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Fundamentals - System Design

Course Contents

what-is-system-design-interview

system-design-interview-template

core-challenges-in-web-scale-app

how-to-scale-a-system

system-design-interview-study-guide

api-design-intro

api-design-example

api-design-pagination

api-design-authentication

api-design-authorization

non-functional-requirements

system-design-components

how-to-achieve-high-availability

tech-stacks-to-achieve-high-availability

back-of-envelope-calculation

back-of-envelope-calculation-real-world-examples

microservice-communications

synchronous-communication

synchronous-communication-implementation

synchronous-communication-failure-handling

circuit-breaker

service-discovery

microservice-async-comm

message-queue-use-cases

redis-queue-tutorial

log-based-message-queues

introduction-to-kafka

evolution-of-computing-environments

evolution-of-a-web-app-stateless-vs-stateful

evolution-of-a-web-app

load-balancing-code-lab

read-write-separation

caching-patterns

cache-aside-pattern

caching-write-through-pattern

caching-write-back-pattern

choosing-caching-pattern

caching-scaling

cdn-cache-invalidation

cache-thundering-herd

dataflow-system-design

push-vs-pull-twitter-timeline

data-structures-behind-databases

introduction-to-storage

key-value-database

document-database

full-text-search-database

blob-object-storage

database-scaling

database-replication

implementing-database-replication

database-replication-codelab

change-data-capture

database-partitioning

advanced-database-partitioning

consistent-hashing

database-partition-codelab

batch-and-stream-processing

batch-processing

dataflow-engines

why-use-batch-processing

stream-processing

batch-vs-stream-processing

lambda-architecture

kappa-architecture

database-optimization

a-database-per-service

multi-system-data-sync

unique-id-generators

rate-limiting-patterns

two-stage-processing

system-design-template

system-design-template-social-media-comments

push-vs-pull

push-vs-pull on CodePeet.

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