(If the title doesn’t ring a bell, google it for some good-hearted laugh)

Today I would like to briefly discuss deletion.

Now, If you’ve been through any software interview lately, there are usually a lot of good and interesting questions about storing data. Should it be indexed? If so, how? Should it be SQL? no-SQL? How about cloud vs local storage? Replicated? Clustered?

It’s less often that deletion and deletion strategies are given the same depth of discussion. And yet, I’ve recently encountered a related challenge at work which has inspired this post. …

A diverse hiring process may not be what you think it is

Interview. Photo by cottonbro from Pexels

What does a diverse hiring process even mean?

I’m a woman. I’m bisexual. I’m trans. I’m a-spec (on the asexual spectrum). That would count as ‘diverse’ on several accounts.

Was there anything of real-world employment substance behind those titles though, given that I’ve spent over 15 years of my career performing as a man, 8 of those as a ‘DevOps guy’ and 4 as a ‘one man show’?

Stupid question, obviously. Tech is a meritocracy and a fair process evaluates solely on meritful criteria.


״It’s time to step up and do more. It’s not good enough to say we value diversity.״

- Brian Krzanich, Intel CEO

A fair process


System Design — When Coding Alone Doesn’t Cut it Anymore

Popularized by GAMFA companies (and considered a prerequisite skill for increasing levels of seniority), System design skills have become highly prized among developers. In a nutshell, system design is the practice of taking a problem expressed in real-world terms (e.g. “design a system that works like Twitter” or “design an efficient instant messaging system”) and translating it into real-world components and subsystems, without implementing them.

As GAMFA companies prove to be an inspiration, the practice of holding system design interviews has permeated through the industry as a testament to advanced delivery skills. …

In our last post, it seemed like we had full error coverage within our grasp.

Why aren’t we done? What is it that stops us from calling out every error our application makes as an event and raise it?

The amorphous nature of the term ‘error’.

True, some things are pretty much obvious errors. This usually applies to technical errors such as the infamous ‘500’ HTTP return code.

But our systems don’t just have to measure to technical standards. They have to be correct from a user’s perspective. What if our login button just turned invisible, for example?

Computers and…

In our previous posts, we’ve covered indicators and metrics. These were attributes of a system which we could define and observe. But we’ve also noticed that they have major limitations around analysis. Indicators supposedly circumvent this by virtue of definition and metrics by the operator’s analysis capability… surely there is something that has more context and detail. Assuming a problematic metric is flagged, we now need to look at the trail of happenings that preceded it. In fact, perhaps just knowing what were the events prior to the metric getting flagged would have sufficed and been more efficient.


If only monitored events could be this colorful and tasty. Alas, they are a different beast.



I wrote these a few months ago and now seems like a good place to post these.

TW: self-deprecating and dark trans-woman-in-tech humor.

(Modelled after excuses made to management, product and end users):


  • A woman, but not entirely up to spec [1]
  • A woman, but with some technical debt.
  • A woman, but next releases are going to be a lot more accurate.
  • A woman, but released with some P1 bugs.
  • A woman, but she doesn’t pass. acceptance tests.
  • A woman, at least according to project status
  • A woman, at least as written in the documentation.
  • A woman, but we…

In our previous post, we have dived into the lovely world of indicators and have explored its value but also its limits. These limits have clearly led us towards observable values that are past indicators. That’s also pretty intuitive, we have everyday examples of metrics.


If indicators were binary observables values, metrics are observables with a broader, more complex value.

Perhaps an example would work well for us here. The amount of fuel left in your car is one such example that comes to mind. This is a quantifiable value (liters or gallons) that can predict a problem (running out…

So, our previous post has defined monitoring for us. As a brief recap, our key takeaway was that good monitoring allows a human to derive insights about your business’ operation, in order to prevent or minimize damage.

In this post we will discuss the indicator, a basic and intuitive building block of monitoring systems. Chances are your monitoring strategy will include these and your code / component should keep these in mind.


So, indicators.

An indicator you do not want to see light up.

An idealized indicator is simply a binary value. On vs Off. Valid vs Invalid. Running vs Stopped. The forces of good uptime vs the forces of…


This series of posts is designed to let you, the reader, broaden your perspectives about the world of tech monitoring by way of a “from scratch” exploration.

As a ‘foundations’ series, this should hopefully prove useful to you regardless of your specific technical domain, even if the focus will be online software systems.

If you’re an ops person or an architect (or the manager of), this should help you evaluate your existing monitoring situation and perhaps gain some more ideas and insights.

If you’re a developer (or the manager of), this should help you empower your ops team and…

Gil Bahat

A Gil, of all trades. DevOps roles are often called “a one man show”. As it turns out, I’m not a man and never was. Welcome to this one (trans) woman show.

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