DesignRounds system design handbook Free system design guides with diagrams, from the basics to distributed systems. https://designrounds.in/learn 2026-10-24T00:00:00Z DesignRounds Scalability: Vertical vs Horizontal Scalinghttps://designrounds.in/learn/scalability2026-10-24T00:00:00ZWhat scalability means, vertical vs horizontal scaling, stateless services, and how real systems grow from one server to thousands. Latency vs Throughputhttps://designrounds.in/learn/latency-vs-throughput2026-10-24T00:00:00ZLatency vs throughput explained: percentiles (p50, p99), tail latency, Little's Law, and how to reason about both in system design. Availability, SLAs, SLOs and the Nineshttps://designrounds.in/learn/availability2026-10-24T00:00:00ZAvailability explained: the nines, SLA vs SLO vs SLI, error budgets, and how redundancy and failover raise uptime in real systems. Back-of-the-Envelope Estimationhttps://designrounds.in/learn/back-of-the-envelope-estimation2026-10-24T00:00:00ZHow to do back-of-the-envelope estimation for system design: QPS, storage, bandwidth, latency numbers and powers of two, with worked examples. Data Modeling for System Design Interviews: Entities to Partition Keyshttps://designrounds.in/learn/data-modeling-for-system-design2026-10-24T00:00:00ZHow to model data in a system design interview: entities, relationships, access patterns, choosing SQL, document or wide-column stores, keys, indexes and partitioning. CAP Theorem and PACELChttps://designrounds.in/learn/cap-theorem2026-10-24T00:00:00ZThe CAP theorem explained correctly: what partitions force you to choose, CP vs AP systems, and PACELC's latency vs consistency trade-off. Consistency Models: Strong, Eventual and Causalhttps://designrounds.in/learn/consistency-models2026-10-24T00:00:00ZConsistency models explained: linearizability, sequential, causal, read-your-writes and eventual consistency, with examples of where each fits. ACID vs BASEhttps://designrounds.in/learn/acid-vs-base2026-10-24T00:00:00ZACID vs BASE explained: atomicity, consistency, isolation, durability, and the basically-available, eventually-consistent alternative. How DNS Workshttps://designrounds.in/learn/dns2026-10-24T00:00:00ZHow DNS resolution works step by step: resolvers, root and TLD servers, record types, TTLs and caching, and DNS-based load balancing. HTTP/1.1 vs HTTP/2 vs HTTP/3https://designrounds.in/learn/http2026-10-24T00:00:00ZHTTP/1.1, HTTP/2 and HTTP/3 compared: connections, multiplexing, head-of-line blocking, QUIC, TLS, and what each means for performance. TCP vs UDPhttps://designrounds.in/learn/tcp-vs-udp2026-10-24T00:00:00ZTCP vs UDP explained: the three-way handshake, reliability, ordering and congestion control, and when to choose UDP for real-time traffic. REST vs gRPC vs GraphQLhttps://designrounds.in/learn/api-styles2026-10-24T00:00:00ZREST vs gRPC vs GraphQL compared: payloads, contracts, performance, streaming and caching, and which API style fits which system. WebSockets vs Server-Sent Events vs Long Pollinghttps://designrounds.in/learn/real-time-communication2026-10-24T00:00:00ZWebSockets vs SSE vs long polling: how each pushes data to clients, connection costs at scale, and how chat and live feeds use them. Load Balancing: L4 vs L7 and Algorithmshttps://designrounds.in/learn/load-balancing2026-10-24T00:00:00ZLoad balancing explained: L4 vs L7 load balancers, round robin, least connections, consistent hashing, health checks and sticky sessions. API Gateway: Features, Examples and Reverse Proxy vs Gatewayhttps://designrounds.in/learn/api-gateway2026-10-24T00:00:00ZWhat an API gateway does: routing, auth, rate limiting, protocol translation, transformation and aggregation, popular gateways, and reverse proxy vs gateway. CDN vs Application Cache: How Content Delivery Networks Workhttps://designrounds.in/learn/cdn2026-10-24T00:00:00ZHow a CDN works, what it caches well and what it can't, data-level caching in Redis, origin shielding, and a framework for deciding what goes where. Consistent Hashinghttps://designrounds.in/learn/consistent-hashing2026-10-24T00:00:00ZConsistent hashing explained with diagrams: the hash ring, virtual nodes, minimal data movement, and its use in caches and databases. Transactions and Isolation Levelshttps://designrounds.in/learn/transactions-isolation-levels2026-10-24T00:00:00ZTransaction isolation levels explained: dirty reads, non-repeatable reads, phantoms, write skew, MVCC, snapshot isolation and serializability. Normalization vs Denormalizationhttps://designrounds.in/learn/normalization-denormalization2026-10-24T00:00:00ZNormalization vs denormalization: normal forms, joins vs duplication, read vs write trade-offs, and how to model data for access patterns. Time-Series Databaseshttps://designrounds.in/learn/time-series-databases2026-10-24T00:00:00ZTime-series databases explained: append-heavy writes, compression, downsampling, retention and how metrics and IoT systems store data. Full-Text Search and the Inverted Indexhttps://designrounds.in/learn/search-and-inverted-index2026-10-24T00:00:00ZHow full-text search works: inverted indexes, tokenization, relevance ranking with BM25, and keeping a search index in sync with a database. Object Storage and Blob Storeshttps://designrounds.in/learn/object-storage2026-10-24T00:00:00ZObject storage explained: buckets, keys and metadata, durability, presigned URLs, multipart uploads, and storing media in system design. Geospatial Indexing: Geohash, Quadtrees and S2https://designrounds.in/learn/geospatial-indexing2026-10-24T00:00:00ZGeospatial indexing explained: geohash, quadtrees and S2 cells, nearby search, and how ride-hailing and maps find what is close. Caching: How It Works, Where It Lives and Why It Mattershttps://designrounds.in/learn/caching2026-10-24T00:00:00ZCaching explained: the speed gap, power laws, time-bounded copies, hit rate math, and the four caching layers from browser and CDN to Redis and the database. Cache-Aside vs Read-Through vs Write-Through vs Write-Behindhttps://designrounds.in/learn/cache-strategies2026-10-24T00:00:00ZCaching strategies compared with labs: cache-aside, read-through, write-through, write-behind and write-around, consistency, data loss and pollution. Cache Eviction Policies: LRU vs LFU and Sizing a Cachehttps://designrounds.in/learn/cache-eviction2026-10-24T00:00:00ZCache eviction explained: LRU, LFU, Redis approximations, choosing a policy, memory math for sizing a cache, and monitoring evictions and hit rate. Cache Invalidation: TTLs, Explicit Invalidation and Stale-While-Revalidatehttps://designrounds.in/learn/cache-invalidation2026-10-24T00:00:00ZHow to keep cached data fresh: choosing TTLs, explicit and event-driven invalidation, TTL as a safety net, stale-while-revalidate and TTL jitter. Message Queueshttps://designrounds.in/learn/message-queues2026-10-24T00:00:00ZMessage queues explained: producers, consumers, acknowledgements, visibility timeouts, dead-letter queues, and when to make work async. Publish-Subscribe