A Weather Analysis Service for Regular People and Meteorologists

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In this episode of Running in Production, Nick Gregory walks us through what it’s like building Vortex Weather which uses Flask and Python to help understand the weather. It’s hosted on bare metal servers running in a colo on top of a self managed Kubernetes cluster.

Nick goes into detail on having to manage 750+ GB of data that needs to be recycled every 2 days and having his own servers with a combined, 24 physical CPU cores, 128+ GB of RAM and 10+ TB of disk space. The app is open source and it’s his side project, so he also talked about tips on how to manage his time and enforce self imposed deadlines.

Topics Include

  • 1:59 – Weather data can come from a number of different sources
  • 3:01 – 750+ GB of data is cycled every 2 days and it needs to be queryable in ~200ms
  • 3:57 – This is Nick’s side project and he’s the sole developer which has its challenges
  • 5:13 – The app is open source on GitHub
  • 5:26 – Motivation for using Python and Flask
  • 6:53 – Picking gunicorn over uwsgi, mainly for ease of deployment
  • 9:32 – The web front-end is a monolith but the data processing happens in a different service
  • 10:55 – Looking at Go for more performance on the math heavy calculations
  • 12:15 – Ingesting data is done through Kubernetes cron jobs and it’s backed by PostgreSQL
  • 15:00 – PostgreSQL is really amazing and works great as a queue back-end
  • 16:34 – PostgreSQL was originally used for the 750 GB of data but then it was moved to S3
  • 18:41 – The files on S3 are 10+ GB in size (each)
  • 19:36 – The files are a huge series of floats in a binary format
  • 21:02 – PostgreSQL ends up storing a little bit of meta-data that’s used to get data from S3
  • 21:19 – It was all moved out of PostgreSQL because…
  • 24:03 – Before the S3 change there were over 2.5 billion rows being saved to PostgreSQL
  • 25:10 – Seriously, PostgreSQL is really good
  • 25:49 – Visualizing weather in a radar view requires a massive amount of computing power
  • 28:23 – Predicting the weather in the short term future based on clouds and wind
  • 30:54 – Docker is being used in development and it’s making things a lot easier
  • 32:01 – Ubuntu is being used as a base OS for the Docker images
  • 33:28 – Traefik sits in front of gunicorn to do TLS termination and act as a reverse proxy
  • 35:10 – Traefik is rock solid but it’s not a complete drop in replacement for nginx
  • 38:27 – (2) servers are sitting in a colo for now, mainly for cost and performance wins
  • 40:13 – The TL;DR on what a colo (colocation) is and what it’s like owning your own hardware
  • 41:27 – Server 1 has 8 CPU cores, 96 GB of RAM, 6 TB of HDD space in RAID-5 and a 2 TB SSD
  • 42:10 – Server 2 is a Threadripper with 16 CPU cores, 64 GB of RAM and (2) 2 TB NVME SSDs
  • 42:53 – How much storage could you fit? 10+ SSDs plus the PCI slots on the motherboard
  • 43:47 – Getting similar capacity and performance with AWS would be a lot more money
  • 44:49 – Nick runs a Debian based distro called Proxmox
  • 45:55 – A good GUI is one of the selling points for Proxmox, even though it’s on a server
  • 46:41 – Kubernetes is self managed but it was configured with Rancher’s RKE
  • 48:49 – Prior to finding RKE, he almost went with Swarm due to Kubernetes’ complexity
  • 49:54 – Currently there’s no error reporting set up, but Sentry.io is on the horizon
  • 51:24 – Deploying code from development to production
  • 51:34 – The weather app is on the Docker Hub at kallsyms/wx_explore
  • 53:22 – CI isn’t being used now but a self hosted Gitlab instance might happen in the future
  • 54:09 – As long as the kubeconfig stays out of CI, then it’s all good
  • 55:43 – How are database migrations dealt with? By avoiding them since they’re not needed
  • 58:56 – What about backing up the database? It’s also not needed since it’s all recreatable
  • 59:57 – The weather tool is made for both regular people and meteorologists
  • 1:03:34 – StatusCake’s free tier is being used to do uptime monitoring
  • 1:05:55 – Best tips? Learning to self manage your time and break down problems
  • 1:07:01 – Learning best practices and tips on how to optimize Docker performance
  • 1:08:05 – Keeping yourself accountable for hitting self imposed deadlines
  • 1:11-20 – You can find Nick on Twitter @kallsyms and on GitHub too
📄 References
⚙️ Tech Stack
🛠 Libraries Used

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Mar 02, 2020

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