System Design for Interviews and Beyond (System Design Thinking)
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Harry Potter

Harry Potter

May 28, 2023

System Design for Interviews and Beyond (System Design Thinking)

Learn system design thinking with the "System Design for Interviews and Beyond" course. Explore functional and non-functional requirements, scalability, performance, reliability, caching, network protocols, messaging patterns, and more. Build reliable, scalable, and fast systems with expert guidance. Enroll now!


Course curriculum


Course introduction

Who will benefit from the course and how

Course overview


How to define system requirements

  • System requirements
  • Functional requirements
  • High availability
  • Fault tolerance, resilience, reliability
  • Scalability
  • Performance
  • Durability
  • Consistency
  • Maintainability, security, cost
  • Synopsis of system requirements

Instructions to accomplish specific system characteristics with the assistance of hardware

  • Locales, availability zones, data focuses, racks, servers
  • Actual servers, virtual machines, holders, serverless
  • Essentials of reliable, scalable, and fast communication

Synchronous versus asynchronous communication

  • Asynchronous informing patterns
  • Network protocols
  • Blocking versus non-blocking I/O
  • Data encoding designs
  • Message affirmation

How to further develop system performance with caching

  • Deduplication cache
  • Metadata cache
  • The significance of queues in distributed systems
  • Queue
  • Full and void queue problems
  • Begin with something basic
  • Blocking queue and producer-consumer pattern
  • Thread pool
  • Big compute architecture