Messaginghttps://designrounds.in/learn/pub-sub2026-10-24T00:00:00ZPublish-subscribe explained: topics, fan-out to many subscribers, push vs pull delivery, and how pub/sub differs from a work queue. Event Streaming and Kafka: Log-Based Message Brokershttps://designrounds.in/learn/event-streaming-kafka2026-10-24T00:00:00ZHow Kafka and log-based brokers work: partitions, offsets, consumer groups, retention, ordering guarantees and replay. Delivery Guarantees: At-Most-Once, At-Least-Once and Exactly-Oncehttps://designrounds.in/learn/delivery-semantics2026-10-24T00:00:00ZMessage delivery semantics explained: at-most-once, at-least-once and effectively-once processing, duplicates, and how to handle them. Idempotency and Idempotency Keyshttps://designrounds.in/learn/idempotency2026-10-24T00:00:00ZIdempotency in APIs and consumers: idempotency keys, dedup tables, safe retries for payments, and designing idempotent operations. Backpressure and Flow Controlhttps://designrounds.in/learn/backpressure2026-10-24T00:00:00ZBackpressure explained: bounded queues, flow control, dropping vs blocking vs buffering, and keeping fast producers from sinking slow consumers. CQRS and Event Sourcing: Separating Reads from Writeshttps://designrounds.in/learn/event-sourcing-cqrs2026-10-24T00:00:00ZCQRS explained with real examples (MySQL + Elasticsearch, DynamoDB notifications), lightweight CQRS, cloud implementations, and event sourcing. Transactional Outbox and Change Data Capturehttps://designrounds.in/learn/outbox-pattern2026-10-24T00:00:00ZThe transactional outbox pattern and change data capture: avoiding dual writes, publishing events reliably, and Debezium-style CDC. The Saga Pattern for Distributed Transactionshttps://designrounds.in/learn/saga-pattern2026-10-24T00:00:00ZThe saga pattern explained: orchestration vs choreography, compensating actions, and keeping data consistent across microservices. Two-Phase Commit (2PC)https://designrounds.in/learn/two-phase-commit2026-10-24T00:00:00ZTwo-phase commit explained: prepare and commit phases, the coordinator, blocking failures, and why most microservices prefer sagas. Consensus Algorithms: Raft and Paxoshttps://designrounds.in/learn/consensus2026-10-24T00:00:00ZConsensus explained through Raft: leader election, log replication, majorities and terms, plus where Paxos, etcd and ZooKeeper fit. Leader Electionhttps://designrounds.in/learn/leader-election2026-10-24T00:00:00ZLeader election in distributed systems: leases, heartbeats, split brain, fencing, and electing a leader with etcd or ZooKeeper. Distributed Locks and Fencing Tokenshttps://designrounds.in/learn/distributed-locks2026-10-24T00:00:00ZDistributed locks explained: lease-based locks, why process pauses break them, fencing tokens, and when to avoid locking entirely. Time, Clocks and Ordering: Lamport and Vector Clockshttps://designrounds.in/learn/clocks-and-ordering2026-10-24T00:00:00ZOrdering events without a global clock: clock skew, Lamport timestamps, vector clocks, hybrid logical clocks and TrueTime. Gossip Protocols and Failure Detectionhttps://designrounds.in/learn/gossip-protocol2026-10-24T00:00:00ZGossip protocols explained: epidemic dissemination, membership, phi-accrual failure detection, and how Cassandra and Consul use gossip. Bloom Filters, HyperLogLog and Count-Min Sketchhttps://designrounds.in/learn/probabilistic-data-structures2026-10-24T00:00:00ZProbabilistic data structures explained: Bloom filters, HyperLogLog and count-min sketch, their error rates, and real system uses. Rate Limiting Algorithmshttps://designrounds.in/learn/rate-limiting2026-10-24T00:00:00ZRate limiting algorithms explained: token bucket, leaky bucket, fixed and sliding windows, and building a distributed rate limiter. Circuit Breakers and Bulkheadshttps://designrounds.in/learn/circuit-breaker2026-10-24T00:00:00ZThe circuit breaker pattern explained: closed, open and half-open states, bulkheads, and stopping one slow dependency from taking down everything. Timeouts, Retries and Exponential Backoffhttps://designrounds.in/learn/retries-and-timeouts2026-10-24T00:00:00ZTimeouts and retries done right: exponential backoff with jitter, retry budgets, deadlines, and avoiding retry storms. Load Shedding and Graceful Degradationhttps://designrounds.in/learn/load-shedding2026-10-24T00:00:00ZLoad shedding and graceful degradation: rejecting work early, prioritising traffic, and keeping core features alive under overload. Disaster Recovery: RPO, RTO and Multi-Regionhttps://designrounds.in/learn/disaster-recovery2026-10-24T00:00:00ZDisaster recovery explained: RPO and RTO, backups, warm and hot standbys, active-active multi-region, and testing failover. Health Checks and Failoverhttps://designrounds.in/learn/health-checks-failover2026-10-24T00:00:00ZHealth checks and failover: liveness vs readiness, deep vs shallow checks, failure detection, and automatic failover without flapping. Monolith vs Microserviceshttps://designrounds.in/learn/monolith-vs-microservices2026-10-24T00:00:00ZMonolith vs microservices: deployment, team ownership, data boundaries and operational cost, plus the modular monolith in between. Service Discoveryhttps://designrounds.in/learn/service-discovery2026-10-24T00:00:00ZService discovery explained: client-side vs server-side discovery, service registries, DNS-based discovery and Kubernetes services. Service Mesh and the Sidecar Patternhttps://designrounds.in/learn/service-mesh2026-10-24T00:00:00ZWhat a service mesh does: sidecar proxies, mTLS, retries, traffic shifting and observability, and when it is worth the complexity. API Pagination: Offset vs Cursorhttps://designrounds.in/learn/pagination2026-10-24T00:00:00ZAPI pagination explained: offset vs cursor (keyset) pagination, stable ordering, performance on large tables, and opaque cursors. Webhookshttps://designrounds.in/learn/webhooks2026-10-24T00:00:00ZHow webhooks work: event delivery over HTTP, signatures, retries and idempotency, ordering, and building a reliable webhook system. Data Engineering Architecture: From Sources to Trusted Data Productshttps://designrounds.in/learn/data-engineering-architecture2026-10-24T00:00:00ZDesign an end-to-end data platform: ingestion, lake and warehouse layers, batch and streaming pipelines, data quality, governance, and serving. Batch vs Stream Processinghttps://designrounds.in/learn/batch-vs-stream-processing2026-10-24T00:00:00ZBatch vs stream processing: MapReduce and Spark vs Flink and Kafka Streams, windows, event time, late data, and lambda vs kappa. Dimensional Modeling Interview Questions and How to Answer Themhttps://designrounds.in/learn/dimensional-modeling-interview-guide2026-10-24T00:00:00ZHow to answer dimensional data modeling interview questions: a step-by-step method, what interviewers probe, common traps, and model answers to frequent questions. Dimensional Modeling: Star Schema, Snowflake Schema and Factshttps://designrounds.in/learn/dimensional-modeling2026-10-24T00:00:00ZDimensional data modeling explained: fact and dimension tables, grain, star