Automation

Finding the Right Yugabyte Api Endpoint

Valerie Parham-Thompson

As YugabyteDB continues to evolve, its extensive API ecosystem offers powerful capabilities for database management and automation. However, with hundreds of API endpoints across overlapping categories, locating exactly the right API endpoint can be challenging. In this guide, I’ll walk you through several proven strategies for efficiently finding the API endpoints you need, along with real-world examples and pro tips I’ve learned from working with YugabyteDB’s API ecosystem.

Method 1: Navigating Categories in the API Documentation

The API documentation (api-docs.yugabyte.com) provides a well-organized categorical view of available endpoints. Understanding how to navigate these categories effectively will significantly speed up your API discovery process:

How do you keep up with technology?

Valerie Parham-Thompson

One of my favorite interview questions is, “How do you keep up with technology?” The answer to this question shows a lot about a candidate. Do they use down time at work to read up on the recent blogs? Are they asking for new assignments to stretch their skillsets? What about the thought leaders are in the space – are they connected?

But we do have to face that there are more new technologies and news about technology than anyone could possibly read about in a day. In my chosen slice of technology, what is a small slice of open source databases, there seems to be a new major database every 6 months. That’s not even counting feature updates, security bugs, and the broad ecosystem around databases. My inbox has been full to overflowing of invitations to review, attend conferences, notice this hot new feature in a top technology, etc.

Tilting at Windmills

Valerie Parham-Thompson

I read recently that 60% of everything you saw on the internet was AI-generated. And that 90% of everything could be AI-generated by 2026, or maybe 99%, depending on the article.

I’m not linking to any of these, because of course it’s all conjecture on their part. But anecdotally, I see a lot more junk online than I did last year. My husband and I recently read a bunch of reviews on a shopping site together, laughing at how badly they had been generated. And the “how to do this one technical thing” Google results are littered with the same article repeated by bots. I had a good run on Stack Overflow and just stopped one day because it was so depressing realizing that it was being mined for content.

Processing Data with Pandas

Valerie Parham-Thompson

I’ve been experimenting with processing data with Pandas this week, specifically historical NOAA weather data, and storing it in a local YugabyteDB cluster. This open data set contains max/min/precipitation for years back to 1750 (not all data points are available for all years or locations). It’s available here: https://www.ncei.noaa.gov/metadata/geoportal/rest/metadata/item/gov.noaa.ncdc:C00861/html

I leveraged my existing demo framework to provision a local YugabyteDB cluster, and then used Pandas to import data from txt and csv files. The txt lookup files were countries, states, stations, and inventory. The csv files were available in different formats. The code I’ve linked below imports all weather data for a single year.

Foreign Data Wrappers

Valerie Parham-Thompson

I was recently setting up a demo to show off query logging features. Two common extensions, pg_stat_statements and pg_stat_monitor, store data locally. In the case of a distributed database, it is helpful to combine the query runtimes on all nodes.

YugabyteDB supports foreign data wrappers, so I decided to use this feature to combine query statistics from each of my three test nodes.

The libraries for the pg_stat_monitor extension are already installed, so the extension just needs to be created:

Provision Ansible Postgres on Mac

Valerie Parham-Thompson

I added a new database to my demo platform: Postgres. This code helps me provision Ansible Postgres on Mac for demo purposes or simple functional testing, and it is an extension of previous work I shared: https://valerieparhamthompson.com/posts/string-search/.

The script does a postgres install via Homebrew for Mac M1 and starts it up, then creates the database, user, etc. needed for the demo. Finally, it populates using my “million table” sql.

Most of this uses the Community.Postgres Ansible module found here: https://docs.ansible.com/ansible/latest/collections/community/postgresql/index.html