Today I TA’d (Teacher’s Assistant) a course with Bridget at GOTO Chicago Conference. There were a number of workshops besides just the Kubernetes 101 like; Working Effectively with Legacy Code with Michael Feathers (@mfeathers), Estimates or NoEstimates with Woody Zuill (@WoodyZuill), Testing Faster with Dan North (@tastapod), Data Science and Analytics for Developers (Machine Learning) with Phil Winder (@DrPhilWinder), and so many others that I’d love to have multi-processed all at the same time! Digging through Kubernetes from a 101 course level was interesting, as I’ve never formally tried to educate myself about Kubernetes, just dove in. My own knowledge is very random about what I do or don’t know about, and a 101 course fills out some of the gaps for me.
The conference is located in a cool and sort of strange place for a conference, out kind of in the lake, called the Navy Pier. Honestly, I dig it, it’s a cool place for a conference. I enjoyed the ~15 minute walk from the hotel to the location too, because it’s right there on the tip of the pier, as shown in the fancy map below.
The workshop is going well. Bridget is filling up student’s brains and I’m going to dork around Kuberneting some Cassandra and Node.js for my talk. I’m pretty stoked as the talk has given me a good excuse to delve into some Node.js again, from a nodal systemic viewpoint, “Node Systems for Node.js Services on Nodes of Systemic Nodal Systems” this Thursday.
Recently I’ve been paying a lot more attention to the job market as I go through the finding, hiring, and gaining customers routine with a number of different companies, recruiters, and individuals I know within the industry. Conversations kick off a million different ways. In this post I’m going to tackle how I work pricing of a job for myself. Many companies have some criteria based on what others in the company are paid and someone in human resources often has some spreadsheet or whatever that tracks this stuff. This is the flip side of the coin, this is my pricing list. It’s really simple, it’s based on what I’m looking for in life and what a company can give me, which in turn dictates what I can do for a company and aligning with what they want too. In the end, this helps insure we both get a win out of the relationship. Continue reading “Pricing Calculations for Work & Projects”
Alright, I’m sure everybody has a vast and expansive understanding of machine learning and all the algorithms involved and…
…not really? Yeah, me neither. Alright, I’ve got a conference for you. The ML4ALL Conference is lined up for May 27–29th where a reasonably sized group of machine learning practitioners and completely new to the field people are going to gather to speak, learn, discuss, and aspire to more and better machine learning. We’d love for you to join us, come speak on a machine learning topic dear to your heart, and enjoy the city, sites, cuisine, and relaxed nature of Portland while you’re at it. Continue reading “ML4ALL (Machine Learning for All)”
In the next few weeks I’ll be doing some work for Honeycomb.io. In preparation I’ve been ramping up on a number of topics, namely the big one is the specific differences in things like observability and monitoring. The aside that makes this relatively easy, is I live and breath this space from a site reliability, apps, and services perspective. Not only am I fortunate in my situation to dive into this topic, I’m excited to do so as well.
I started this research just checking out what material Honeycomb.io has available onsite and additionally what Charity Majors has written, or spoken about at conferences. The first two were easy to find with a simple Google search and checking out the Honeycomb.io Blog. For each of these materials I’ve provided a summary before each linked reference. Enjoy. Continue reading “Reading Up on Observability and Monitoring”
I need a tool just to do some testing against an API end point. I figured I’d throw one together real quick in Go. With a few libraries it’s just a few steps to get the job done. The following is that project. Eventually I’ll create the services that will run in some containers I’ll throw into a Kubernetes cluster, but for now, it’s all CLI. Onward.The first thing I’ll need is Cobra. Continue reading “Building a Data Thrashing CLI Tool in Go”
Alright, there’s this one algorithm that I’ve solved before. I’ve always found it to be a rather fun little exercise to work out. It popped into my head recently and I wanted to recollect how the logic of it went, but my Google-fu wasn’t so great. In the end, I didn’t find the algorithm problem statement but I’ve recollected it as best as I could from memory. If you know what the name of this challenge is I’d love to know what it’s called or if I’ve put it back together correctly. Ping me @Adron.So the story goes something like this. There once were some nations with a number of cities in each nation. Every citizen has access to every city and every city has a town center for all the citizens to enjoy. Recently the roads were damaged from a lack of maintenance work, ya know, like in real life. Meanwhile there was a revolution that led to catastrophic war that destroyed all the town centers in the nations. So now none of the cities have reachable town centers or functional working town centers anymore! The citizens of the world are angry at the nations and demand immediate fixes to their roads and town centers, with a priority on the town centers! The leaders have decided that the roads shall be repaired and have hired me (you) to assist!The nation has n cities, we’ll number 1 to n. The cities have two way roads, totalling m roads. A citizen has access to the town center if: their city contains a town center and their city has a road to travel from their city with a town center to another city with a town center.
The following is a map of one great nation of cities with currently impassable roads that must be repaired.
Continue reading “Algorithms 101 Roads & Town Centers”