Topcat's System Design Template

https://leetcode.com/discuss/career/229177/My-System-Design-Template

(1) FEATURE EXPECTATIONS [5 min]

---

  (1) Use cases
  (2) Scenarios that will not be covered
  (3) Who will use
  (4) How many will use
  (5) Usage patterns

(2) ESTIMATIONS [5 min]

---

  (1) Throughput (QPS for read and write queries)
  (2) Latency expected from the system (for read and write queries)
  (3) Read/Write ratio
  (4) Traffic estimates
    - Write (QPS, Volume of data)
    - Read  (QPS, Volume of data)
  (5) Storage estimates
  (6) Memory estimates
    - If we are using a cache, what is the kind of data we want to store in cache
    - How much RAM and how many machines do we need for us to achieve this ?
    - Amount of data you want to store in disk/ssd

(3) DESIGN GOALS [5 min]

---

  (1) Latency and Throughput requirements
  (2) Consistency vs Availability  [Weak/strong/eventual => consistency | Failover/replication => availability]

(4) HIGH LEVEL DESIGN [5-10 min]

---

  (1) APIs for Read/Write scenarios for crucial components
  (2) Database schema
  (3) Basic algorithm
  (4) High level design for Read/Write scenario

(5) DEEP DIVE [15-20 min]

---

(1) Scaling the algorithm
(2) Scaling individual components:
  -> Availability, Consistency and Scale story for each component
  -> Consistency and availability patterns
(3) Think about the following components, how they would fit in and how it would help
  a) DNS
  b) CDN [Push vs Pull]
  c) Load Balancers [Active-Passive, Active-Active, Layer 4, Layer 7]
  d) Reverse Proxy
  e) Application layer scaling [Microservices, Service Discovery]
  f) DB [RDBMS, NoSQL]
    > RDBMS
      >> Master-slave, Master-master, Federation, Sharding, Denormalization, SQL Tuning
    > NoSQL
      >> Key-Value, Wide-Column, Graph, Document
        Fast-lookups:
        -------------
          >>> RAM  [Bounded size] => Redis, Memcached
          >>> AP [Unbounded size] => Cassandra, RIAK, Voldemort
          >>> CP [Unbounded size] => HBase, MongoDB, Couchbase, DynamoDB
  g) Caches
    > Client caching, CDN caching, Webserver caching, Database caching, Application caching, Cache @Query level, Cache @Object level
    > Eviction policies:
      >> Cache aside
      >> Write through
      >> Write behind
      >> Refresh ahead
  h) Asynchronism
    > Message queues
    > Task queues
    > Back pressure
  i) Communication
    > TCP
    > UDP
    > REST
    > RPC

(6) JUSTIFY [5 min]

---

  (1) Throughput of each layer
  (2) Latency caused between each layer
  (3) Overall latency justification