliance. A key focus will be on the log file integrity validation feature, which ensures logs have not been tampered with. The lesson will conclude with a practical walkthrough of the CloudTrail console to view recent events.
This lesson introduces the core concepts of AWS EC2, focusing on the fundamental decisions required to provision a virtual server. We will start by defining an EC2 instance, an Amazon Machine Image (AMI) as a template, and the various instance type families (e.g., General Purpose, Compute Optimized) to match hardware to workload needs. A significant portion will be dedicated to a practical comparison of the primary EC2 pricing models: On-Demand for flexibility, Reserved Instances for cost savings on predictable workloads, and Spot Instances for fault-tolerant, cost-sensitive tasks. The lesson concludes by contrasting the two main storage options: persistent, network-attached Elastic Block Store (EBS) volumes versus ephemeral, high-performance, physically-attached Instance Store volumes.
This lesson introduces the core concepts of data visualization within the AWS ecosystem, focusing on Amazon QuickSight. It begins by identifying different types of data consumers (from data experts to business users) and their needs. We will then dive into QuickSight as a cloud-native, serverless BI service, exploring its key differentiators, such as the SPICE in-memory engine for high performance. The session will cover how to connect to various AWS and third-party data sources, the distinction between a "Data Source" and a "Dataset", and the fundamental steps of data preparation within the QuickSight UI. You will learn the basics of the analysis workspace, including the concepts of dimensions and measures, and how to use AutoGraph to create your first visual.
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