madd86/awesome-system-design

Features

• Curated Learning Resources - Acts as a curated collection of high-quality documentation and educational materials for self-directed technical study.
• Reference Guides - Serves as a comprehensive reference guide that organizes complex technical topics for professional skill acquisition.
• System Design Interview Preparation - Provides curated educational materials for navigating system design interviews and mastering architectural theory.
• Awesome List - A community-curated directory that catalogs and links out to other open-source projects, rather than a standalone tool you run yourself.
• Distributed Systems Architecture - Provides a core educational curriculum on the principles and patterns of distributed systems.
• Technical Interview Preparation - Offers structured study materials and practice challenges for preparing for technical interviews and hiring assessments.
• Container Orchestrators - Covers platforms that automate the deployment, scaling, and management of containerized applications across clusters.
• Cluster and Service Orchestration - Provides comprehensive platforms for managing distributed system health, service discovery, and component orchestration.
• Message Queues - Covers infrastructure for asynchronous task buffering, message passing, and reliable event-driven workflow execution.
• Message Broker Infrastructure - Details core software and architectural patterns for routing, queuing, and persisting messages between decoupled system components.
• Message Brokers - Facilitates asynchronous data exchange through message queues to decouple service communication.
• Load Balancers - Explains systems that distribute network traffic across multiple servers to optimize resource use and ensure high availability.
• Distributed Data Management - Covers systems focused on the storage, mapping, and consistent replication of data across distributed environments.
• System Design Resources - Comprehensive resources for distributed computing and system design.
• Distributed Computing - Explains frameworks designed to execute large-scale data analytics and processing tasks across distributed computing clusters.
• Stream Processing - Covers architectures and frameworks designed for the continuous ingestion, transformation, and analysis of high-velocity data streams.
• Declarative Query Languages - Covers high-level query languages that allow data manipulation without specifying execution steps.
• Distributed Task Schedulers - Covers systems for orchestrating and distributing complex data processing workflows across computing clusters.
• File Storage Systems - Explains architectures for storing and retrieving data in hierarchical directory structures across distributed nodes.
• In-Memory Data Stores - Explains systems that store and manage transient application data directly in system memory for high-performance access.
• Relational Data Stores - Covers systems relying on relational databases for structured storage and complex query support.
• Wide-Column Stores - Explains NoSQL database systems designed for high-scale storage with flexible, dynamic column structures.
• Distributed Data Infrastructure - Provides guidance on systems and tools for managing data storage across distributed environments.
• Horizontal Scaling Tools - Covers patterns for scaling services by adding nodes dynamically to handle high-throughput workloads.
• Data Ingestion - Covers processes and services that receive, clean, and prepare raw data for entry into a storage system.
• File System Abstractions - Provides architectural abstractions that decouple high-level application logic from underlying storage state management.
• Web API Design Patterns - Teaches standardized request and response patterns for building robust network interfaces.
• Caching - Details systems that store frequently accessed data in temporary memory to reduce latency and improve application performance.
• Distributed Query Processing - Provides methods for executing and parallelizing data queries across multiple nodes in a distributed environment.
• Document Stores - Explains database systems that store, retrieve, and manage information as semi-structured document objects.
• Graph Querying - Covers languages and tools designed for traversing and querying connected data structures.
• Traffic Load Balancers - Covers tools for distributing network traffic across multiple service instances to ensure high availability.

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