System Design - Scalability, Reliability & Distributed Patterns Flashcards

Question 1

What is Latency?

Accepted Answer

Latency is the time delay between a user's action (request) and the system's response. Lower latency means a faster, more responsive user experience and is a key performance metric.

Question 2

What is System Design?

Accepted Answer

System Design is the process of defining the architecture, modules, interfaces, and data for a system to satisfy specified requirements. It's about building robust, scalable, and reliable software solutions.

Question 3

Define Scalability in System Design.

Accepted Answer

Scalability is the ability of a system to handle a growing amount of work (e.g., user requests, data volume) by adding resources, while maintaining performance and responsiveness. It ensures the system can grow with demand.

Question 4

Explain Vertical Scalability.

Accepted Answer

Vertical scalability (scaling up) involves adding more resources (e.g., `CPU`, `RAM`, faster disk) to an existing single server or machine. It's simpler to implement but has hardware limits and introduces a single point of failure.

Question 5

Explain Horizontal Scalability.

Accepted Answer

Horizontal scalability (scaling out) involves adding more servers or nodes to a distributed system to share the workload. It's more complex to manage but offers near-limitless growth potential and improved fault tolerance.

Question 6

What is Reliability in System Design?

Accepted Answer

Reliability is the probability that a system will perform its intended function without failure for a specified period under specified conditions. It focuses on minimizing downtime, errors, and data loss.

Question 7

Define Availability.

Accepted Answer

Availability is the proportion of time a system is operational and accessible to users. It's often expressed as a percentage (e.g., 'five nines' for 99.999% availability) and is crucial for user experience.

Question 8

Define Throughput.

Accepted Answer

Throughput is the number of operations, requests, or transactions a system can process per unit of time (e.g., requests per second, messages per minute). Higher throughput indicates greater processing capacity.

Question 9

Explain the CAP Theorem.

Accepted Answer

The CAP Theorem states that it's impossible for a distributed data store to simultaneously provide more than two out of the following three guarantees: `Consistency`, `Availability`, and `Partition Tolerance`.

Question 10

What are the three components of the CAP Theorem?

Accepted Answer

The three components are:
1.  `Consistency`: All clients see the same data at the same time, regardless of which node they connect to.
2.  `Availability`: Every request receives a response, without guarantee that it contains the most recent version of the information.
3.  `Partition Tolerance`: The system continues to operate despite arbitrary message loss or failure of part of the system.

Question 11

What is Load Balancing and why is it used?

Accepted Answer

Load balancing is the process of distributing incoming network traffic across multiple servers to ensure no single server is overloaded. It improves responsiveness, increases availability, and enhances fault tolerance by preventing bottlenecks.

Question 12

Explain Caching in System Design.

Accepted Answer

Caching involves storing frequently accessed data in a faster, temporary storage layer (cache) closer to the user or application. This reduces latency, decreases database load, and improves overall system performance. Common strategies include `LRU` (Least Recently Used) and `LFU` (Least Frequently Used).

Question 13

What is Sharding (or Data Partitioning)?

Accepted Answer

Sharding is the technique of dividing a large database or dataset into smaller, more manageable pieces called shards or partitions. Each shard can be hosted on a separate server, improving scalability, performance, and manageability of very large datasets.

Question 14

How do Message Queues contribute to system design?

Accepted Answer

Message queues enable asynchronous communication between different parts of a system. Producers send messages to the queue, and consumers retrieve and process them independently. This decouples services, improves fault tolerance, and smooths out traffic spikes. Examples: Kafka, RabbitMQ, SQS.

Question 15

Define Eventual Consistency.

Accepted Answer

Eventual consistency is a consistency model where, if no new updates are made to a given data item, all reads of that item will eventually return the last updated value. It prioritizes availability and partition tolerance over strong consistency, common in distributed databases.

Question 16

Compare Monolithic vs. Microservices Architecture.

Accepted Answer

A `Monolith` is a single, tightly coupled application where all components run as one service. It's simpler to develop initially but harder to scale and maintain as it grows.

A `Microservices` architecture builds an application as a collection of small, independent services, each running in its own process and communicating via `API`s. It offers better scalability, fault isolation, and technology diversity but adds operational complexity.

Question 17

What is Fault Tolerance?

Accepted Answer

Fault tolerance is the ability of a system to continue operating without interruption, or with minimal degradation, even if one or more of its components fail. This is achieved through redundancy, replication, and graceful degradation mechanisms.

Question 18

Explain Database Replication.

Accepted Answer

Database replication involves creating and maintaining multiple copies of a database. This improves data availability, fault tolerance (by providing backups), and read scalability (by distributing read queries across replicas). Common types include `Master-Slave` and `Multi-Master`.

Question 19

What is a Content Delivery Network (CDN)?

Accepted Answer

A CDN is a geographically distributed network of proxy servers and their data centers. Its goal is to provide high availability and performance by distributing service spatially relative to end-users, serving content (e.g., images, videos, static files) from the nearest edge location.

Question 20

Describe the Circuit Breaker Pattern.

Accepted Answer

The Circuit Breaker Pattern is a design pattern used to prevent a system from repeatedly trying to execute an operation that is likely to fail (e.g., calling a failing external service). When a service repeatedly fails, the circuit breaker 'trips' (opens), preventing further calls to that service for a period, allowing it to recover and preventing cascading failures.

Question 21

What is Idempotency in API design?

Accepted Answer

An operation is idempotent if it can be applied multiple times without changing the result beyond the initial application. For example, deleting a resource multiple times has the same effect as deleting it once. This is crucial for building reliable distributed systems where requests might be retried.

Question 22

Differentiate between Stateless and Stateful Services.

Accepted Answer

A `Stateless` service does not store any client-specific data or session information between requests; each request contains all necessary information. They are easier to scale horizontally.

A `Stateful` service stores client-specific data or session information, often in memory, across multiple requests. They are harder to scale and manage, as state needs to be synchronized or persisted across instances.

System Design - Scalability, Reliability & Distributed Patterns

Cards in this deck

Related Flashcard Sets

JLPT N5 - Essential Grammar & Kanji

Kubernetes Fundamentals & Container Orchestration

Pharmacology - Drug Classes & Mechanisms of Action

CompTIA Security+ (SY0-601) - Threats, Attacks & Vulnerabilities