vs snowflake schemas, surrogate keys and designing a warehouse model. The Four-Step Dimensional Design Process: Process, Grain, Dimensions, Factshttps://designrounds.in/learn/four-step-dimensional-design2026-10-24T00:00:00ZKimball's four-step dimensional design process explained: choose the business process, declare the grain, identify dimensions and facts, with a worked example. Fact Table Types: Transaction, Periodic and Accumulating Snapshotshttps://designrounds.in/learn/fact-table-types2026-10-24T00:00:00ZFact table types explained: transaction, periodic snapshot, accumulating snapshot and factless facts, additive vs semi-additive measures, and when to use each. Dimension Table Techniques: Surrogate Keys, Role-Playing, Junk and Morehttps://designrounds.in/learn/dimension-table-techniques2026-10-24T00:00:00ZDimension table design techniques: surrogate and durable keys, date dimensions, role-playing, degenerate, junk, mini and audit dimensions, and late-arriving data. Slowly Changing Dimensions: SCD Type 1, 2 and 3 Explainedhttps://designrounds.in/learn/slowly-changing-dimensions2026-10-24T00:00:00ZSlowly changing dimensions explained: SCD Type 1, 2 and 3, effective dates and current flags, surrogate keys, and loading SCD2 tables with MERGE. Hierarchies and Bridge Tables in Dimensional Modelinghttps://designrounds.in/learn/hierarchies-and-bridge-tables2026-10-24T00:00:00ZModeling hierarchies and many-to-many relationships in a warehouse: fixed and ragged hierarchies, flattening, bridge tables, weighting factors and double counting. Conformed Dimensions and the Data Warehouse Bus Matrixhttps://designrounds.in/learn/conformed-dimensions-bus-matrix2026-10-24T00:00:00ZConformed dimensions and facts, the enterprise bus matrix, shrunken dimensions and drilling across: how separate fact tables stay consistent and combinable. Dimensional Modeling Example: E-commerce Orders, Returns and Inventoryhttps://designrounds.in/learn/dimensional-model-example-ecommerce2026-10-24T00:00:00ZA complete dimensional model for an online store: bus matrix, order-line and returns facts, a shipment accumulating snapshot, daily inventory, and the SQL it answers. Dimensional Modeling Example: Ride-Hailing Trips and Drivershttps://designrounds.in/learn/dimensional-model-example-ride-hailing2026-10-24T00:00:00ZA complete dimensional model for a ride-hailing app like Uber: trip facts, a trip lifecycle snapshot, driver activity, role-playing locations, surge and shared rides. Machine Learning System Architecture: Data to Production Modelshttps://designrounds.in/learn/machine-learning-system-architecture2026-10-24T00:00:00ZHow production ML systems connect data pipelines, training, feature stores, model registries, deployment, online serving, and drift monitoring. AI Application Architecture: Retrieval, Tools and Guardrailshttps://designrounds.in/learn/ai-application-architecture2026-10-24T00:00:00ZDesign an AI application around foundation models: request orchestration, retrieval-augmented generation, tools, safety, evaluation, and cost controls. Deployment Strategies: Blue-Green, Canary and Rollinghttps://designrounds.in/learn/deployment-strategies2026-10-24T00:00:00ZDeployment strategies compared: rolling, blue-green and canary releases, feature flags, database migrations and fast rollback. Observability: Logs, Metrics and Traceshttps://designrounds.in/learn/observability2026-10-24T00:00:00ZObservability explained: logs, metrics and distributed traces, RED and USE methods, cardinality, and alerting on symptoms. Autoscalinghttps://designrounds.in/learn/autoscaling2026-10-24T00:00:00ZAutoscaling explained: horizontal and vertical scaling, target metrics, scale-up lag, cooldowns, predictive scaling and warm pools. API Authentication: API Keys vs Sessions vs JWThttps://designrounds.in/learn/authentication-authorization2026-10-24T00:00:00ZAPI authentication compared: API keys for apps, server-side sessions, self-contained JWTs, revocation and refresh tokens, and Sign in with Google (OIDC). Encryption in Transit and at Resthttps://designrounds.in/learn/encryption2026-10-24T00:00:00ZEncryption in system design: TLS in transit, encryption at rest, envelope encryption with a KMS, key rotation and hashing passwords. Data Engineering Roadmap 2026: From Pipelines to Interviewshttps://designrounds.in/learn/data-engineering-roadmap2026-10-21T00:00:00ZA step-by-step data engineering roadmap for 2026: Spark batch, Kafka streaming, data modeling, lakehouse storage, data quality, backfills and interviews. Serverless Architecturehttps://designrounds.in/learn/serverless2026-10-21T00:00:00ZServerless architecture explained: functions as a service, cold starts, scaling to zero, limits, pricing, and the workloads it suits. Data Engineering System Design Interview: Framework and Examplehttps://designrounds.in/learn/data-engineering-system-design-interview2026-10-21T00:00:00ZHow to answer data engineering system design interview questions: a six-step framework, requirement questions, back-of-the-envelope math and a worked example. Data Engineering Design Patterns: Lambda, Kappa, Mesh, Lakehousehttps://designrounds.in/learn/data-engineering-design-patterns2026-10-21T00:00:00ZSeven data architecture patterns with real examples: Lambda and Kappa architecture, event-driven and serverless pipelines, CQRS, data mesh and lakehouse. What Is a Data Lakehouse? Lakehouse Architecture Explainedhttps://designrounds.in/learn/lakehouse-architecture2026-10-21T00:00:00ZData lakehouse architecture explained: lakehouse vs data lake vs warehouse, why plain Parquet falls short, Delta Lake and Iceberg, catalogs and query engines. What Is Data Mesh? Principles, Architecture and Exampleshttps://designrounds.in/learn/data-mesh2026-10-21T00:00:00ZWhat is data mesh? Its four principles, how domains share data products without copying, federated governance, data mesh vs lakehouse, and when to use it. Partitioning vs Bucketing vs Liquid Clustering, Explainedhttps://designrounds.in/learn/data-layout-optimization2026-10-21T00:00:00ZPartitioning vs bucketing vs liquid clustering and Z-ordering for Spark and lakehouse tables, and fixing the small file problem with compaction. Best System Design Interview Prep Resources and Tools (2026)https://designrounds.in/learn/best-system-design-interview-resources2026-10-21T00:00:00ZThe best system design interview resources compared: books, guides, AI practice platforms and mock interviews, what each costs and which to pick. Design a Real-Time Analytics Pipeline (Food Delivery Example)https://designrounds.in/learn/design-food-delivery-analytics2026-10-21T00:00:00ZData engineering system design example: a real-time analytics pipeline for a food delivery app like Uber Eats or Swiggy, using Kafka, Spark and Redis. Core System Design Challenges and How to Scale a Systemhttps://designrounds.in/learn/core-design-challenges2026-10-20T00:00:00ZThe four recurring challenges of web-scale systems (users, data, speed, consistency) and the scaling toolkit that solves them, with