🧵 Two of my most- and first-used checks when doing a performance audit are surprisingly old school: 1) Validate HTML 2) Disable JS.

🕵️‍♂️ How Google's PageRank algorithm works

The PageRank algorithm gives each page a rating of its
importance, which is a recursively defined measure of importance, based on if important pages link to it.
It's recursive because the importance of a page refers back to the importance of other pages that link to it

Here's how it works in practice:
1⃣ We start with some pages and crawl them for links

2⃣ Each page has 1/N points (where N as the total number of pages)

3⃣ Add points to each page for the amount of links to it, divided by the number
of links emanating from the sources of these links

~8yrs ago (Dec’12) I got a job @Google. Those were still early days of cloud. I joined GCP @<150M ARR & left @~4B (excld GSuite). Learned from some of the smartest ppl in tech. But we also got a LOT wrong that took yrs to fix. Much of it now public, but here’s my ring-side view👇

By 2008, Google had everything going for it w.r.t. Cloud and we should’ve been the market leaders, but we were either too early to market or too late. What did we do wrong? (1) bad timing (2) worse productization & (3) worst GTM.

We were 1st to “containers” (lxc) & container management (Borg) - since '03/04. But Docker took LXC, added cluster management, & launched 1st. Mesosphere launched DCOS. A lot of chairs were thrown around re: google losing this early battle, though K8 won the war, eventually 👏

We were 1st to “serverless” (AppEngine). GAE was our beachhead -- it was the biggest revenue source early on but the world wasn’t ready for serverless primitives. We also didn’t build auxiliary products fast enough. Clients that outgrew GAE wanted “building block” IaaS offerings.

1st to hadoop (map-reduce ‘04) but our hosted Hadoop launched in ‘15. AWS EMR was ~200M ARR by then. 1st to cloud storage (GFS ’03), but didn’t offer a filestore till ‘18! Customers were asking for it since 2014. Didn’t launch archival storage or direct interconnect till v. late.

#UX and #design friends, we need to talk about estimating. I'd like to share some advice that's come up 3 times this week, in hopes it's useful. And it's echoed, by the way, in the BUSINESS OF UX course @EliNatoli and I are teaching at my UX 365 Academy (link at the end).

(1/12)

Avoiding wars with clients is a matter of how you structure your engagements, along with how you spell out what you're doing in your proposals/contracts. That starts with estimating.

The biggest 2 rules I follow are these:

(2/12)

1. I do not EVER estimate a project in full from start-to-finish.

2. Once we're past initial Discovery (see below), I estimate in small chunks, e.g. "here's what will take us to the next iteration/review."

(3/12)

NEVER estimate past the point where you may get new information based on a build/test cycle.

Believe me when I say that you'll be wrong every time. Ask me how I know ;-)

(4/12)

So instead, first, I estimate a Consult/Discovery part that details what I think we need to do to get a handle on what's actually wrong here, and how long that will take.

For example...

(5/12)

A quick thread on intelligence analysis in the context of cyber threat intelligence. I see a number of CTI analysts get into near analysis paralysis phases for over thinking their assessments or over obsessing about if they might be wrong. (1/x)

Consider this scenario. A CTI analyst identifies new intrusions and based on the collection available and their expertise note that the victims are all banks. Their consumer wants to know when threats specifically target banks (not just that banks are victims).

The CTI analyst has, from their collection, at this time, and based on their expertise enough to make an activity group (leveraging the Diamond Model in this example) that meet's the requirement of their consumer. So what's the problem?

The CTI analyst begins to over think it. "What if I had more collection? Would my analysis change? I really don't *know* they aren't also targeting mining companies in Australia as I don't have collection there."

The analyst knows their analysis is going to be shared. Maybe even public. "What if another team or professional intelligence firm has more collection and ends up noting that it isn't banking specific at all. Banks are victims, not targets. Will my consumer distrust me later?"