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Edge Computing for WebApp

Jimmy Moon
December 05, 2022

Edge Computing for WebApp

Explaining brief a history of edge computing for webapp

Jimmy Moon

December 05, 2022

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  1. Mainframe 
 computing - 1960 ~ 1970 - Large, monolithic

    systems - Physical datacenter on-site - Serving via terminals
  2. Server / Client 
 computing - 1980 ~ 1990 -

    Primary datacenter for large project and data storage - Working on the network for multiple client connections - Serving via local computer
  3. Cloud 
 computing is - 2000 ~ 2010 - Data

    centers as public cloud platform not on-site - All of the processing and storage happening o ff site in the cloud - Running many of services, Infra, Services, Containers, Workers, Functions ... - AWS, GCP, Azure, ...
  4. Edge Computing - Ultra-low latency and decrease in bandwidth use

    - Decrease in server resources - Functionality not only static resources - Mobile, IoT, Apps need for speed
  5. Kelsey Hightower 'You can host not just images but logic

    and run it safely on the Edge, like why now ?'
  6. Process Isolation - Next process model after container, worker on

    cloud - Running in sandbox, isolated and stateless - Starting up really fast - Executing optimized minimalistic code - V8 Isolates(Vercel, Deno, Cloud f lare), microVMs(AWS f irecracker), WASI(WebAssembly) gVisor, OSv
  7. Optimized Minimalistic Code - Generate highly optimized machine code -

    low-level incremental computation engine for individual functions
  8. HTTP Default Protocol - `Web is becoming the computer then

    the concept of http being the most dominant protocol` - Kelsey Hightower - 0-RTT(Zero Round Trip Time) via TLS 1.3 or QUIC - HTTP/3 powered by `UDP`
  9. Edge Computing for WebApp - Using functions on the Edge

    as like local package - Using server resources on the cache of Edge as like local f iles - WebApp/Functions can be served in compact size as much as decreased - Bring computing power from outside Browsers in a second - Centralized WebApp can be running close to users - ...
  10. WAS on Bare-Metal - Using computing power of dedicated physical

    server - Physical distance and count are matter
  11. VMs on Cloud - Using computing power of multiple instances

    in a physical - Scale-up and down instantly - Physical distance is still matter but not count
  12. Function / Lambda - Using computing power on centralized functions

    on cloud - Computing and virtualization is becoming more granular - Serverless - Physical distance is still matter but not count
  13. Edge - Using computing power on decentralized compact functions on

    each Edges - Ultra-low latency to function and resources - Physical distance and count doesn't matter