diagrams and numbers. Non-Functional Requirements: Availability, Scalability, Latency, Consistencyhttps://designrounds.in/learn/non-functional-requirements2026-10-20T00:00:00ZNon-functional requirements in system design: availability, scalability, latency and consistency, how to state them, and the patterns that deliver each one. QPS, Load Parameters and Resource Estimationhttps://designrounds.in/learn/measuring-load-qps2026-10-20T00:00:00ZHow to describe load: DAU to QPS, read/write ratio, connections, throughput vs RPS, latency vs response time, what each QPS tier needs, with real examples. SQL vs NoSQL vs Object Storage: How to Choose Storagehttps://designrounds.in/learn/sql-vs-nosql2026-10-20T00:00:00ZThe three kinds of storage (SQL, NoSQL and blob storage) and how to choose: data model, transactions, consistency, query needs, "just use Postgres" and hybrid designs. Relational (SQL) Databases: Tables, Keys and ACID Transactionshttps://designrounds.in/learn/relational-databases2026-10-20T00:00:00ZHow relational databases work: schemas, primary and foreign keys, joins, ACID transactions and the WAL, where SQL fits, popular engines and how they scale. NoSQL Databases: Key-Value, Document, Wide-Column and Graphhttps://designrounds.in/learn/nosql-database-types2026-10-20T00:00:00ZWhy NoSQL exists (schema rigidity, horizontal scaling), the four families with examples, when to use NoSQL and what it gives up compared with SQL. Key-Value Databases: Redis, DynamoDB and When to Use Themhttps://designrounds.in/learn/key-value-databases2026-10-20T00:00:00ZKey-value databases explained: the Dynamo idea, get/put/delete by key, why lookups are fast and scaling is easy, key design, and real uses at Dropbox, Snap and Disney+. Document Databases: MongoDB, JSON Documents and When to Use Themhttps://designrounds.in/learn/document-databases2026-10-20T00:00:00ZDocument databases explained: the ORM problem, self-contained JSON documents, embedding vs referencing, where they fit, where they don't, and MongoDB basics. OLTP vs OLAP: Transactional vs Analytical Databaseshttps://designrounds.in/learn/oltp-vs-olap2026-10-20T00:00:00ZOLTP vs OLAP explained: small key lookups vs huge scans, why warehouses use column storage and compression, star schemas, and how ETL connects the two. Database Indexing and Storage Engines: Hash Indexes, B-Trees and LSM Treeshttps://designrounds.in/learn/database-indexing2026-10-20T00:00:00ZHow databases store and find data: sequential vs random I/O, hash indexes, B-tree search and node splits, LSM trees, composite and covering indexes, and when an index hurts. LSM Trees and SSTables: How Write-Heavy Databases Workhttps://designrounds.in/learn/lsm-trees-sstables2026-10-20T00:00:00ZLSM trees and SSTables explained: sparse indexes, memtables and the WAL, leveled compaction, tombstones, Bloom-filtered reads and write amplification, with runnable code. How to Scale a Database: Replication, Caching and Shardinghttps://designrounds.in/learn/scaling-databases2026-10-20T00:00:00ZHow to scale a database step by step: vertical vs horizontal, replicas and caching for reads, partitioning for writes, and combining partitions with replicas. Database Replication: Leader-Follower, Multi-Leader and Leaderlesshttps://designrounds.in/learn/replication2026-10-20T00:00:00ZDatabase replication explained: single-leader, multi-leader and leaderless designs, replication logs, sync vs async and semi-sync, failover, and a Redis hands-on. Change Data Capture (CDC): Syncing Search, Caches and Warehouseshttps://designrounds.in/learn/change-data-capture2026-10-20T00:00:00ZChange data capture explained: the dual-write problem, log-based CDC with Debezium and Kafka, trigger and polling alternatives, use cases and trade-offs. Database Sharding and Partitioning: Keys, Indexes and Rebalancinghttps://designrounds.in/learn/sharding2026-10-20T00:00:00ZSharding explained: range vs hash vs composite keys, choosing a shard key, hot spots and salting, local vs global secondary indexes, rebalancing and a MySQL demo. Database Optimization: Indexes, Hot/Cold Data, Denormalization and Viewshttps://designrounds.in/learn/database-optimization2026-10-20T00:00:00ZPractical database optimization: choosing indexes, EXPLAIN, separating hot and cold data, denormalization and materialized views, with the trade-offs of each. Cache Key Design: Namespaces, Versioning and Key Sizehttps://designrounds.in/learn/cache-key-design2026-10-20T00:00:00ZHow to design cache keys: namespaced and versioned keys, key size, common key patterns, hash tags, and avoiding collisions and unbounded key spaces. Cache Consistency: Dual Writes, Races and Delete vs Updatehttps://designrounds.in/learn/cache-consistency2026-10-20T00:00:00ZWhy caches go stale: the dual-write problem, read/write races, why delete beats update, delayed double delete, version stamps and a staleness spectrum. Distributed Caching: Sharding, Redis Cluster and Hot Keyshttps://designrounds.in/learn/distributed-caching2026-10-20T00:00:00ZSharding a cache across nodes: modulo vs consistent hashing, Redis Cluster hash slots and hash tags, client vs proxy routing, and hot key fixes. Cache High Availability: Replicas, Sentinel and Redis Clusterhttps://designrounds.in/learn/cache-high-availability2026-10-20T00:00:00ZKeeping a cache up when nodes fail: primary-replica replication, Redis Sentinel failover, split brain, Redis Cluster HA, and graceful degradation. Cache Warming and Cold Startshttps://designrounds.in/learn/cache-warming2026-10-20T00:00:00ZWhy a cold cache can take down a database, when cold starts happen, warm-up strategies (gradual, ramped, pre-loaded) and protecting the database. Cache Penetration, Avalanche and Stampede (Thundering Herd)https://designrounds.in/learn/cache-failure-modes2026-10-20T00:00:00ZThe three cache failure modes and their defenses: Bloom filters and null caching, TTL jitter, request coalescing, stale-while-revalidate, with labs. Cache Security and Monitoring: What Not to Cache, What to Measurehttps://designrounds.in/learn/cache-security-and-monitoring2026-10-20T00:00:00ZCache security risks (auth leakage, cached credentials, PII) and the four metrics to monitor: hit rate, latency, evictions and memory, with alert thresholds. How to Discuss Caching in a System Design Interviewhttps://designrounds.in/learn/caching-in-interviews2026-10-20T00:00:00ZAn eight-point checklist for caching in system design interviews, worked through an e-commerce product page: what to say, common mistakes and what interviewers want. The Cache-First Pattern: Caching at 100M Usershttps://designrounds.in/learn/cache-first-pattern2026-10-20T00:00:00ZWhy caching becomes mandatory at large scale: protection, speed and cost, what to cache, which strategy, when not to cache, and how to present it. Unique ID Generation: Snowflake, UUID, ULID and Custom IDshttps://designrounds.in/learn/unique-id-generation2026-10-20T00:00:00ZGenerating unique IDs in distributed systems: why auto-increment breaks, Snowflake bit layout and