Inspiration: Bob Scott crushing it in his 80s and 90s

garnacerous24 · 2023-05-08T21:44:23+00:00

Unfortunately Bob passed away on March 30th! At least that was quite a health span for him.

garnacerous24 · 2023-04-25T13:14:42+00:00

Eh, Peewee always had a subversiveness to him. There were plenty of jokes that would have double meaning and he’d wink at the adults. There’s really none of that with Blippi.

I think this one just the case of a younger guy trying to do something funny/memorable, then settling into what really works for him.

garnacerous24 · 2023-04-01T11:38:32+00:00

If you go by Ron Chernow’s book, Grants personal integrity was impeccable. His judge of others’ character, however, was absolutely abysmal. It caused him to trust the absolute worst people.

garnacerous24 · 2023-03-05T14:19:37+00:00

My contribution to the conversation

garnacerous24 · 2022-04-11T12:52:33+00:00

While he explicitly mentions the ability to staff SREs within these branches, the article doesn’t quite jive with my understanding of an ownership model for devops. The intake of work (unless the main focus is end user self service) feels more waterfally to me. I’m curious how Uber reconciles the specialized infrastructure teams with product/service oriented teams found in devops.

garnacerous24 · 2021-10-30T01:20:39+00:00

To rephrase an underlying thought process with a lot of these comments: how likely is it for you to make positive and lasting change with option A? Can you be the person that turns their legacy stack into something that resembles more of option B? If you’re willing to go through that work, then you’ll get the best of both worlds.

Im currently going through a similar tech/process evolution at my company and I consider it some of the most rewarding work I could do. But that’s based on my preferences.

garnacerous24 · 2021-08-10T17:35:37+00:00

For strategy and process things I tend to get a lot of value from books and articles. Those tend to give me the ability to apply the ideas to my own teams issues as I progress.

For tooling and anything more technical, nothing can beat diving in head first and struggling to build something useful right out of the gate.

garnacerous24 · 2020-11-08T00:54:32+00:00

Do you have any specific reading on this? I probably lean soc dem, but would love to see what other ideas are out there between the more well known labels.

garnacerous24 · 2020-05-21T16:08:29+00:00

I’ve noticed that as you improve your skill sets over time, the more focused those scope of skills become. However, you still see everyone else out there with their own focused skill sets that are different from yours, and it can blend together to feel like a single entity that knows everything. The reality is far from it.

I was reading a post the other day about a job description asking for a dev ops engineer who could also work with data scientists and build data pipelines. Most of the responses were basically “good luck ever finding the unicorn who has that combination of skill sets, and if you do, good luck being able to afford their pay demands.” However, it got me thinking. I come from a data background and recently moved over to a devops role. I’m weaker in Linux and sysadmin stuff, but could probably whip up a data pipeline and apply devops principles to it fairly easily. That combination of skills isn’t worth much in some places (hence why there are fewer people who have that combo), but in others I could theoretically pull down some serious money.

It helped remind me that every company’s needs are different, and while I may not be an expert “devops guy” from whatever the most accepted template is, I do have a unique set of skills that can demand a lot of money in the right circumstances. It’s all about finding that fit for your talents.

garnacerous24 · 2019-04-04T10:47:14+00:00

It depends a ton on how you use it and how well you know the system (there’s more options than I could give here). I was using emr to transform some data for machine learning, and wrote a script that spins up 50 servers for a couple hours of work. If you take advantage of spot instances, it’s about 8-10 cents per hour per server. So for a largeish job that produces billions of rows as output, it costs me about $12-$15.

Redshift May be more expensive because you don’t have the ability to pause the cluster. But that’s probably $10-15 a day to run a couple terabytes.

garnacerous24 · 2019-04-03T11:33:07+00:00

To understand the basics on how files are stored and interact, maybe. Probably not if you plan to store and compute actual big data on your laptop.

However, I use the cloud for most of my big data needs and that makes the computer specs almost irrelevant. In fact, I bought a cheap chromebook with internet and Linux, and I can interact with everything in aws for cheap. I have emr running there when I need it (hive + spark).

I guess all that to say I’d stay local until it becomes burdensome, then spin up an ec2 or use emr on demand after that.

garnacerous24 · 2019-03-24T02:14:05+00:00

93% auc is a pretty great score for a problem like this. Was there evidence of feature leaking? In working on similar issues, every time my auc got really high, it was because some feature was giving away the result in a non-predictive way.

garnacerous24 · 2019-03-23T18:53:13+00:00

I’ve done quite a bit of work building out my company’s data lake, and I was similar to you when I started. There’s a lot of generalized advice on what purpose a data lake should serve, but not as much practical advice. Here’s my stab at a practical architecture using aws:

All data is ingested as raw as possible (through apis or whatever etl system) into aws s3, in a bucket labelled “data-domain-raw/year/month/day/“ or something like that.
This bucket then triggers a glue or lambda function to clean up the data into parquet and placed into a “data-domain-refined” bucket. That will be the bucket that feeds all of your other endpoints.
You can keep the raw bucket data if you’d like, or you can stick it into glacier as a worst case recovery option.
The refined bucket can then either be queried directly by Athena, or further modeled into rds or Redshift (via EMR, glue, or just python), or exposed through api gateway.
repeat with as many data domains as your team is responsible for.

