System Design Guide for Software Professionals : Build Scalable Solutions - from Fundamental Concepts to Cracking Top Tech Company Interviews

System Design Guide for Software Professionals Build Scalable Solutions - from Fundamental Concepts to Cracking Top Tech Company Interviews

Enhance your system design skills to build scalable and efficient systems by working through real-world case studies and expert strategies to excel in interviews Key Features Comprehensive coverage of distributed systems concepts and practical system design techniques. Insider tips and proven strate...

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Detalles Bibliográficos
Otros Autores: Sinha, Dhirendra, author (author), Chopra, Tejas, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham, England : Packt Publishing [2024]
Edición:First edition
Materias:
Computer software > Development.
Software architecture.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009843332606719
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright and Credits
  • Contributors
  • Table of Contents
  • Preface
  • Part 1: Foundations of System Design
  • Chapter 1: Basics of System Design
  • What is system design?
  • Software system
  • Distributed software system
  • Understanding system design
  • What are the types of system design?
  • High-level system design
  • System architecture
  • Data flow
  • Scalability
  • Fault tolerance
  • Low-level system design
  • Algorithms
  • Data structures
  • APIs
  • Code optimization
  • Importance of system design in the industry
  • Practical examples of the importance of system design
  • Summary
  • Chapter 2: Distributed System Attributes
  • A hotel room booking example
  • Consistency
  • Strong consistency
  • Eventual consistency
  • Availability
  • Understanding partition tolerance
  • Network partition
  • Partition tolerance
  • Latency
  • Durability
  • Reliability
  • Fault tolerance
  • Scalability
  • Vertical scaling
  • Horizontal scaling
  • Summary
  • Chapter 3: Distributed Systems Theorems and Data Structures
  • CAP theorem
  • PACELC theorem
  • Paxos
  • Raft
  • BGP
  • The Byzantine fault
  • Byzantine fault tolerance
  • Modern BFT
  • FLP impossibility theorem
  • Consistent hashing
  • Bloom filters
  • Count-min sketch
  • HyperLogLog
  • Summary
  • Part 2: Core Components of Distributed Systems
  • Chapter 4: Distributed Systems Building Blocks: DNS, Load Balancers, and Application Gateways
  • Exploring DNS
  • DNS querying
  • Scalability, reliability, and consistency in DNS
  • Scalability
  • Reliability
  • Consistency
  • Load balancers
  • Placing load balancers
  • Advantages of load balancers
  • Global and local load balancing
  • DNS and GSLB
  • Load balancer algorithms
  • Load balancing at different layers of the Open Systems Interconnection (OSI) model
  • Deployment of load balancers
  • Implementing load balancers.
  • Application gateways
  • Features and capabilities
  • Microservices architectures
  • Cloud-native implementations
  • On-premises options
  • Summary
  • Chapter 5: Design and Implementation of System Components -Databases and Storage
  • Databases
  • Types of databases
  • Relational databases
  • NoSQL databases
  • The advantages and disadvantages of relational and NoSQL databases
  • NoSQL databases
  • Key-value stores
  • What is a key-value store?
  • Use in distributed systems
  • Designing a key-value store
  • Enhancing scalability and data replication
  • Boosting scalability
  • Consistent hashing
  • Virtual nodes
  • Data duplication strategies
  • Implementing get and put functions
  • Implementing get and put operations
  • Using r and w
  • Ensuring fault tolerance and identifying failures in a key-value store
  • Managing temporary failures
  • Addressing permanent failures
  • Ring membership promotion for failure detection
  • A system design interview - key value store design questions and strategies
  • DynamoDB
  • No fixed schema
  • API functions
  • Partitioning data in DynamoDB
  • Throughput optimizations in DynamoDB
  • High availability in DynamoDB
  • Column-family databases
  • HBase
  • HBase details
  • Graph-based databases
  • The Neo4j graph database
  • Neo4j details
  • Relational modeling versus graph modeling
  • Graph modeling
  • Adding a new node to an existing graph
  • Summary
  • References
  • Chapter 6: Distributed Cache
  • What is caching?
  • What is distributed caching?
  • How is it different from regular caching?
  • Use cases
  • Benefits of using a distributed cache
  • Challenges of using distributed caching
  • Designing a distributed cache
  • Requirements
  • Design journey
  • Popular distributed cache solutions
  • Redis
  • Memcached
  • How to choose between Redis and Memcached
  • Summary
  • Chapter 7: Pub/Sub and Distributed Queues.
  • The evolution of distributed systems
  • Designing a distributed queue
  • Designing a pub/sub system
  • Key characteristics of pub/sub systems
  • Pub/sub system design considerations
  • Kafka
