donnemartin

Load balancers, caching, databases, distributed systems, scalability. Everything that sounds intimidating when a senior engineer starts talking. A massive free resource for understanding how large-scale systems work. donnemartin/system-design-primer

System Design Primer Learn how larger applications handle traffic, databases, caching and scaling. It's especially useful for understanding system design interviews. A good next step once you're comfortable with coding basics. GitHub repo - donnemartin/system-design-primer

4 free GitHub repos to crack system design interviews System design round coming up? You don't need a paid course to start. These 4 GitHub repos are free to read. Our take: one repo read end to end beats starring all four. 1. System Design Primer: donnemartin/system-design-primer 2. system-design (Karan Pratap Singh): karanpratapsingh/system-design 3. awesome-scalability: binhnguyennus/awesome-scalability 4. awesome-system-design-resources: ashishps1/awesome-system-design-resources Daily AI explainers on Instagram: instagram.com/theinferenceai.tech Free: 50 LLM interview questions PDF: harshal-dharpure.kit.com Voiceover: AI-generated (TTS) #programming #systemdesign #codinginterview #github

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System design capstone and final assessment --- title: "System design capstone and final assessment" published: true description: "Design a system from a one-line brief, with a pacing guide, a 100-point rubric and a 12-question assessment." tags: systemdesign, architecture, career, tutorial series: System Design Learning Path --- Part 8 of 8 · week 8 of the learning path The capstone has each team design a new system from a one-line brief, using the same six steps as the case studies, and the final assessment checks that everyone can apply the ideas to fresh scenarios. Capstone brief. Pick one, or have the trainer assign it: - A photo sharing feed for 50 million daily users. - A ride-hailing service that matches riders to nearby drivers. - A file sync service like a cloud drive. - A notification service that sends push, email and SMS at scale. - A distributed rate limiter used by many services. Deliverables: a design document of up to four pages following the six steps, one architecture diagram with numbered steps, and a 15-minute presentation followed by 10 minutes of questions. Pacing for a 45-minute design interview or review | Minutes | Step | | --- | --- | | 5 | Clarify requirements and scope | | 5 | Estimate load and storage | | 5 | Define the API and data model | | 10 | Draw the high-level design | | 15 | Deep dive on the two or three hardest parts | | 5 | Trade-offs, failures and monitoring | Common mistakes: skipping requirements, designing without numbers, leaving a single point of failure, ignoring duplicates and retries, forgetting how it will be monitored, and choosing exotic technology without a reason. Capstone rubric (100 points, pass mark 70) | Criterion | Points | What good looks like | | --- | --- | --- | | Requirements and scope | 15 | Functional and non-functional needs are explicit, with scope limits stated | | Estimation | 15 | Numbers are reasonable, shown, and used to drive choices | | Architecture and data model | 25 | A clear diagram, sensible components, API and data model that fit the requirements | | Deep dives | 25 | Consistency, scaling and failure handling are worked through for the hardest parts | | Trade-offs and operations | 20 | Alternatives are weighed, and monitoring, security and cost are addressed | Final assessment (12 scenario questions, pass mark 9, Architect level needs 11) 1. A photo app has 50 million daily users who each upload 2 photos of 3 MB a day. About how much new storage is needed per day before replication? - A) 30 TB - B) 300 TB - C) 3 PB - D) 3 TB 2. Which pattern keeps a multi-service order consistent without a distributed transaction? - A) A saga with compensating actions - B) A shared lock across services - C) A bigger database - D) Retrying every step forever 3. A service must guarantee that a database update and the matching event are both recorded. What should it use? - A) Publish the event first, then update the database - B) Update the database, then publish in a separate step - C) A bigger queue - D) The outbox pattern: write both in one transaction and publish from the outbox 4. A chat message reaches the server twice because the client retried. How do you avoid showing it twice? - A) Compare timestamps - B) Ignore all retries - C) Deduplicate by a client-generated message ID - D) Increase the timeout 5. A new video loads slowly for its first viewers but fast for later ones. Why? - A) Disk wear - B) The first request fills the edge cache from the origin and later requests hit the cache - C) DNS caching - D) Encoding finishes later 6. Two refund requests for the same payment arrive at the same moment. What stops the system refunding more than was paid? - A) Hope they do not collide - B) Separate caches - C) Eventual consistency - D) A transaction on a versioned or locked payment row, so the second request sees the first refund 7. A user updates their profile but sees the old value on reload. What is the likely cause and fix? - A) Reading from a lagging follower; read your own writes from the leader - B) A browser bug; clear cookies - C) Too few indexes; add more - D) Encryption; turn it off 8. A table keyed by timestamp has one overloaded partition. What is the best fix? - A) Give that partition larger disks - B) Add more replicas - C) Hash or combine the key so current writes spread across partitions - D) Delete old data 9. Two services always deploy together and share a database. What is this? - A) An ideal microservices design - B) A distributed monolith; merge them or redraw the boundaries - C) A gateway problem - D) A replica problem 10. The card network times out on an authorization. What should the payment service do? - A) Mark it processing and check its status or reconcile before any retry - B) Retry the authorization at once - C) Tell the customer it failed and refund - D) Delete the payment 11. Peak traffic is 3 million requests per second. Each server can handle 5,000 per second, and you run servers at 50% of that. About how many servers are needed? - A) 600 - B) 300 - C) 2,400 - D) 1,200 12. Events for the same order arrive out of order at a consumer. What is the best design? - A) Turn off the broker - B) Add more consumers - C) Key by order ID so they share a partition, and use version numbers to ignore stale events - D) Make the messages smaller {% details Final assessment answers %} 1. B 50 million times 2 times 3 MB is 300 TB per day. 2. A 3. D 4. C 5. B 6. D 7. A 8. C 9. B 10. A 11. D each server effectively handles 2,500 per second at 50% load, and 3 million divided by 2,500 is 1,200 servers. 12. C {% enddetails %} Sources and further reading - System Design Primer, with more practice problems and sample solutions for capstone ideas. - Designing Data-Intensive Applications, for checking consistency and failure reasoning in deep dives. - Timeouts, retries, and backoff with jitter, for the failure-handling part of the rubric. Resources - Designing Data-Intensive Applications by Martin Kleppmann, the main reference for Modules 3 and 4. - Building Microservices by Sam Newman, for Module 2. - System Design Interview by Alex Xu, for more worked designs. - Site Reliability Engineering from Google, for reliability and monitoring practice. - Stripe documentation on idempotent requests and on webhooks, for Module 7. The real-world figures in the case studies (message volume, hours uploaded and watched, connection counts) come from public statements and engineering write-ups and are used as inputs for exercises. Trainers should check the current numbers before each cohort. ``

