The video tutorial provides an overview of Amazon EC2's role in big data processing, focusing on different instance types such as spot, reserved, and on-demand instances. It explains the cost benefits and use cases for each type, emphasizing the importance of checkpointing for spot instances and the cost savings of reserved instances for long-term use. The tutorial also covers auto scaling for handling variable data loads and discusses the role of EC2 in EMR clusters, highlighting the differences between master and compute nodes.

What is a key characteristic of Spot instances in AWS EC2?

• They are only used for machine learning tasks.

• They are reserved for a specific period.

• They are the most expensive option.

• They can be terminated by AWS at any time.

Why might you choose Reserved instances for your AWS EC2 usage?

• For short-term, unpredictable workloads.

• To get a discount for long-term, stable workloads.

• To avoid any risk of instance termination.

• For workloads that require high availability.

When is it most appropriate to use On-demand instances?

• For workloads that require high computational power.

• For workloads with unpredictable usage patterns.

• For workloads that can tolerate interruptions.

• For workloads that are stable and predictable.

How does Auto Scaling benefit data processing in AWS?

• It reduces the need for data backup.

• It automates the scaling of resources based on demand.

• It provides a fixed number of resources regardless of demand.

• It ensures data is always stored in multiple locations.

In an EMR cluster, what is the primary role of compute nodes?

• To manage the cluster's overall operations.

• To execute tasks without storing data.

• To provide backup for master nodes.

• To store and process data.