Distributed Systems

Design a CQRS-based backend that scales read and write workloads independently using a transactional command model and asynchronously updated read models. Covers event/CDC pipelines, projection correctness, caching, and consistency trade-offs at high scale.

Design a horizontally scalable architecture by making compute stateless, partitioning stateful stores, and decoupling workloads with queues/streams. Focuses on hot partitions, fanout, caching, and consistency trade-offs while targeting low latency and 99.99% availability.

Learn how circuit breakers prevent cascading failures and keep services responsive during outages.

A complete study plan for system design interviews. Covers all 23 major design case studies from URL shorteners to distributed systems, with recommended study order and capacity estimation cheat sheets.

A centralized coordination service for distributed systems providing configuration management, leader election, distributed locking, and service discovery

Paxos is the foundational consensus algorithm that enables distributed systems to agree on values despite failures — the theoretical bedrock behind Google Chubby, Apache ZooKeeper, and every modern consensus protocol.

Spanner is Google's globally distributed database that provides externally consistent reads and writes — the first system to achieve global ACID transactions at scale using TrueTime and Paxos.

Comprehensive guide to Agentic AI Systems: Designing Reliable LLM Agent Architectures with Tool Use, Memory, and Guardrails for software engineers

Comprehensive guide to Agentic AI Systems: Designing LLM-Powered Workflows with Tool Use, Memory, and Guardrails for software engineers

Explore key patterns like circuit breakers, bulkheads, and saga orchestration that make distributed systems resilient and scalable.

Learn how to design a highly available, distributed caching system with consistent hashing, replication, and eviction policies.

Learn how to design a scalable URL shortening service with high availability, low latency, and analytics capabilities.

Strategies and patterns for managing data consistency across distributed microservices, including event sourcing and SAGA patterns.

Distributed stream processing framework for real-time analytics, event-driven applications, and complex event processing

Distributed streaming platform designed for high-throughput, real-time data pipelines and event-driven architectures

Real-time computation system for processing unbounded streams of data with guaranteed message processing

Google's Distributed Storage System for Structured Data.

Understanding consensus algorithms that can tolerate Byzantine (malicious) failures in distributed systems

Understanding the fundamental trade-offs in distributed systems design and implementation

Understanding fault tolerance and failure handling in distributed systems

Understanding data distribution and load balancing in distributed systems

Separating read and write operations for scalable and maintainable distributed systems

Coordinating access to shared resources across distributed systems

Amazon's distributed key-value storage system designed for high availability and eventual consistency.

Distributed search and analytics engine built on Apache Lucene for real-time search, logging, and data analytics

Retry strategy that progressively increases delay between retry attempts to handle transient failures and prevent system overload

Google's scalable distributed file system designed for large distributed data-intensive applications.

Understanding epidemic-style information dissemination protocols for scalable and fault-tolerant distributed systems

Scaling strategy that increases system capacity by adding more machines or instances rather than upgrading existing hardware

Ensuring operations can be safely retried without unintended side effects

LinkedIn's distributed streaming platform designed for high-throughput, low-latency data streaming.

Understanding how distributed systems select a leader to coordinate operations and maintain consistency

Google's simplified data processing on large clusters.

Concurrency control mechanism that assumes conflicts are rare and handles them when they occur, using version numbers or timestamps to detect concurrent modifications

Extension of CAP theorem describing trade-offs in distributed systems during both network partitions and normal operation

Messaging pattern for decoupled communication between distributed systems

Understanding quorum-based consensus mechanisms for ensuring consistency and availability in distributed systems

Raft protocol explained for interviews: leader election + log replication. RequestVote/AppendEntries, Raft vs Paxos, etcd/Consul use. Read now.

Global vs local secondary indexes in distributed systems

Understanding techniques to prevent split-brain scenarios in distributed systems where multiple nodes believe they are the leader

Explore the most influential Apache Software Foundation projects used in modern distributed systems and data processing