AWS Solutions Architect Associate (SAA-C02) Exam Prep Course - 2021 UPDATED! - Load Balancer Concepts

The video tutorial introduces the concept of load balancing, explaining its importance in improving system performance. It covers the history and basic principles of load balancing, including the roles of load balancers in managing requests between requesters and servicers. The tutorial distinguishes between sender and receiver initiated load balancing, and compares static and dynamic load balancing, highlighting AWS Elastic Load Balancing as an example of dynamic load balancing. Various algorithms used in load balancing, such as round robin and threshold-based, are discussed. The video concludes with considerations for implementing load balancing, emphasizing the need for synchronized storage among servicing nodes.

What is the primary purpose of load balancing in a system?

• To increase the number of servers

• To distribute tasks across multiple servers

• To eliminate the need for servers

• To reduce the number of servers

Which component is responsible for directing incoming requests to different nodes?

• Database server

• Application server

• Load balancer

• Web server

In sender-initiated load balancing, who decides the best target for a request?

• The receiver

• The sender

• The load balancer

• The client

What is a key characteristic of dynamic load balancing?

• Tasks are not assigned to any server

• Tasks are assigned to specific servers permanently

• Tasks are dynamically assigned to servers

• Tasks are only assigned to one server

Which load balancing algorithm involves rotating requests through servicing nodes?

• Threshold-based

• Centrally managed

• Round-robin

• Randomized

What is a potential issue if servicing nodes do not have synchronized storage?

• Reduced server load

• Increased server costs

• Inconsistent data for users

• Faster data processing

Which algorithm might consider the current service load and time of day?

• Round-robin

• Randomized

• Centrally managed

• Threshold-based