Scaling Organizations - Scribing

In the process of growing a company there’s several hurdles based on the size of the company. What worked at 5 doesn’t work at 20, what works at 20 doesn’t work at 50, and what worked at 50 doesn’t work at 150. There’s a lot of talk about two pizza teams and scaling development teams out there. One thing I haven’t seen quite enough of is details around scribing and documenting things.

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Postgres and Connection Pooling

Connection pooling is quickly becoming one of the more frequent questions I hear. So here’s a primer on it. If there’s enough demand I’ll follow up a bit further with some detail on specific Postgres connection poolers and setting them up.

The basics

For those unfamiliar, a connection pool is a group of database connections sitting around that are waiting to be handed out and used. This means when a request comes in a connection is already there whether in your framework or some other pooling process, and then given to your application for that specific request or transaction. In contrast, without any connection pooling your application will have to reach out to your database to establish a connection. While in the most basic sense you may thinking connecting to a database is quick, often theres some overhead here. An example is SSL negotiation that may have to occur which means you’re looking at not 1-2 ms but often closer to 30-50.

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Personas, Data Science, K-means

If one of the industry lingo terms in title didn’t make your skin crawl a little then I need to try harder. At the same time you’ve probably heard someone use one of them in a non-trolling way in the last month. All three of these can often actually mean the same or similar things, it’s just people approach them differently from their world perspective.

Personas don’t have to be marketing only speak, and data science doesn’t have to be only for stats people. My goal here is to simply set a context for the rest of the meat which talks about how you can simply look at your data and let it surface things you may not have known. Read on

Postgres Datatypes – the Ones You’re Not Using.

Postgres has a variety of datatypes, in fact quite a few more than most other databases. Most commonly applications take advantage of the standard ones – integers, text, numeric, etc. Almost every application needs these basic types, the rarer ones may be needed less frequently. And while not needed on every application when you do need them they can be an extremely handy. So without further ado let’s look at some of these rarer but awesome types.

hstore

Yes, I’ve talked about this one before, yet still not enough people are using it. Of this list of datatypes this is one that could also have benefit for most if not all applications. Read on

What You Need to Know About April 7 and Your Security on the Web.

On April 7 a vulnerability, nicknamed heartbleed, was discovered in a programming library that helps power somewhere over half of the internet. In the most basic sense this library allowed intentional external parties to acquire data that was thought to be safe and secure from whomever was running a vulnerable website. There was little to know one that was except from this due to their security practices, major examples of sites that were affected include:

  • Yahoo
  • Amazon.com
  • Netflix
  • Various banks
  • Many more

If you’re interested in more technical details you can follow along or on the Heroku blog.

The short of it is you, yes you as in everyone, should rotate your passwords once all websites are safe. For further details please continue reading.

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Some Non-traditional Marketing Tips

Marketing is generally unexciting to a ton of engineers, until it brings eyeballs which bring feedback and dollars. Marketing doesn’t have to always be cheesy campaigns or ads, it can often just be surfacing the things your customers actually do want to care about. My favorite type of marketing is when a service sells me on something at the exact time I want it. Here’s a few short tips on some non-traditional marketing that won’t seem sleezy but still can work quite well.

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A Year’s Look at Postgres

A couple years back I started more regularly blogging, though I’ve done this off and on before, this time I kept some regularity. A common theme started to emerge with some content on Postgres about once a month because most of what was out there was much more reference oriented. A bit after that I connected with petercooper, who runs quite a few weekly email newsletters. As someone thats been interested helping give others a good reason to create content the obvious idea of Postgres Weekly emerged.

Since then we’ve now had the newsletter running for over a year, helped surface quite a bit of content, and grown to over 5,000 subscribers. First if you’re not subscribed, then go subscribe now.

And if you need some inspiration or just want to reminisce with me… here’s a look back at a few highlights over the past year:

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PostgreSQL 9.4 - Looking Up (With JSONB and Logical Decoding)

Just a few weeks back I wrote a article discussing many of the things that were likely to miss making the 9.4 PostgreSQL release. Since that post a few weeks ago the landscape has already changed, and much more for the positive.

The lesson here, is never count Postgres out. As Bruce discussed in a recent interview, Postgres is slow and steady, but much like the turtle can win the race.

So onto the actual features:

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Tracking Month Over Month Growth in SQL

In analyzing a business I commonly look at reports that have two lenses, one is by doing various cohort analysis. The other is that I look for Month over Month or Week over Week or some other X over X growth in terms of a percentage. This second form of looking at data is relevant when you’re in a SaaS business or essentially anythign that does recurring billing. In such a business focusing on your MRR and working on growing your MRR is how success can often be measured.

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PostgreSQL 9.4 - What I Was Hoping For

Theres no doubt that the 9.4 release of PostgreSQL will have some great improvements. However, for all of the improvements it delivering it had the promise of being perhaps the most impactful release of Postgres yet. Several of the features that would have given it my stamp of best release in at least 5 years are now already not making it and a few others are still on the border. Here’s a look at few of the things that were hoped for and not to be at least until another 18 months.

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