code, UUID vs ULID vs partitioned sequences, and Stripe-style IDs. Fallbacks and Graceful Degradationhttps://designrounds.in/learn/fallbacks-graceful-degradation2026-10-20T00:00:00ZFallback strategies when a dependency fails: cached responses, safe defaults, graceful degradation and placeholders, and how they pair with circuit breakers. Synchronous vs Asynchronous Communication Between Microserviceshttps://designrounds.in/learn/sync-vs-async-communication2026-10-20T00:00:00ZHow microservices communicate: blocking request/response vs messages and events, cascading failures, thread pool exhaustion, and when to use each. Database per Microservicehttps://designrounds.in/learn/database-per-service2026-10-20T00:00:00ZThe database-per-service pattern: each microservice owns its data behind an API, the benefits, the consistency and cross-service query costs, and when not to use it. Stateless vs Stateful Servers: Sessions, Sticky Sessions and Shared Statehttps://designrounds.in/learn/stateless-vs-stateful2026-10-20T00:00:00ZWhy scalable web servers are stateless: the lost shopping cart, sticky sessions, client-side storage options and shared session stores like Redis. Dataflow Patterns: Database, Service Calls, Message Queues, Push vs Pullhttps://designrounds.in/learn/dataflow-patterns2026-10-20T00:00:00ZHow data moves between services: a shared database, synchronous calls or message queues, and push vs pull delivery with long polling and server-sent events. Fan-Out on Write vs Fan-Out on Read (and Fan-Out/Fan-In)https://designrounds.in/learn/fan-out2026-10-20T00:00:00ZFan-out on write vs fan-out on read for timelines, Twitter's hybrid for celebrities, and the general fan-out/fan-in pattern for search, feeds and notifications. The Pre-Computing Pattern: Compute on Write, Not on Readhttps://designrounds.in/learn/precomputation-pattern2026-10-20T00:00:00ZPre-computing explained: move expensive, repeated queries to write time with materialized views, denormalization, indexes and fan-out; trade-offs and hybrids. Two-Stage Processing: Fast Filter, Then Precise Rankinghttps://designrounds.in/learn/two-stage-processing2026-10-20T00:00:00ZThe two-stage pattern behind search, recommendations and fraud detection: a cheap high-recall filter, then expensive ranking on a small candidate set. Backfills and Reprocessing in Data Pipelineshttps://designrounds.in/learn/backfill-and-reprocessing2026-10-20T00:00:00ZHow to reprocess historical data safely: full reload, incremental backfill and parallel versioning, idempotent writes, atomic partitions and designing for replays. Data Pipeline Error Handling: Dead-Letter Queues, Retries and Monitoringhttps://designrounds.in/learn/pipeline-error-handling2026-10-20T00:00:00ZHandling failures in data pipelines: dead-letter queues, failure categories, retries with backoff and jitter, circuit breakers and the metrics to monitor. Materialized Views and Pre-Aggregationhttps://designrounds.in/learn/materialized-views2026-10-20T00:00:00ZMaterialized views explained: compute on write instead of read, a streaming page-views example, dimension explosion, late events and the 80/20 two-tier approach. Real-Time Analytics Architecture: Stream to Cache, TSDB and Hot/Coldhttps://designrounds.in/learn/real-time-analytics-architecture2026-10-20T00:00:00ZThree real-time analytics architectures (stream to cache, time-series database, hybrid hot and cold), how to choose and evolve, and handling late data and cardinality. MapReduce and Unix Pipelines: How Batch Processing Scaleshttps://designrounds.in/learn/mapreduce2026-10-20T00:00:00ZFrom Unix pipelines to MapReduce: map, shuffle and reduce with word count, why the shuffle dominates, combiners, fault tolerance and multi-stage limits. Distributed File Systems: How HDFS Workshttps://designrounds.in/learn/distributed-file-systems2026-10-20T00:00:00ZHDFS explained: 128 MB blocks and 3× replication, NameNode vs DataNodes, read and pipelined write paths, failover, rack awareness and data locality. What Is Stream Processing? Unbounded Data, Brokers and Statehttps://designrounds.in/learn/stream-processing2026-10-20T00:00:00ZStream processing explained: bounded vs unbounded data, Kafka as the input layer, the read-process-write loop, state, and when streaming beats batch. Stream Processing Frameworks: Flink, Kafka Streams, Spark and Beamhttps://designrounds.in/learn/stream-processing-frameworks2026-10-20T00:00:00ZWhat stream frameworks provide, Flink vs Kafka Streams deployment, unified batch and stream processing in Flink, Spark Structured Streaming and Beam, and how to choose. Lambda vs Kappa Architecturehttps://designrounds.in/learn/lambda-vs-kappa-architecture2026-10-20T00:00:00ZLambda (batch + speed + serving layers) vs Kappa (one stream pipeline, reprocess by replay): worked examples, maintenance costs and how to choose. Authorization: RBAC vs ABAC vs OAuth Scopeshttps://designrounds.in/learn/authorization-rbac-abac-oauth2026-10-20T00:00:00ZAuthorization models explained: role-based (RBAC), attribute-based (ABAC), OAuth scopes, ReBAC and ACLs, with policy code and how to choose and combine them. The System Design Template: Write to a Queue, Read from a Cachehttps://designrounds.in/learn/system-design-template2026-10-20T00:00:00ZThe master system design template: stateless services, a queue on the write path, a cache on the read path, and how it solves Twitter and WhatsApp. Problem Decomposition: Verbs, Nouns and Adjectives in System Designhttps://designrounds.in/learn/problem-decomposition-framework2026-10-20T00:00:00ZTurn a vague system design prompt into requirements: verbs become use cases, nouns become owned entities, adjectives become constraints that justify components. Design Twitter: A Step-by-Step System Design Walkthroughhttps://designrounds.in/learn/design-twitter2026-10-20T00:00:00ZDesign Twitter step by step: use cases, entities and constraints, APIs, an incremental high-level design, and deep dives on celebrities, trends and search. Design a URL Shortener (bit.ly): Step-by-Step System Designhttps://designrounds.in/learn/design-url-shortener2026-10-20T00:00:00ZDesign a URL shortener step by step: requirements, estimates, data model, APIs, caching and 302 redirects, unique IDs with base62, and sharding by ID prefix. Design Pastebin: Object Storage, CDN and Edge Expiryhttps://designrounds.in/learn/design-pastebin2026-10-20T00:00:00ZDesign Pastebin: metadata in a database, text in object storage behind a CDN, random IDs, surviving write spikes, scaling to 1B users, edge expiry and tombstones. Design a Webhook Service: Reliable, Secure Event Ingestionhttps://designrounds.in/learn/design-webhook-service2026-10-20T00:00:00ZDesign a webhook receiver: queue-buffered ingestion, failure handling per component, HMAC signatures, idempotent duplicates and out-of-order events. Design Typeahead / Autocomplete: Ranked Tries and Precomputed Top-Khttps://designrounds.in/learn/typeahead-autocomplete2026-10-20T00:00:00ZDesign search autocomplete: a ranked trie with precomputed