I've been posting more regularly on Twitter recently. Sometimes, I like to use it as a way to publicly share thoughts and updates. I'll even use it to share long-form thoughts by creating long threads. At the end of the thread, I ask the @threadreader bot to "unroll" my Tweets so it reads more like a blog.
I'm embedding my recent Weekly Update Twitter posts below:
Start of Twitter thread. Click to see whole thread on Twitter:
https://twitter.com/youngchingjui/status/1155848557993181185?s=21
✅ finally built script to track usage of my servers. It’s a python script uploaded to AWS lambda. The script pings my half-dozen servers for data usage and writes the data onto 1) a MySQL server hosted on AWS RDS, 2) BigQuery database, and 3) google sheets✅ built a dashboard on server usage data using Tableau public. I now have the dashboard scrolling on my Life Flips app.✅ went through another few hours of the Udemy course I’m taking on writing shell scripts. This has been a much needed course!
▫️get react native set up on my computer again (I did a hard hard drive reset last week)▫️redesign my Podcast Social app on Sketch▫️convert the sketch elements into react native code
(Sometimes I don’t know how to answer this question. Not necessarily “stuck” on anything - just mounds of work to get through!)- I guess working with React Native? This will be my first react native project, so I expect lots of delays and learning!
This itself is a funny story. Why make my #Python script write to 3 different databases? Here’s how it started:
This is my first time working with and setting up databases. I wanted to store structured usage data for analysis in the future. Didn’t really know the difference between DB options (#MySQL vs. PostgreSQL vs. BigQuery...?). But a relational database sounded nice.
Initially I went with Google Cloud Platform’s #CloudSQL option. Set it up, I have free credits left, and tested it out. I was able to interact with it with my Python script - great!
But over the next few days, I realized that my #GCP MySQL database was eating up lots of credits. It was costing me USD2.50 a day! What the heck? I wasn’t using it, wasn’t writing new data to it, no new queries were made....
Later I found out that the new Cloud SQL engine doesn’t automatically shut off when inactive. Not sure why they have this policy. But it made it very expensive to play around with Cloud SQL
Fine, let’s try out #AWS Relational Database Service. They had a vanilla MySQL option. I’ve heard of MySQL before...it’s probably popular. And they have a free tier. Great.
Setup was seamless, their browser console is more responsive than GCPs, and I got a quickly server up and running. I downloaded MySQLWorkbench to connect remotely...and it works! I quickly wrote some Python script to test out reading and writing - it works!
Great. I incorporated the AWS MySQL DB into my Python script. I would extract usage data from my GCP-hosted VMs and write the data to MySQL. Eventually, I want to build an easy dashboard that automatically retrieves data from this database.