design patterns for scaling web applications
TRANSCRIPT
Design patterns for scaling web applications
SysAdmin Bulgaria meetup #01
tl;dr
Web application architecture
Life’s too short for bad software- Lew Cirne
tl;dr
Scalability patterns
The only real problem is scaling.Everything else is a sub-problem.
- O’Dell’s Axiom
Let’s start with hardware
Web application architecture
● Single machine web server● Two-tier web application● Multi-Tier application● Message Bus architecture● Service-Oriented architecture
Single machine web server
Single machine web server
● All in one servero Real IPo Web servero Application servero Databaseo Storageo Compute
● All in one servero Security problemo Shared CPUo Shared memoryo SPOFo Maintenance =
Downtime
Single machine web server
Two-tier web application
Two-tier web application
● Dedicated resources
● Multiple POF● Internal network● Maintenance =
downtime
● Different hardware generations
● Expensive
Multi Tier web application
Multi-tier web application
● Separate responsibility to teams● Most of security at first tier● Independant scaling● Front-end can talk with APIs internaly● Every tier can have it’s own hardware
requirements● Global Load Balancer
Global Load Balancer
Message Bus application
Message Bus application
● Many to Many communication between servers
● Replaces constantly polling the database● Asyncronious, not sorted● Loosly coupled systems● Support different hardware
Service Oriented Architecture
Service Oriented Architecture
● Loosly coupled systems● Service oriented company - small teams● Can provide services to third parties● Can subscribe to services from third parties
Scaling Up
● Bottleneck● Measure Results● Horizontal
duplication● Functional/Service
split● Lookup-oriented
split
● Caching● Data sharding● Threading● Queueing● Content Delivery
Networks
Theory of constraints
● Identify the Bottleneck● Utilize the Bottleneck● Adjust Non-Bottlenecks● Elevate the Bottleneck● Review the Process
Finding the bottleneck
● Accumulation● Throughput● Full Capacity● Wait Times
Measure results
Caching
cache hit ratio = cache lookups / cache hits● Store most recent data● Store most used data● Store only repeatedly used data
Cache invalidation - TTL
Threads and Queues
● Single thread process vs Multi thread process
● Queues FIFO, LIFO
Content delivery network
Additional reading