The video tutorial discusses distributed systems, focusing on CouchDB. It begins with an overview of the current system setup and its limitations. The tutorial then explores enhancing fault tolerance and high availability by adding nodes. The CAP theorem is explained, highlighting the trade-offs between consistency, availability, and partition tolerance. The video concludes with challenges in implementing distributed systems, particularly eventual consistency and ensuring the latest data state across nodes.

What is the primary reason for adding more nodes to a distributed system?

• To increase the system's speed

• To simplify the system architecture

• To enhance fault tolerance and availability

• To reduce the cost of operation

According to the CAP theorem, which two properties does CouchDB prioritize?

• Consistency and Availability

• Availability and Partition Tolerance

• Consistency and Partition Tolerance

• Scalability and Security

What is the term used to describe the delay in data consistency across nodes in a distributed system?

• Immediate Consistency

• Delayed Consistency

• Eventual Consistency

• Partial Consistency

What challenge arises when multiple nodes handle requests in a distributed system?

• Simplified data management

• Reduced system speed

• Difficulty in ensuring the latest data state

• Increased system cost

How can a distributed system ensure it displays the latest changes?

• By updating the state with change notifications

• By ignoring partition tolerance

• By using a single master node

• By reducing the number of nodes