About this course

75 illustrations

8 hours of video content

Course syllabus

  • System requirements (functional and non-functional requirements)
  • Functional requirements (how to characterize, working backwards approach)
  • High availability (time-based and count-based availability, design principles behind high availability, processes behind high availability, SLO, SLA)
  • Fault tolerance, resilience, reliability (blunder, fault, failure, fault tolerance, resilience, game day versus confusion designing, expected and surprising failures, reliability)
  • Scalability (vertical and level scaling, flexibility versus scalability)
  • Performance (inertness, throughput, percentiles, how to expand compose and throughput, bandwidth)
  • Durability (backup (full, differential, steady), Assault, replication, checksum, availability versus durability)
  • Consistency (consistency models, possible consistency, linearizability, monotonic peruses, read-your-composes (read-after-compose), consistent prefix peruses)
  • Maintainability, security, cost (maintainability perspectives (failure modes and alleviations, checking, testing, organization), security aspects(CIA ternion, character and authorizations the board, foundation insurance, data assurance), cost angles (designing, support, hardware, programming))
  • Synopsis of system requirements (a solitary rundown of the most famous non-functional requirements)
  • Districts, availability zones, data focuses, racks, servers (how hardware assists with accomplishing specific characteristics)
  • Actual servers, virtual machines, holders, serverless (advantages and disadvantages of various registering conditions, what are they great for)
  • Synchronous versus asynchronous communication (synchronous and asynchronous request-reaction models, asynchronous informing)
  • Asynchronous informing patterns (message lining, publish/subscribe, contending consumers, request/reaction informing, need queue, guarantee check)
  • Network protocols (TCP, UDP, HTTP, HTTP request and reaction)
  • Blocking versus non-blocking I/O (attachment (blocking and non-blocking), association, thread per association model, thread per request with non-blocking I/O model, occasion circle model, simultaneousness versus parallelism)
  • Data encoding designs (literary versus binary configurations, blueprint sharing choices, backward compatibility, forward compatibility)
  • Message affirmation (protected and risky affirmation modes)
  • Deduplication cache (neighborhood versus outside cache, adding data to cache (expressly, certainly), cache data ousting (size-based, time-based, unequivocal), termination versus invigorate)
  • Metadata cache (cache-aside pattern, read-through and compose through patterns, compose behind (compose back) pattern)
  • Queue (bounded and unbounded queues, round buffer (ring buffer) and its applications)
  • Full and void queue problems (load shedding, rate limiting, how to manage failed requests, backpressure, flexible scaling)
  • Begin with something straightforward (similitudes between single machine and distributed system ideas, interview tip)
  • Blocking queue and producer-consumer pattern (producer-consumer pattern, pause and tell, semaphores, blocking queue applications)
  • Thread pool (upsides and downsides, central processor bound and I/O-bound assignments, agile closure)
  • Big compute architecture (batch processing model, embarrassingly equal problems)
  • Log (memory versus plate, log division, message position (offset))
  • Index (how to carry out a proficient index for an informing system)
  • Time series data (how to store and recover time series data at scale and with low idleness)
  • Straightforward key-value database (how to build a basic key-value database, log compaction)
  • B-tree index (how databases and informing systems use B-tree indexes)
  • Embedded database (embedded versus far off database)
  • RocksDB (memtable, compose ahead log, arranged strings table (SSTable))
  • LSM-tree versus B-tree (log-organized combine tree data structure, compose enhancement, read intensification)
  • Page cache (how to increment plate throughput (batching, zero-duplicate read))
  • Push versus pull (advantages and disadvantages of both models)
  • Host discovery (DNS, anycast)
  • Service discovery (server‑side and client-side discovery patterns, service library and its applications)
  • Peer discovery (peer discovery choices, membership and failure recognition problems, seed hub, how tattle protocol works and its applications)
  • The most effective method to pick a network protocol (when and how to pick between TCP, UDP and HTTP)
  • Network protocols, all things considered, systems (test: what network protocol would you decide for different system design problems)
  • Video over HTTP (versatile real time)
  • CDN (how to utilize it, how it works, mark of presence (POP), benefits)
  • Push and pull technologies (short surveying, long surveying, websocket, server-sent occasions)
  • Push and pull technologies, in actuality, systems (test: what technology would you decide for different system design problems)
  • Large-scale push architectures (C10K and C10M problems, instances of large-scale push architectures, the most noticeable problems of handling enduring associations at large scale)
  • What else to be aware to build reliable, scalable, and fast systems (a rundown of normal problems in distributed systems, a rundown of system design ideas that assist with taking care of these problems, three-level architecture)
  • Timeouts (fast failures, slow failures, association and request timeouts)
  • How to manage failed requests (strategies for handling failed requests (drop, retry, failover, fallback))
  • When to retry (idempotency, test: which AWS Programming interface failures are protected to retry)
  • Instructions to retry (remarkable backoff, jitter)
  • Message delivery guarantees (at-most-once, basically once, precisely once)
  • Consumer balances (log-based informing systems, checkpointing)
  • Batching (upsides and downsides, how to handle batch requests)
  • Compression (advantages and disadvantages, compression calculations and the compromises they make)
  • Step by step instructions to scale message consumption (single consumer versus numerous consumers, problems with different consumers (request of message handling, double handling))
  • Partitioning, in actuality, systems (upsides and downsides, utilizations of partitioning)
  • Partitioning strategies (query strategy, range strategy, hash strategy)
  • Request routing (physical and virtual shards, request routing choices)
  • Rebalancing partitions (how to rebalance partitions)
  • Consistent hashing (how to execute, benefits and burdens, virtual hubs, utilizations of consistent hashing)
  • System overload (why safeguarding the system from overload is significant)
  • Autoscaling (scaling arrangements (metric-based, plan based, prescient))
  • Autoscaling system design (how to design an autoscaling system)
  • Load shedding (how to carry out it in distributed systems, significant contemplations)
  • Rate limiting (how to utilize the information acquired in the course for tackling the problem of rate limiting (bit by bit guide))
  • Synchronous and asynchronous clients (confirmation control systems, blocking I/O and non-blocking I/O clients)
  • Circuit breaker (circuit breaker limited state machine, significant contemplations)
  • Fail-fast design principle (problems with slow services (chain responses, flowing failures) and ways of addressing them)
  • Bulkhead (how to execute this pattern in distributed systems)
  • Shuffle sharding (how to carry out this pattern in distributed systems)
  • The end (a rundown of points that we will cover in the following module of the course)


Mikhail Smarshchok

Hello! This is Mikhail Smarshchok from the System Design Interview YouTube channel . I'm a programmer enthusiastically for getting the hang of, instructing and tutoring. Having over 15 years of industry experience, most recent 9 years I dealt with building scalable, highly available and low dormancy distributed systems. For quite a while, I have considered what is the best method for learning system design. While there are numerous magnificent assets for learning individual ideas, few give a comprehensive perspective on the best way to design systems. And even after you've contributed a ton of time and acquired a ton of information, it's still difficult to foster genuine system design thinking. Thinking that helps answer questions like: where to begin my design; where to go straightaway; how to break this big obscure problem into sub-problems that I know how to address; and regardless of whether I know the response, might I at any point make a reasonable deduction? So I provoked myself to make a course that can help build and further develop system design thinking. And after two years, you can see the consequence of this work. Go ahead and associate/follow me on LinkedIn where I attempt to post a greater amount of my viewpoints and learning material consistently:



What number of modules will be in the course?

There will be 3 modules in the "System design for interviews and beyond" course. The ongoing module is the first of three.

Inform us really concerning these modules.

Module 1 spotlights on the crucial ideas of system design. Module 2 will cover a greater amount of these ideas as well as a few further developed points. Module 3 will cover subjects like maintainability.


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Harry Potter

Harry Potter

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