Optidash Is an Image Processing and Optimization API

Running in Production

English - June 28, 2021 04:00 - 1 hour - 61.1 MB - ★★★★★ - 8 ratings
Technology News Tech News deployment elixir flask hosting node rubyonrails phoenix production python techstacks Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed

Previous Episode: CourseMaker Is an Online Course Builder for Technical Makers

Next Episode: Avo Is a Framework for Creating Ruby on Rails Admin Panels

Przemek Matylla talks about building an image processing API with C, Python and Node. It's hosted on bare metal servers.

In this episode of Running in Production, Przemek Matylla talks about building
an image processing and optimization API with mostly C, Python and Node. It’s
hosted on bare metal servers in a data center and has been running in
production since 2019.

Przemek talks about handling 20-50 million+ daily API calls, how they’re using
C, image detection techniques, using Lua scripting with nginx, building their
own servers in a data center, using boring technology and much more.

Topics Include

3:17 – An average day has about 20 million API calls, busy days have 50m+
4:11 – Breaking down where C, Node and other languages are being used
6:46 – What happens when you upload an image to their API
9:06 – Really figuring out the file type of something that’s been uploaded
11:54 – Dealing with edge cases as they come up but preparing a bit ahead of time
14:45 – Switching from Core ML on Apple hardware to Tensorflow on AMD hardware
19:43 – There’s no framework sitting on top of the Node API server
22:28 – The customer facing web dashboard is using Express, the marketing site is Jekyll
24:41 – They’re mostly B2B so feature requests end up being 1 on 1 calls
25:23 – Handling payments with Stripe and using a Node / Angular app for it
28:04 – Using Lua with nginx for rate limiting, also nginx is their load balancer
31:05 – You can’t go wrong with boring and predictable technology
31:47 – MongoDB, Redis and Elasticsearch are all running on 3 nodes each
32:18 – Having nearly instant access to a ton of data helps figure things out
34:52 – What it was like finding a freelance C developer
35:55 – Sending webhooks out is controlled by a separate Node Bull driven app
38:41 – Dealing with GDPR compliance and storing images on GlusterFS for 1 hour
40:50 – Going with bare metal servers in their own data center over the cloud
44:51 – The servers have 32-256GB of memory and a range of different CPUs
46:34 – Having spare parts and dealing with hardware failures
49:15 – About 50 servers run the latest Ubuntu LTS and are managed with Puppet
51:22 – The deployment process for a number of different services
54:19 – It takes ~30min to replace a drive and every service is tripled up
56:48 – The database servers are replicated and there’s alarms and alerts set up
58:56 – Rate limiting was put in place for limiting API calls to customers
1:01:12 – There’s custom payment rates depending on each customer’s requirements
1:03:06 – Best tips? Over provision like crazy and monitoring lets you sleep at night
1:03:31 – Do what works for you, don’t copy another company because it works for them
1:05:48 – Check out https://optidash.ai, their tech blog and GitHub account

Links

📄 References

https://www.techpowerup.com/gpu-specs/firepro-d700.c2555
https://www.amd.com/en/products/epyc
https://first-colo.net/en/
https://www.backblaze.com/blog/backblaze-hard-drive-stats-q1-2021/
https://optirank.io/

⚙️ Tech Stack

express →

node →

angularjs →

c →

python →

swift →

jekyll →

aws →

cloudflare →

docker →

elasticsearch →

firebase →

glusterfs →

influxdb →

mailgun →

mongodb →

nginx →

puppet →

redis →

server-density →

🛠 Libraries Used

https://numpy.org/
https://developer.apple.com/documentation/coreml
https://www.tensorflow.org/
https://github.com/OptimalBits/bull
https://github.com/capistrano/capistrano
https://www.influxdata.com/time-series-platform/telegraf/

Support the Show

This episode does not have a sponsor and this podcast is a labor of love. If
you want to support the show, the best way to do it is to purchase one of my
courses or suggest one to a friend.

Dive into Docker is a video course that takes you from not knowing what Docker is
to being able to confidently use Docker and Docker Compose for your own apps.
Long gone are the days of "but it works on my machine!". A bunch of follow
along labs are included.

Build a SAAS App with Flask is a video course where we build a real
world SAAS app that accepts payments, has a custom admin, includes high test
coverage and goes over how to implement and apply 50+ common web app features.
There's over 20+ hours of video.