Day-1 of finding goated GitHub repos System Design Primer: One of the most popular repositories on GitHub, offering a comprehensive, organized walkthrough of scalability, latency, caching, load balancing, and sample interview questions. Link: donnemartin/system-design-primer t.co

System design fundamentals: estimate, scale and trade off --- title: "System design fundamentals: estimate, scale and trade off" published: true description: "Back-of-envelope math, the core building blocks and the design method used in every later post." tags: systemdesign, architecture, beginners, tutorial series: System Design Learning Path --- Part 1 of 8 · week 1 of the learning path Every large design is the same few building blocks combined to meet numbers, so learn the blocks and learn to estimate before drawing any boxes. Learning objectives - Turn a product request into functional and non-functional requirements. - Do back-of-envelope estimates for traffic, storage and bandwidth. - Explain what each core building block does and when to use it. Requirements first - Functional: what the system does (send a message, upload a video, charge a card). - Non-functional: how well it does it: scale, latency, availability, durability, consistency, security and cost. - Ask about scope and priorities before designing; a design for 1,000 users and one for 100 million are different systems. Estimation cheat sheet | Fact | Rule of thumb | | --- | --- | | Seconds in a day | About 86,400, so requests per day divided by 86,400 gives average QPS | | Peak versus average | Plan for 2 to 3 times average, more for spiky products | | Memory read | About 100 nanoseconds | | SSD random read | About 100 microseconds | | Round trip inside one datacenter | About 0.5 milliseconds | | Round trip across continents | About 150 milliseconds | | Storage | Records per day times record size times retention | Worked example: 10 million daily users each make 20 reads and 2 writes a day. Reads are 200 million a day, about 2,300 per second on average and about 7,000 at a 3x peak. Writes are 20 million a day, about 230 per second and about 700 at peak. At 1 KB per write, that is 20 GB a day, or about 7.3 TB a year before replication. Building blocks | Block | Job | Key choices | | --- | --- | --- | | Load balancer | Spreads requests across instances | Layer 4 or layer 7, health checks, algorithm | | Cache | Serves hot data from memory | Cache-aside versus write-through, eviction, expiry, stampede protection | | CDN | Serves static and cacheable content near users | What to cache, expiry, invalidation | | Relational database | Structured data with transactions | Indexes, replicas, sharding | | NoSQL store | Scale and flexible models | Key-value, document, wide-column, graph | | Queue or log | Decouples producers and consumers, absorbs spikes | Ordering, retention, delivery guarantees | | Object storage | Cheap durable storage for large files | Lifecycle, access control | | Search index | Full text and filtered queries | Refresh lag, relevance | | Rate limiter | Protects services from abuse and overload | Token bucket, per-user or per-key limits | Scaling basics: make services stateless so any instance can serve any request; scale out behind a load balancer; cache reads; replicate data for reads and safety; shard data when one node cannot hold or write it all. When the network splits, a distributed store must choose consistency or availability, so decide per feature which matters more. Design exercise: a URL shortener gets 100 million new links a month with ten reads per write. Estimate write and read QPS, storage over five years and cache size for the hottest 20% of links, then list the blocks you would use. Quiz 1 (5 questions, pass mark 4) 1. About what is the average QPS for 86.4 million requests a day? - A) 100 - B) 1,000 - C) 10,000 - D) 86,400 2. Why is a stateless service easy to scale? - A) It uses sticky sessions - B) It keeps sessions in local memory - C) Any instance can serve any request, so you add instances behind a load balancer - D) It needs a single large server 3. What is cache-aside? - A) The cache is the only store - B) Reads bypass the cache - C) The database pushes every write into the cache - D) The app checks the cache first and, on a miss, reads the database and fills the cache 4. What does a CDN mainly do? - A) Serves static and cacheable content from locations near users, cutting latency and origin load - B) Stores financial transactions - C) Runs SQL queries - D) Encrypts the database 5. How should you size for traffic peaks? - A) Use the average only - B) Ignore peaks - C) Plan for a multiple of average, commonly 2 to 3 times or more, plus headroom - D) Assume every second is a peak {% details Quiz 1 answers %} 1. B 86.4 million divided by 86,400 seconds is 1,000 requests per second. 2. C 3. D 4. A 5. C {% enddetails %} Sources and further reading - Latency numbers every programmer should know, the Jeff Dean and Peter Norvig figures behind the estimation table; the numbers are rough and dated, so use them for orders of magnitude. - System Design Primer, an open study guide covering the building blocks in this module. - Designing Data-Intensive Applications by Martin Kleppmann, for caching, replication and consistency in depth. --- Part 1 of 8 in the System Design Learning Path series. Next: part 2.

