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Category: Work

Where do you see yourself in five years?

Seriously, HR people ask the weirdest questions.

“Where do you see yourself in five years?”

For a Twentysomething with no owned property and no family the truthful answer is of course “In a different company, twice removed. Not because you suck more than anywhere else, but, like, statistically.”

“Where do you see yourself in five years?” “Week 27 or 28?” — LionKingLee

That time when you finish school and university and before you settle down with dependencies that make you immobile – it is an important time in your life. Use it wisely: Change jobs every two to three years, and make it count.


The company as a social engine

So why is everything so complicated? At work, I mean.

Think of a small company. A single person, a founder, is building her business. She knows her way around, it’s all in her head: The plan, the things that are important and why, and how they are to be executed. Also, tradeoffs to be corrected later, potential opportunities for later and a lot of other meta: Stuff that does not get executed right now, but that informs decisions, priorities and preferences. Things work with some precision, though, like a well programmed wetware CPU.

The moment that stuff becomes too large for a single person to handle, more people are involved and things need to be verbalized, written down, given form.

At that point, things change quite a bit:


On collecting the right kind of data

So Microsoft just blogged this:

Transform your organization with Microsoft Workplace Analytics

Workplace Analytics taps into Office 365 email and calendar metadata, including to/from data, subject lines and timestamps, to shine a light on how the organization collaborates and spends time. It turns this digital exhaust—the data that comes naturally from our everyday work—into a set of behavioral metrics that can be used to understand what’s going on in an organization.

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So Soundcloud is unwell, financially, and has laid off 173 people, about 40% of their workforce. Such things are never welcome, and usually they are sad affairs.

Except when somebody throws a bunch of Data Scientists, ML people or Backend people into the water. Check out the thread below this tweet:


Data Scientists in the water, the Pi-HR-anhas have a feeding frenzy.

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A case for IP v6

So when companies talk about IP V6, it is very often at the scope of “terminating V6 at the border firewall/load balancer and then lead it as V4 into the internal network. Problems that arise there are most often tracking problems (»Our internal statistics can’t handle V6 addresses in Via: headers from the proxy«).

But when you do containers, the need for V6 is much more urgent and internal. Turns out that Docker Port Twiddling is exactly the nuisance that it looks like and networkers strongly urge you to surgically remove all traces of native Docker networking bullshit and go all in on IP-per-Container. Mostly, because that’s what IPs are for: Routing packets, determining their destination and stuff. Networkers have ASICs and protocols that are purpose-built for this stuff.

Now, let us assume you have a modern 40- or 56-core machine that you are running stuff on in your Kubernetes cluster. It means that you will easily at least 30 and up to 100 pods per machine. In a moderately sized cluster with some 100 nodes you get to use 100×100, 10.000 IPs to handle that. And because IP space is not handed out in sets of one, but in the form of subnets per node, you will have need for more than 10k addresses. Expect to consume a /17 or /16 to handle this.

Even if you are digging into 10/8 for internal addressing here, this is going to be a problem – it’s unlikely that you will be able to use all of 10/8, because non-cluster things exist, too, in your environment, and you will likely have more than one cluster.

With V6, things are becoming a complete non-issue, with the minor issue of getting V6 running on the inside of your organisation.

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Xing, srsly?

If you contacted me on Xing, and wondered why I did not react: It’s mosty because I have stopped caring about the platform. At all.