Distributed Systems Questions and Answers for Viva

Answer-1: A Distributed System is a system that consists of multiple independent components (machines or nodes) that work together to achieve a common goal, communicating over a network.

Answer-2: The main characteristics include decentralization, scalability, fault tolerance, concurrency, and the ability to function across multiple locations.

Answer-3: Benefits include improved scalability, fault tolerance, resource sharing, high availability, and flexibility.

Answer-4: Challenges include network latency, synchronization, consistency, fault tolerance, security, and maintaining communication between nodes.

Answer-5: The CAP theorem states that a distributed system can only guarantee two out of the three properties: Consistency, Availability, and Partition Tolerance.

Answer-6: Consistency ensures all nodes have the same data at any given time, while Availability ensures the system is operational and can respond to requests even if some nodes are down.

Answer-7: Partition Tolerance means that the system can continue to operate even if network partitions or communication failures occur between nodes.

Answer-8: A distributed database is a database that is distributed across multiple machines or locations, with the data being stored in different locations to improve performance and reliability.

Answer-9: A centralized database is managed in a single location, while a distributed database spreads the data across multiple locations for better performance, fault tolerance, and scalability.

Answer-10: Microservice architecture is a design pattern where an application is divided into smaller, independently deployable services, which often communicate over a network, forming a distributed system.

Answer-11: A node is an individual machine or component within a distributed system that performs specific tasks and communicates with other nodes to achieve a common goal.

Answer-12: Message passing refers to the communication mechanism in which nodes send and receive messages over the network to share data or request services in a distributed system.

Answer-13: Synchronous communication requires both sender and receiver to be active and wait for a response, while asynchronous communication allows the sender and receiver to operate independently without waiting for each other.

Answer-14: Types of failures include network failures, node crashes, partition failures, message loss, and concurrency issues.

Answer-15: Fault tolerance refers to the ability of a distributed system to continue operating even if one or more of its components fail.

Answer-16: Data replication involves copying data from one node to another in a distributed system to improve data availability and fault tolerance.

Answer-17: Eventual consistency is a consistency model where updates to data are propagated through the system asynchronously, ensuring that, eventually, all nodes will have consistent data.

Answer-18: Strong consistency ensures all nodes see the same data at the same time, while eventual consistency allows temporary discrepancies in data, with the guarantee that consistency will be achieved eventually.

Answer-19: A distributed ledger is a decentralized database that records transactions across multiple nodes, ensuring data consistency and security, commonly used in blockchain technology.

Answer-20: Quorum refers to the minimum number of nodes required to perform an operation in a distributed system to ensure consistency and fault tolerance.

Answer-21: Sharding is a technique used to distribute data across multiple nodes by breaking it into smaller, manageable pieces (shards) to improve performance and scalability.

Answer-22: Load balancing is the process of distributing incoming traffic or workloads across multiple nodes in a distributed system to ensure optimal resource utilization and system performance.

Answer-23: A Distributed Hash Table (DHT) is a decentralized data structure used to distribute data across multiple nodes in a distributed system, ensuring efficient and scalable data storage and retrieval.

Answer-24: A coordinator is responsible for managing the communication and synchronization between nodes in a distributed system, ensuring operations are completed successfully.

Answer-25: Leader election is a process where a distributed system selects a leader node to coordinate activities and make decisions on behalf of the system.

Answer-26: Horizontal scaling involves adding more nodes to the system, while vertical scaling involves upgrading the existing hardware or resources of a node.

Answer-27: A distributed transaction involves multiple nodes in a distributed system coordinating to ensure that a transaction is completed successfully, maintaining consistency and atomicity.

Answer-28: A two-phase commit protocol is a distributed algorithm used to ensure that all participants in a transaction either commit or abort the transaction to maintain consistency.

Answer-29: Synchronous replication requires data to be written to all replicas before a write operation is confirmed, while asynchronous replication allows the write operation to be confirmed before data is propagated to replicas.

Answer-30: A distributed file system is used to store and manage data across multiple nodes in a distributed system, ensuring data availability, fault tolerance, and scalability.

Answer-31: A cloud-based distributed system operates on cloud infrastructure, providing scalability and resource management, while an on-premise distributed system operates on locally managed hardware.

Answer-32: Synchronization in distributed systems involves coordinating the actions of different nodes to ensure that they are working in a consistent and ordered manner.

Answer-33: A distributed cache is a system that stores data in multiple nodes across a network, allowing for faster access to frequently used data and reducing the load on primary databases.

Answer-34: A replicated log is a log file that is copied across multiple nodes in a distributed system to ensure that all nodes have an identical record of events and transactions.

Answer-35: Time synchronization ensures that the clocks of all nodes in a distributed system are aligned, preventing issues like data inconsistency and race conditions.

Answer-36: An atomic operation is an indivisible operation that either completes entirely or not at all, ensuring consistency in a distributed system.

Answer-37: A distributed consensus algorithm is used to ensure that all nodes in a distributed system agree on a common decision or value, even in the presence of failures.

Answer-38: Paxos is a consensus algorithm that ensures a distributed system can reach agreement on a single value, even if some nodes fail or messages are delayed.

Answer-39: Raft is a consensus algorithm designed to be easier to understand than Paxos, and it ensures that a distributed system can achieve consistency and fault tolerance.

Answer-40: Write skew is a consistency issue that occurs when concurrent writes to different nodes in a distributed system result in conflicting states.

Answer-41: Network partitioning can lead to communication failures between nodes, potentially causing inconsistencies and impacting system availability and consistency.

Answer-42: A replica is a copy of data stored in multiple locations or nodes in a distributed system to ensure fault tolerance, redundancy, and high availability.

Answer-43: Gossip protocols allow nodes in a distributed system to share information about state or failures, ensuring consistent knowledge across the system.

Answer-44: A distributed semaphore is a synchronization tool used to control access to shared resources in a distributed system, preventing race conditions and conflicts.

Answer-45: Consistency models define how a distributed system ensures that all nodes have the same data at any given time, impacting performance, fault tolerance, and reliability.

Answer-46: Strong consistency can reduce availability and increase latency, as it requires all nodes to be synchronized before providing responses.

Answer-47: A distributed event bus allows components in a distributed system to communicate asynchronously by sending and receiving events or messages, improving decoupling.

Answer-48: Idempotency ensures that multiple identical operations or requests do not cause unintended side effects, maintaining consistency in a distributed system.

Answer-49: A stateful service maintains session information or state across multiple requests, while a stateless service does not rely on previous requests and treats each one independently.

Answer-50: A distributed task queue manages and schedules tasks across multiple nodes in a distributed system, ensuring that tasks are efficiently distributed and executed.