top-K in memory, prefix sharding, hot-prefix caching, offline builds with atomic swaps and trending. Design Tinder: Geo Feeds, Swipes and Mutual Matcheshttps://designrounds.in/learn/design-tinder2026-10-20T00:00:00ZDesign Tinder: a geo-indexed candidate feed, a swipe firehose sharded by swiper, derived matches with deterministic IDs, and a Bloom-filter seen set. Build a Social Media Comment System: Kafka, MongoDB and Redishttps://designrounds.in/learn/social-media-comment-system2026-10-20T00:00:00ZA hands-on build of a comment system with separate read and write paths: Flask, Kafka as a buffer, MongoDB, Redis, a load test and eventual consistency. System Design Roadmap 2026: Beginner to Advanced, Step by Stephttps://designrounds.in/learn/system-design-roadmap2026-10-17T00:00:00ZThe core system design roadmap every engineer starts with: fundamentals, building blocks, distributed systems and interview practice, each step linked to a free guide. Backend System Design Roadmap: LLD, Databases and Real Systemshttps://designrounds.in/learn/backend-system-design-roadmap2026-10-17T00:00:00ZThe backend (SDE) system design roadmap after the core: low-level design, API and database depth, reliable async work and the building blocks of classic questions. ML System Design Roadmap: From Data to Production Modelshttps://designrounds.in/learn/machine-learning-system-design-roadmap2026-10-17T00:00:00ZAn ML system design roadmap: features, training, serving, ranking and recommendations, evaluation, monitoring, plus RAG, vector search and LLM serving. Platform Engineering and SRE Roadmap: Kubernetes to SLOshttps://designrounds.in/learn/platform-engineering-roadmap2026-10-17T00:00:00ZA platform engineering and SRE roadmap: containers, Kubernetes, infrastructure as code, CI/CD, observability, SLOs, incident response and resilience. Distributed Systems Roadmap: Replication, Consensus, Consistencyhttps://designrounds.in/learn/distributed-systems-roadmap2026-10-17T00:00:00ZA distributed systems roadmap: failure models, replication and quorums, consistency, clocks, consensus with Raft, CRDTs and geo-replicated databases. Frontend System Design Roadmap: Web and Mobile Interviewshttps://designrounds.in/learn/frontend-system-design-roadmap2026-10-17T00:00:00ZA frontend system design roadmap for web and mobile: rendering strategies, state, caching, performance, offline sync, security and release engineering. API Design Best Practices: Resources, Versioning and Errorshttps://designrounds.in/learn/api-design2026-10-17T00:00:00ZREST API design best practices for system design: resource naming, status codes, versioning, pagination, idempotency, errors and backward compatibility. Optimistic vs Pessimistic Lockinghttps://designrounds.in/learn/optimistic-vs-pessimistic-locking2026-10-17T00:00:00ZOptimistic vs pessimistic locking explained: version columns, SELECT FOR UPDATE, lost updates, and how ticket booking avoids selling the same seat twice. Database Connection Poolinghttps://designrounds.in/learn/connection-pooling2026-10-17T00:00:00ZDatabase connection pooling explained: why connections are expensive, pool sizing, PgBouncer-style poolers, serverless pitfalls and pool exhaustion. Redis in System Design: Data Structures and Use Caseshttps://designrounds.in/learn/redis2026-10-17T00:00:00ZRedis explained for system design: strings, hashes, sorted sets and streams, caching, leaderboards, rate limits, persistence, replication and Redis Cluster. Partial Failure and the Fallacies of Distributed Computinghttps://designrounds.in/learn/fallacies-of-distributed-computing2026-10-17T00:00:00ZWhy distributed systems are hard: partial failure, unreliable networks, the eight fallacies of distributed computing, and crash to Byzantine failure models. The Two Generals Problem and FLP Impossibilityhttps://designrounds.in/learn/two-generals-and-flp2026-10-17T00:00:00ZThe Two Generals Problem and the FLP impossibility result explained simply, and why real systems still reach agreement with timeouts and majorities. Quorum Reads and Writes: R + W > N, Sloppy Quorums and Hinted Handoffhttps://designrounds.in/learn/quorums2026-10-17T00:00:00ZQuorum replication explained: N, R and W, why R + W > N gives overlapping reads, sloppy quorums, hinted handoff, read repair and tunable consistency. How Dynamo-Style Key-Value Stores Workhttps://designrounds.in/learn/dynamo-style-key-value-store2026-10-17T00:00:00ZHow Dynamo-style key-value stores work: partitioning on a hash ring, replication, quorums, vector clocks, anti-entropy and failure handling, step by step. Write-Ahead Logging (WAL) and Durabilityhttps://designrounds.in/learn/write-ahead-log2026-10-17T00:00:00ZWrite-ahead logging explained: why databases log before they write, fsync and group commit, checkpoints, crash recovery and log-based replication. Merkle Trees and Anti-Entropy Repairhttps://designrounds.in/learn/merkle-trees2026-10-17T00:00:00ZMerkle trees explained: hash trees that compare large datasets cheaply, anti-entropy repair between replicas, and their use in Cassandra, Git and blockchains. CRDTs: Conflict-Free Replicated Data Typeshttps://designrounds.in/learn/crdts2026-10-17T00:00:00ZCRDTs explained: counters, sets and sequences that merge without conflicts, state vs operation based CRDTs, and how collaborative editors use them. Hot Keys and Hot Partitions: Detecting and Fixing Skewhttps://designrounds.in/learn/hot-partitions2026-10-17T00:00:00ZHot keys and hot partitions explained: why skew breaks sharded systems, detecting them, key salting, splitting, caching and request coalescing fixes. Distributed SQL Databases: Spanner, CockroachDB and NewSQLhttps://designrounds.in/learn/distributed-sql2026-10-17T00:00:00ZHow distributed SQL databases work: range sharding, Raft-replicated ranges, distributed transactions and clocks in Spanner, CockroachDB and similar systems. Multi-Region Databases and Geo-Replicationhttps://designrounds.in/learn/geo-replication2026-10-17T00:00:00ZGeo-replication explained: single-leader vs multi-leader across regions, conflict resolution, follower reads, data residency and the cost of consistency. Video Streaming: Transcoding, HLS, DASH and Adaptive Bitratehttps://designrounds.in/learn/video-streaming-adaptive-bitrate2026-10-17T00:00:00ZHow video streaming works: upload, transcoding ladders, HLS and DASH segments, adaptive bitrate players and CDN delivery behind YouTube and Netflix. Payment Systems: Ledgers, Double-Entry Accounting and Reconciliationhttps://designrounds.in/learn/payment-system-ledger2026-10-17T00:00:00ZHow payment systems stay correct: double-entry ledgers, payment state machines, idempotent PSP calls, webhooks and daily reconciliation, step by step. Large File Uploads: Chunking, Resumable Uploads and Deduplicationhttps://designrounds.in/learn/resumable-file-uploads2026-10-17T00:00:00ZDesigning large file uploads: chunking, resumable and multipart uploads, presigned URLs, checksums, content-defined deduplication and sync for cloud storage. Distributed Job Scheduling: