dramble

tl;dr: I successfully got the Intel I340-T4 4x Gigabit NIC working on the Raspberry Pi Compute Module 4, and combining all the interfaces (including the internal Pi interface), I could get up to 3.06 Gbps maximum sustained throughput.

Update: I was able to boost things a bit to get 4.15 Gbps! Check out my video here: 4+ Gbps Ethernet on the Raspberry Pi Compute Module 4.

After my failure to light up a monitor with my first attempt at getting a GPU working with the Pi, I figured I'd try something a little more down-to-earth this time.

And to that end, I present to you this four-interface gigabit network card from Intel, the venerable I340-T4:

I realized I haven't posted about my DrupalCon Seattle 2019 session titled Everything I know about Kubernetes I learned from a cluster of Raspberry Pis, so I thought I'd remedy that. First, here's a video of the recorded session:

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The original Pi Dramble 6-node cluster, running the LAMP stack.

 ____________________________________________
/ Fool me once, shame on you. Fool me twice, \
\ prepare to die. (Klingon Proverb)          /
 --------------------------------------------
        \   ^__^
         \  (oo)\_______
            (__)\       )\/\
                ||----w |
                ||     ||

(Excerpt from Ansible for DevOps, chapter 12.)

The fallout from this year's microSD card performance comparison has turned into quite a rabbit hole; first I found that new 'A1' and 'A2' classifications were supposed to offer better performance than the not-Application-Performance-class-rated cards I have been testing. Then I found that A2 rated cards offer no better performance for the Raspberry Pi—in fact they didn't even perform half as well as they were supposed to, for 4K random reads and writes, on any hardware I have in my possession.

Update: See follow-up post about A1 vs A2 performance, Raspberry Pi microSD follow-up, SD Association fools me twice?.

After I published my 2019 Raspberry Pi microSD card performance comparison, I received a lot of feedback about newer 'A2' Application Performance class microSD cards, and how they could produce even better performance for a Raspberry Pi.

None of these cards are fakes; grainy halftone printing is visible because I shot this with a macro lens.

Note: I also posted a separate review of some A2 'Application Performance' class cards, see this post: A2-class microSD cards offer no better performance for the Raspberry Pi.

As a part-time tinkerer and full-time developer, I have been fascinated by single board computers (SBCs) since the first Raspberry Pi was introduced almost a decade ago. I have owned and used every generation of Raspberry Pi, in addition to most of the popular competitors. You can search my site for tons of articles on these experiences.

Update: Since posting this, there have been some interesting new developments in this area, for example:

• There is now a Drupal/Kubernetes SIG which meets every other Wednesday.
• There are Kubernetes Drupal Operators which can manage Drupal instances in Kubernetes; I maintain the geerlingguy/drupal-operator but there are a couple others out there in development.

Since 2014, I've been working on various projects which containerized Drupal in a production environment. There have always been a few growing pains—there will for some time, as there are so few places actually using Docker or containers in a production environment (at least in a 'cloud native' way, without tons of volume mounts), though this is changing. It was slow at first, but it's becoming much more rapid.

If you're running Kubernetes clusters at scale, it pays to have good monitoring in place. Typical tools I use in production like Prometheus and Alertmanager are extremely useful in monitoring critical metrics, like "is my cluster almost out of CPU or Memory?"

But I also have a number of smaller clusters—some of them like my Raspberry Pi Dramble have very little in the way of resources available for hosting monitoring internally. But I still want to be able to say, at any given moment, "how much CPU or RAM is available inside the cluster? Can I fit more Pods in the cluster?"

So without further ado, I'm now using the following script, which is slightly adapted from a script found in the Kubernetes issue Need simple kubectl command to see cluster resource usage:

Usage is pretty easy, just make sure you have your kubeconfig configured so kubectl commands are working on the cluster, then run:

Over the past month, I started rebuilding the Raspberry Pi Dramble project using Kubernetes instead of installing and configuring the LEMP stack directly on nodes via Ansible (track GitHub issues here). Along the way, I've hit tons of minor issues with the installation, and I wanted to document some of the things I think turn people away from Kubernetes early in the learning process. Kubernetes is definitely not the answer to all application hosting problems, but it is a great fit for some, and it would be a shame for someone who could really benefit from Kubernetes to be stumped and turn to some other solution that costs more in time, money, or maintenance!

Back in 2015, I wrote a popular post comparing the performance of a number of microSD cards when used with the Raspberry Pi. In the intervening three years, the marketplace hasn't changed a ton, but there have been two new revisions to the Raspberry Pi (the model 3 B and just-released model 3 B+). In that article, I stated:

One of the highest-impact upgrades you can perform to increase Raspberry Pi performance is to buy the fastest possible microSD card—especially for applications where you need to do a lot of random reads and writes.

A few months ago, when I spoke at php[tek] in St. Louis, I had the honor of being interviewed by Cal Evans on the Voices of the elePHPant podcast! In the interview, we discussed Drupal 8, Acquia, the Raspberry Pi Dramble, and the PHP community.

Check out the interview: Interview with Jeff Geerling - Voices of the elePHPant.

There's also a video recording of the podcast, embedded below: