(1) APIs for Read/Write scenarios for crucial components
(2) Database schema
(3) Basic algorithm
(4) High level design for Read/Write scenario
(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
(1) Throughput of each layer
(2) Latency caused between each layer
(3) Overall latency justification