Cron, Delayed Jobs and Leaseshttps://designrounds.in/learn/distributed-task-scheduler2026-10-17T00:00:00ZHow distributed job schedulers work: cron and delayed jobs, time-bucketed queues, leases and heartbeats, retries, at-least-once execution and dead letters. High-Level Design vs Low-Level Design (HLD vs LLD)https://designrounds.in/learn/hld-vs-lld2026-10-17T00:00:00ZHLD vs LLD explained: what each interview round tests, the deliverables of high-level and low-level design, and how to prepare for both with examples. SOLID Principles Explained with Exampleshttps://designrounds.in/learn/solid-principles2026-10-17T00:00:00ZThe SOLID principles explained with code examples: single responsibility, open-closed, Liskov substitution, interface segregation and dependency inversion. Design Patterns for LLD Interviews: Strategy, Observer, Factoryhttps://designrounds.in/learn/design-patterns2026-10-17T00:00:00ZThe design patterns that come up in low-level design interviews: strategy, observer, factory, builder, singleton, decorator, adapter and state, with examples. ETL vs ELT: Differences, Pros and Cons, and When to Use Eachhttps://designrounds.in/learn/etl-vs-elt2026-10-17T00:00:00ZETL vs ELT explained: where transformations run, how cloud warehouses changed the trade-off, data quality and cost, and how to choose for a pipeline. Data Warehouse vs Data Lake vs Lakehousehttps://designrounds.in/learn/data-warehouse-vs-data-lake2026-10-17T00:00:00ZData warehouse vs data lake vs lakehouse: storage, schemas, query engines, governance and cost compared, and how to choose an analytics architecture. Medallion Architecture: Bronze, Silver and Gold Layershttps://designrounds.in/learn/medallion-architecture2026-10-17T00:00:00ZThe medallion architecture explained: bronze, silver and gold layers in a lakehouse, what belongs in each, data quality gates and common mistakes. Stream Processing: Windows, Watermarks and Late Datahttps://designrounds.in/learn/stream-processing-windows-watermarks2026-10-17T00:00:00ZStream processing concepts explained: event time vs processing time, tumbling, sliding and session windows, watermarks, late data and stateful operators. How Apache Spark Works: Driver, Executors, Partitions and Shuffleshttps://designrounds.in/learn/apache-spark-architecture2026-10-17T00:00:00ZApache Spark architecture explained: driver and executors, lazy DAGs, partitions, shuffles, broadcast joins, data skew and tuning Spark jobs at scale. Columnar File Formats and Partitioning: Parquet, ORC and Avrohttps://designrounds.in/learn/columnar-file-formats2026-10-17T00:00:00ZParquet vs ORC vs Avro explained: row vs columnar storage, compression, predicate pushdown, partitioning, the small files problem and choosing a format. Open Table Formats: Apache Iceberg, Delta Lake and Hudihttps://designrounds.in/learn/open-table-formats2026-10-17T00:00:00ZOpen table formats explained: how Apache Iceberg, Delta Lake and Hudi add ACID transactions, time travel, schema evolution and compaction to data lakes. Data Pipeline Orchestration: Airflow, DAGs and Backfillshttps://designrounds.in/learn/data-pipeline-orchestration2026-10-17T00:00:00ZData pipeline orchestration explained: DAGs, scheduling, dependencies, retries, idempotent tasks and backfills in Airflow, Dagster and similar tools. Data Quality and Data Observability: Checks, SLAs and Alertshttps://designrounds.in/learn/data-quality2026-10-17T00:00:00ZData quality and data observability explained: freshness, volume, schema and distribution checks, data SLAs, where to test in a pipeline and alerting. Data Contracts and Schema Evolutionhttps://designrounds.in/learn/data-contracts-schema-evolution2026-10-17T00:00:00ZData contracts and schema evolution explained: producer-owned schemas, compatibility rules, schema registries, breaking changes and versioning events. Feature Stores: Online vs Offline Features and Training-Serving Skewhttps://designrounds.in/learn/feature-store2026-10-17T00:00:00ZFeature stores explained: offline and online stores, point-in-time correct training data, streaming features and how they prevent training-serving skew. Recommendation System Design: Candidate Generation and Rankinghttps://designrounds.in/learn/recommendation-system-design2026-10-17T00:00:00ZHow recommendation systems are designed: candidate generation, two-tower retrieval, multi-stage ranking, re-ranking for diversity and feedback loops. ML Model Serving: Batch vs Real-Time Inferencehttps://designrounds.in/learn/model-serving2026-10-17T00:00:00ZML model serving explained: batch vs online inference, latency budgets, dynamic batching, GPU utilisation, model versioning, shadow and canary deployments. ML Evaluation: Offline Metrics, Online Metrics and Choosing Bothhttps://designrounds.in/learn/ml-evaluation-metrics2026-10-17T00:00:00ZHow to evaluate ML systems: precision, recall, AUC, NDCG and calibration offline, then CTR and guardrails online, and why offline wins don't always ship. A/B Testing and Experimentation Platformshttps://designrounds.in/learn/ab-testing-experimentation2026-10-17T00:00:00ZA/B testing for system design: randomisation units, assignment, metrics and guardrails, sample size, peeking, and building an experimentation platform. Distributed Model Training: Data, Model and Pipeline Parallelismhttps://designrounds.in/learn/distributed-training2026-10-17T00:00:00ZDistributed training explained: data, model and pipeline parallelism, all-reduce, sharded optimizers, checkpointing and failure recovery on GPU clusters. ML Model Monitoring: Data Drift, Concept Drift and Feedbackhttps://designrounds.in/learn/ml-model-monitoring2026-10-17T00:00:00ZML model monitoring explained: data drift vs concept drift, delayed labels, prediction and feature monitoring, alerting and when to retrain a model. MLOps: Model Registry, CI/CD for Models and Reproducibilityhttps://designrounds.in/learn/mlops-model-registry2026-10-17T00:00:00ZMLOps explained: experiment tracking, model registries, versioned data and code, CI/CD for models, approvals, rollback and reproducible training. Retrieval-Augmented Generation (RAG) Architecturehttps://designrounds.in/learn/retrieval-augmented-generation2026-10-17T00:00:00ZRAG architecture explained: chunking, embeddings, vector and hybrid search, re-ranking, prompt assembly, citations and evaluating retrieval quality. Vector Databases and Approximate Nearest Neighbor Searchhttps://designrounds.in/learn/vector-databases2026-10-17T00:00:00ZVector databases explained: embeddings, cosine similarity, ANN indexes like HNSW and IVF, filtering, recall vs latency and scaling vector search. LLM Inference and Serving: Batching, KV Cache and Latencyhttps://designrounds.in/learn/llm-inference-serving2026-10-17T00:00:00ZHow LLM serving works: prefill and decode, the KV cache, continuous batching, streaming tokens, quantization, routing between models and cost per request. Physical Servers vs VMs vs Containers vs Serverlesshttps://designrounds.in/learn/containers-vs-virtual-machines2026-10-17T00:00:00ZPhysical