system design primer

• performance vs. scalability.
  • performance is when the system is fast for a single user.
  • scalability is when the service is fast for many users.
• latency vs. throughput.
  • latency is the time it takes to perform an action or produce a result.
  • throughput is the number of these actions per unit of time.
• cap-theorem.
  • consistency-patterns.
  • availability
  • availability-patterns.
• content-delivery-network.
• load-balancer.
• reverse-proxy.
• microservices in the application layer.
  • services such as consul, etcd, and zookeeper can help your microservices talk to each other.
  • disadvantages.
    • microservices add complexity.
• ways to scale databases.
  • database-replication.
  • database-federation.
  • database-sharding.
  • denormalization.
• nosql-database.
• sql vs nosql-database.
  • sql advantages.
    • structured data/strict schemas.
    • complex joins/relational data.
    • transactions.
  • nosql-database advantages.
    • dynamic schema.
    • non-relational data.
    • if you don’t need complex joins.
    • can store lots of data.
    • examples:
      • log data.
      • leaderboard data.
      • temporary data.
      • metadata.
• caching
• asynchronism.
• methods-of-communication.

references

• https://github.com/donnemartin/system-design-primer

further reading

• https://lethain.com/introduction-to-architecting-systems-for-scale/