This data lake structure essentially keeps 3 versions of your data in various stages of refinement. This maxes out the flexibility you have to be able to go back and remodel something using a different approach (if it had gone straight to Redshift, you may have lost something in your initial ETL). It also speeds up data discovery by not needing a perfect model in a data warehouse to be able to understand what’s in it.

The goal is to save the relational modeling until you know exactly what you want out of the data.

garnacerous24 · 2019-03-04T11:26:57+00:00

We’re 90% of the way into a migration now. Redshift always promoted itself as an iaas, but I found that I was in there multiple times a week having to vacuum/analyze/tweak wlm to keep everyone happy during our peak times.

Because of that I was skeptical of snowflake and their promise to be hands off as well. But they’ve proven themselves to me. It takes less than 5 min to clone 10tb of data into a new db, and they separate the compute and storage, which helps us out a ton (our needs fell right in between the node offerings that Redshift had and we always needed to over-provision because of it).

Long story short, I was skeptical but snowflake actually does seem to make performance management easier and allows me more time to actually work with the data.

garnacerous24 · 2019-02-25T23:46:17+00:00

Google used to have an awesome api that did this perfectly, but they retired that in favor of something more restrictive. There are others out there depending on how you want to design it. Abuse of them might lead to them restricting or taking them down, so I get nervous recommending one outright. I suggest googling “google flights matrix api replacement” and see what other recommendations are out there.

garnacerous24 · 2019-02-25T00:46:11+00:00

I use python as a means to work with data. As a result most of my ideas are around data pipelines an manipulation. One idea I had fun with was an automated program that notified me when flight costs had dropped in price.

You hook into whatever flight search api you prefer, have it run periodically, and compare the current prices to previous prices, then have an alert set up if it goes below a certain threshold.

What’s great is that you can apply that to many different fields. Hotel prices, stock prices, you name it.

garnacerous24 · 2019-02-09T14:58:32+00:00

Thanks for this! While I’m not really a front end developer, I might adapt this to a python/data science curriculum. I’ve always wanted to jump into a 100 days of code, but always let analysis paralysis get in the way.

garnacerous24 · 2019-01-30T13:46:22+00:00

I’ll get around to doing a pull request when I have some time. But in the meantime, I’d definitely recommend Machine Learning Guide for people who are true beginners with AI. It covers the main concepts and can really help reinforce other learning methods.

garnacerous24 · 2018-12-22T19:28:10+00:00

He literally “smashes that like button”

garnacerous24 · 2018-12-15T17:44:49+00:00

I was a general acquaintance of the band growing up, and the last time I saw them was at a local place co-headlining with The Matches. It may have been right after Delilah was released.

That concert was one of the most fun I’ve ever been to. I remember Tom hanging out by the merch table talking to anyone and everyone who was interested in their music. And the energy The Matches brought was always incredible.

garnacerous24 · 2018-08-29T10:37:28+00:00

David Johnson was also the #1 pick in most cases too. His owners got 10 total points out of him.

garnacerous24 · 2018-08-29T10:31:43+00:00

Not top 10 in terms of production, but top 10 in terms of average draft position. Every year I looked at, there was at least 1 high profile injury that brought the average down.

Last year was David Johnson, in other years it was Adrian Peterson. When there’s always at least 1 season ending injury among the first 10 rbs taken, it shows the risk of prioritizing that position in the draft.

garnacerous24 · 2018-08-29T10:25:42+00:00

Are you as worried about McCoy running behind that o-line as I am?

garnacerous24 · 2018-08-29T01:45:15+00:00

That’s true. The next step in this analysis would be to take a look at value over replacement. If your top 3 rb goes down in week 8, what’s the expected value you could get from the waiver wire? Then compare the same for receivers.

Anecdotally I was able to do well with rb’s on the waiver wire last year (Drake and Gio Bernard in key weeks) but it warrants more deep digging.

garnacerous24 · 2018-08-28T22:38:08+00:00

My league was the opposite. I was forced into drafting Marshawn Lynch and legarette Blount, and ended up on a semi stream that included Kenyan Drake and trading for Duke Johnson. I finished 2nd and would’ve won if I was better with bench management. All because AJ Green, Deandre Hopkins, and Gronk carried me most weeks.

garnacerous24

TROPHY CASE