Distributed Systems

In high-concurrency microservices architectures, preventing race conditions when multiple stateless worker instances access shared resources requires Distribute…

System design interviews evaluate a candidate's ability to architect scalable, resilient, and cost-effective distributed systems under real-world constraints. S…

An order-ingestion API writes to an in-memory queue, a worker pool drains it, and a payment provider on the other end gets slow. The queue keeps accepting every…

A shopping cart write to cart-77 needs to land on enough replicas that a later read is guaranteed to see it — but "enough" is a number you choose, and the numbe…

A 4-node session cache scales to 5 nodes to handle more traffic. With hash(key) % N, that single node addition changes almost every key's target node, and the c…

A user changes their display name, refreshes the page a second later from a phone on a different network, and sees the old name. Nothing crashed. No request fai…

The CAP theorem states that when a distributed system is partitioned, it cannot guarantee both linearizable consistency and availability for every request. Cons…

This guide is for backend engineers who know HTTP and database transactions but need to decide where six microservice patterns fit. By the end, you can trace on…

A trip booking needs a flight, a hotel room, and a card charge to either all succeed or all unwind — but each lives in a different service with its own database…

A signup service inserts a new User row, then calls the broker to publish UserRegistered so the welcome-email and loyalty services can react. The database commi…

An invoicing consumer reads InvoiceApproved from a queue, calls the payment processor to charge the card, and commits its offset. The broker redelivers the mess…

A team says "we need to shard the database" when the actual measured problem is a 200GB events table that scans slowly, or "let's add replication" when what the…

A consumer service scales from two instances to eight expecting throughput to climb accordingly — instead, six of the eight sit idle while the same two partitio…

Two background workers pick up the same financial payout job at the exact same millisecond. Without mutual exclusion across separate servers, both workers proce…

Building fault-tolerant distributed databases requires keeping multiple server nodes synchronized on a sequence of state machine operations. Before Raft, Paxos …

In microservices architectures, cascading failures present a constant operational threat. If a downstream payment gateway or third-party inventory API experienc…

Single-region database deployments create single points of failure (SPOFs). If an entire cloud availability zone or geographic region experiences a fiber cut, p…

Executing long-running computations — such as generating PDF invoices, processing video uploads, or sending transactional email batches — inside synchronous web…

Transitioning from monolithic database architectures to distributed microservices breaks traditional ACID database transactions. When an e-commerce order workfl…

In distributed storage systems, keeping data consistent across multiple independent server nodes in the presence of network partitions, hardware crashes, and me…

A distributed lock feels like it should be enough: acquire it, do your write, release it, and only one client at a time gets to touch the resource. It works rig…