Building A FaaA Platform With Redis: Paulo Arruda

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Paulo Arruda presented on designing a simple serverless/FaaS architecture using Redis. The key aspects discussed were: 1) Using Redis to store metadata about workspaces and functions. 2) Implementing a reliable queue pattern with Redis to distribute function execution across multiple "Runners" and decouple the HTTP server from code execution. 3) When a request comes in, the HTTP server pushes the job onto an input queue in Redis. Runners then pull jobs off the queue and execute the function code.

Technology

PRESENTED BY
Building a FaaS platform with Redis
Paulo Arruda
faastRuby, Founder

PRESENTED BY
1 What is faastRuby?
A brief introduction to the platform.
2 Demo
Agenda:
3 Designing a simple FaaS architecture with Redis

PRESENTED BY
Serverless Software Development
platform for Ruby & Crystal
Components:
• faastRuby Local - A local emulator
to develop & test Ruby and Crystal
Serverless Apps
• faastRuby FaaS - Cloud or
Self-Hosted FaaS solution

PRESENTED BY
Develop
• Develop and test on your local
machine from your favorite code
editor
• Optionally synchronize your local
code changes to cloud-based
staging environments instantly
Run
• When you invoke your functions
via an HTTP request, the code is
executed in a self-contained,
isolated sandbox inside of an
always-warm Runner
Workflow
Deploy
• Deploy your functions to a workspace
in the cloud.
• Workspaces are groups of functions
that can be used to mimic
environments and compose a set of
routes for a distributed app built with
functions.

PRESENTED BY
* Redis and storage scalability, as well as overall
security, are out of the scope of this presentation.
From inception to first release
Requirements
● Fast
● Scalable*
● Secure*
● Triggered via HTTP
● Multiple Environments

PRESENTED BY
The idea
● Responds to 1 request at a
time
● Cleans itself up after each
run

PRESENTED BY
Using Redis to store metadata

PRESENTED BY
Workspace Metadata
Fields
● ID
2938
● Name
my_workspace
● Disk path
/workspaces/my_workspace
Key
● w:[workspace_name]

PRESENTED BY
Function Metadata
Fields
● ID
2938
● Name
my_function
● Runtime
ruby:2.5
● Disk path
[workspace_path]/my_function
Key
● w:[workspace_name]:my_function

PRESENTED BY
The Loadbalancing Problem
● Can't predict execution
time
● Complex Loadbalancing
algorithm

PRESENTED BY
Redis to the rescue: Reliable Queue Pattern

PRESENTED BY
Decoupling HTTP Server from Code Execution

$PRESENTED BY Request / Response { "function_metadata": (disk path, workspace_name, etc), "event": (body, query, headers, etc), "response_queue": "042b42aa-f274-4ba1-a2b8-ec883697ff51" } HTTP Server pushes job to input queue and listens on volatile queue with name 042b42aa-f274-4ba1-a2b8-ec883697ff51$

PRESENTED BY
● We used Redis as main database for the platform
● We used the Reliable Queue Pattern to distribute the execution
between Runners
Recap

Thank you!
faastRuby.io
Twitter: @parrudanet

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