  • The importance of Kafka in distributed systems
  • Kafka Streams
  • Kinesis
  • Summary
  • Part 3: System Design in Practice
  • Chapter 8: Design and Implementation of System Components: API, Security, and Metrics
  • REST APIs
  • Design principles of REST APIs
  • Use cases for REST APIs
  • Strengths and weaknesses
  • gRPC APIs
  • Design principles of gRPC APIs
  • Use cases for gRPC APIs
  • Strengths and weaknesses
  • Comparing REST and gRPC
  • API security
  • Authentication
  • Authorization
  • Secure communication of APIs
  • Rate limiting
  • Distributed systems logging
  • Centralized logging
  • Best practices for implementing distributed logging
  • Metrics in a distributed system
  • Types of metrics
  • Open source tools for metrics
  • Best practices for implementing metrics
  • Alerting in a distributed system
  • Designing effective alerts
  • Open-source tools for alerting
  • Best practices for implementing alerting
  • Tracing in a distributed system
  • Distributed tracing
  • Open-source tools for distributed tracing
  • Best practices for implementing tracing
  • Best practices
  • Summary
  • Chapter 9: System Design - URL Shortener
  • Real-world use cases
  • Functional requirements
  • Non-functional requirements
  • Client APIs needed
  • Estimates and calculations
  • System design
  • Core challenge
  • Choice of database
  • High-level solution architecture
  • Requirements verification
  • Summary
  • Chapter 10: System Design - Proximity Service
  • Real-world use cases
  • Functional requirements
  • Non-functional requirements
  • Client APIs needed
  • Estimates and calculations
  • System design
  • High-level system design
  • Core challenge.
  • Final high-level solution architecture
  • Requirements verification
  • Summary
  • Chapter 11: Designing a Service Like Twitter
  • Functional requirements
  • Non-functional requirements
  • Data model
  • Scale calculations
  • Exploring high-level design
  • Microservices architecture
  • Designing Tweet Service
  • Data storage
  • Tweet creation flow
  • Tweet retrieval flow
  • Caching
  • Designing User Service
  • Data storage
  • User registration flow
  • User authentication flow
  • Follow/unfollow flow
  • Retrieving followers/followees
  • Low-level design - Timeline Service
  • Data flow
  • Timeline retrieval flow
  • Push-based updates
  • Designing Search Service
  • Data flow and indexing
  • Search query processing
  • Relevance scoring and ranking
  • Additional considerations
  • Summary
  • Chapter 12: Designing a Service Like Instagram
  • Functional requirements
  • Non-functional requirements
  • Designing the data model
  • Scale calculations
  • High-level design
  • Components and modules in the high-level architecture
  • Low-level design
  • Designing the Photo Upload Service
  • News Feed Service
  • User Service
  • Additional considerations
  • Summary
  • Chapter 13: Designing a Service Like Google Docs
  • Functional requirements
  • Non-functional requirements
  • Data model
  • Relationships
  • Scale calculations
  • Assumptions
  • Storage requirements
  • Bandwidth considerations
  • Processing requirements
  • High-level design
  • Software components and modules of high-level design
  • Low-level design
  • Designing the document service
  • Designing the Collaboration Service
  • Designing the Access Control Service
  • Additional considerations and best practices
  • Summary
  • Chapter 14: Designing a Service Like Netflix
  • Functional requirements
  • Non-functional requirements
  • Designing the data model
  • Relationships
  • Scale calculations
  • Assumptions.
  • Storage estimation
  • Bandwidth estimation
  • Processing estimation
  • High-level design
  • Low-level system design
  • Video Service
  • Video upload and storage
  • Video encoding and transcoding
  • Video streaming
  • Caching and content delivery
  • User Service
  • User authentication and authorization
  • User profile management
  • Database and caching
  • Recommendation Service
  • The CDN
  • CDN architecture and content distribution
  • Request routing and video streaming
  • Adaptive bitrate streaming
  • Content security and DRM
  • Summary
  • Chapter 15: Tips for Interviewees
  • Tips for preparation for system design interviews
  • Understanding the fundamentals
  • Studying common system design patterns
  • Practicing designing systems
  • Learning from online resources
  • Honing your communication skills
  • Reviewing and reflecting
  • Tips for the interview session
  • Understanding the problem statement
  • Breaking down the problem
  • Key steps to follow
  • Communicating your solution effectively
  • Summary
  • Chapter 16: System Design Cheat Sheet
  • Which data store should we use for a use case?
  • Which data structures should we use for a use case?
  • Which components should we use for which use case?
  • What protocol should we use for which use case?
  • Which solution should we use for which core challenge?
  • Summary
  • Index.

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