servers, virtual machines, containers and serverless compared: how each isolates workloads, pros and cons, and when to use which. Kubernetes Architecture: Control Plane, Nodes, Pods and Serviceshttps://designrounds.in/learn/kubernetes-architecture2026-10-17T00:00:00ZKubernetes architecture explained: API server, etcd, scheduler and controllers, nodes and kubelet, pods, deployments, services and the reconciliation loop. Infrastructure as Code: Terraform, State and Drifthttps://designrounds.in/learn/infrastructure-as-code2026-10-17T00:00:00ZInfrastructure as code explained: declarative vs imperative, Terraform plan and apply, remote state and locking, modules, drift detection and policy checks. CI/CD Pipelines: From Commit to Productionhttps://designrounds.in/learn/ci-cd-pipelines2026-10-17T00:00:00ZCI/CD pipelines explained: continuous integration, build artifacts, test stages, continuous delivery vs deployment, environment promotion and rollback. Feature Flags and Dynamic Configurationhttps://designrounds.in/learn/feature-flags2026-10-17T00:00:00ZFeature flags explained: release, experiment and kill-switch flags, targeting rules, evaluating flags safely at scale, config propagation and flag debt. Incident Management, On-Call and Blameless Postmortemshttps://designrounds.in/learn/incident-management2026-10-17T00:00:00ZIncident management explained: severity levels, on-call, incident roles, mitigation before root cause, status updates and writing blameless postmortems. Capacity Planning and Load Testinghttps://designrounds.in/learn/capacity-planning2026-10-17T00:00:00ZCapacity planning explained: forecasting demand, headroom and utilisation targets, load testing methods, finding the bottleneck and planning for peaks. Multi-Tenancy: Isolation Models for SaaS and Platformshttps://designrounds.in/learn/multi-tenancy2026-10-17T00:00:00ZMulti-tenant architecture explained: silo, pool and bridge models, tenant isolation, noisy neighbours, per-tenant limits, data partitioning and cost. Secrets Management: Vaults, Rotation and Workload Identityhttps://designrounds.in/learn/secrets-management2026-10-17T00:00:00ZSecrets management explained: why secrets don't belong in code, vaults and KMS, dynamic short-lived credentials, rotation, workload identity and auditing. Internal Developer Platforms and Golden Pathshttps://designrounds.in/learn/internal-developer-platform2026-10-17T00:00:00ZInternal developer platforms explained: golden paths, service templates, self-service infrastructure, service catalogs, guardrails and measuring adoption. Chaos Engineering and Resilience Testinghttps://designrounds.in/learn/chaos-engineering2026-10-17T00:00:00ZChaos engineering explained: steady-state hypotheses, fault injection, blast radius, game days and building confidence that a system survives failure. Frontend System Design Interview: A Framework and Examplehttps://designrounds.in/learn/frontend-system-design-interview2026-10-17T00:00:00ZHow to approach a frontend system design interview: requirements, component architecture, data model, API interface and optimisations, with a worked example. CSR vs SSR vs SSG vs ISR: Web Rendering Strategieshttps://designrounds.in/learn/rendering-strategies2026-10-17T00:00:00ZWeb rendering strategies compared: client-side rendering, server-side rendering, static generation, ISR, hydration and streaming, and when to use each. Web Performance and Core Web Vitals: LCP, INP and CLShttps://designrounds.in/learn/core-web-vitals2026-10-17T00:00:00ZWeb performance explained: Core Web Vitals (LCP, INP, CLS), the critical rendering path, code splitting, lazy loading and performance budgets. Frontend State Management: Local, Global and Server Statehttps://designrounds.in/learn/frontend-state-management2026-10-17T00:00:00ZFrontend state management explained: local vs global vs server state, stores, data-fetching caches, normalisation, optimistic updates and when to use each. Browser Caching: HTTP Cache Headers and Service Workershttps://designrounds.in/learn/browser-caching2026-10-17T00:00:00ZBrowser caching explained: Cache-Control, ETags and revalidation, immutable hashed assets, service worker caching strategies and what never to cache. Infinite Scroll and List Virtualizationhttps://designrounds.in/learn/list-virtualization2026-10-17T00:00:00ZInfinite scroll done right: cursor pagination, prefetching, windowed list virtualization, image placeholders, scroll restoration and accessibility. Image Optimization: Formats, Responsive Images and Lazy Loadinghttps://designrounds.in/learn/image-optimization2026-10-17T00:00:00ZImage optimization explained: AVIF and WebP, responsive srcset and sizes, lazy loading, placeholders, image CDNs and avoiding layout shift. Offline-First Apps: Local Storage, Sync and Conflict Resolutionhttps://designrounds.in/learn/offline-first-sync2026-10-17T00:00:00ZOffline-first app design explained: local databases, an outbox of pending changes, delta sync with cursors, conflict resolution and background sync. How Push Notifications Work: APNs, FCM and Web Pushhttps://designrounds.in/learn/push-notifications2026-10-17T00:00:00ZHow push notifications work: device tokens, APNs, FCM and Web Push, delivery guarantees, fan-out at scale, preferences, quiet hours and deduplication. Mobile Release Engineering: Staged Rollouts and Forced Updateshttps://designrounds.in/learn/mobile-release-engineering2026-10-17T00:00:00ZMobile release engineering explained: app store review, phased rollouts, feature flags, minimum supported versions, forced updates and crash monitoring. Micro-Frontends: Architecture, Composition and Trade-offshttps://designrounds.in/learn/micro-frontends2026-10-17T00:00:00ZMicro-frontends explained: splitting a web app by team, build-time vs runtime composition, module federation, shared dependencies and when to avoid them. Frontend Security: XSS, CSRF, CORS and Content Security Policyhttps://designrounds.in/learn/frontend-security2026-10-17T00:00:00ZFrontend security explained: XSS and how to prevent it, CSRF and SameSite cookies, CORS, Content Security Policy and storing tokens safely in the browser. System Design Interview Guide: The 6-Step Framework and How to Preparehttps://designrounds.in/learn/system-design-interview2026-10-14T00:00:00ZWhat a system design interview tests, the 6-step framework, how staff and startup rounds differ, what each level must show, common mistakes and a 4-week plan. System Design Interview Questions to Practice, by Role and Levelhttps://designrounds.in/learn/system-design-interview-questions2026-10-14T00:00:00ZSystem design interview questions grouped by role (SDE, data engineering, ML, platform, distributed systems, frontend) and level, with what each one tests. How to Study and Practice System Design (Without Memorizing Answers)https://designrounds.in/learn/how-to-practice-system-design2026-10-14T00:00:00ZHow to study system design: why memorized answers fail, what to learn in which order, and how books, mock interviews and AI practice fit together.