@KgosiKevin @_furnx I recommend this repo. donnemartin/system-design-primer

System Design Primer: how apps handle millions of users How do apps serve millions of users? This free guide explains. The System Design Primer teaches how big systems are built and scaled, with Anki flashcards to help you remember. It is a favourite for system design interviews. Get it free on GitHub: donnemartin/system-design-primer Comment "SCALE" and I'll send you the link. Follow RepoDrop for a free GitHub tool every day. #shorts #github #systemdesign

GitHub 스타 TOP 10 오픈소스 (2026.10.15 기준) GitHub에서 별(스타)을 가장 많이 받은 저장소 TOP 10 (2026년 10월 15일 기준) 00:00 10위 awesome-python 00:19 9위 coding-interview-university 00:35 8위 developer-roadmap 00:46 7위 system-design-primer 01:01 6위 openclaw 01:14 5위 free-programming-books 01:28 4위 freeCodeCamp 01:41 3위 public-apis 01:54 2위 awesome 02:06 1위 build-your-own-x 순위·별 개수는 GitHub API(api.github.com)로 조회했고, 별 개수는 계속 바뀝니다. 1위 codecrafters-io/build-your-own-x — ★553,348 — 저장소의 LICENSE 참고 codecrafters-io/build-your-own-x 2위 sindresorhus/awesome — ★519,278 — CC0-1.0 sindresorhus/awesome 3위 public-apis/public-apis — ★488,929 — MIT public-apis/public-apis 4위 freeCodeCamp/freeCodeCamp — ★457,094 — BSD-3-Clause freeCodeCamp/freeCodeCamp 5위 EbookFoundation/free-programming-books — ★399,091 — CC-BY-4.0 EbookFoundation/free-programming-books 6위 openclaw/openclaw — ★392,069 — MIT openclaw/openclaw 7위 donnemartin/system-design-primer — ★374,285 — 저장소의 LICENSE 참고 donnemartin/system-design-primer 8위 nilbuild/developer-roadmap — ★369,449 — 저장소의 LICENSE 참고 nilbuild/developer-roadmap 9위 jwasham/coding-interview-university — ★362,528 — CC-BY-SA-4.0 jwasham/coding-interview-university 10위 vinta/awesome-python — ★327,562 — 저장소의 LICENSE 참고 vinta/awesome-python ※ 화면의 저장소 이미지는 각 저장소가 GitHub에 올려 둔 대표 이미지(소셜 미리보기)이며 각 저작권자에게 권리가 있습니다. ※ 나레이션 음성(Microsoft Azure AI Speech), 배경음악(ACE-Step), 일부 장면 그림은 AI로 생성했습니다. #GitHub #오픈소스 #개발자