performance

tl;dr: Run composer require zaporylie/composer-drupal-optimizations:^1.0 in your Drupal codebase to halve Composer's RAM usage and make operations like require and update 3-4x faster.

A few weeks ago, I noticed Drupal VM's PHP 5.6 automated test suite started failing on the step that runs composer require drupal/drush. (PSA: PHP 5.6 is officially dead. Don't use it anymore. If you're still using it, upgrade to a supported version ASAP!). This was the error message I was getting from Travis CI:

I ran the test suite locally, and didn't have the same issue (locally I have PHP's CLI memory limit set to -1 so it never runs out of RAM unless I do insane-crazy things.

There are times when you may notice your MySQL or MariaDB database server getting very slow. Usually, it's a very stressful time, as it means your site or application is also getting very slow since the underlying database is slow. And then when you dig in, you notice that logs are filling up—and in MySQL's case, the slow query log is often a canary in a coal mine which can indicate potential performance issues (or highlight active performance issues).

But—assuming you have the slow query log enabled—have you ever grabbed a copy of the log and dug into it? It can be extremely daunting. It's literally a list of query metrics (time, how long the query took, how long it locked the table), then the raw slow query itself. How do you know which query takes the longest time? And is there one sort-of slow query that is actually the worst, just because it's being run hundreds of times per minute?

Lately I've been spending a lot of time working with Drupal in Kubernetes and other containerized environments; one problem that's bothered me lately is the fact that when autoscaling Drupal, it always takes at least a few seconds to get a new Drupal instance running. Not installing Drupal, configuring the database, building caches; none of that. I'm just talking about having a Drupal site that's already operational, and scaling by adding an additional Drupal instance or container.

One of the principles of the 12 Factor App is:

IX. Disposability

Maximize robustness with fast startup and graceful shutdown.

Disposability is important because it enables things like easy, fast code deployments, easy, fast autoscaling, and high availability. It also forces you to make your code stateless and efficient, so it starts up fast even with a cold cache. Read more about the disposability factor on the 12factor site.

I've had a long history playing around with Raspberry Pis and other Single Board Computers (SBCs); from building a cluster of Raspberry Pis to run Drupal, to building a distributed home temperature monitoring system with Raspberry Pis, I've spent a good deal of time testing the limits of an SBC, and also finding ways to use their strengths to my advantage.

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.

tl;dr: EFS is NFS. Networked file systems have inherent tradeoffs over local filesystem access—EFS doesn't change that. Don't expect the moon, benchmark and monitor it, and you'll do fine.

On a recent project, I needed to have a shared network file system that was available to all servers, and able to scale horizontally to anywhere between 1 and 100 servers. It needed low-latency file access, and also needed to be able to handle small file writes and file locks synchronously with as little latency as possible.

Amazon EFS, which uses NFS v4.1, checks all of those checkboxes (at least, to a certain extent), and if you're already building infrastructure inside AWS, EFS is a very cost-effective way to manage a scalable NFS filesystem. I'm not going to go too much into the technical details of EFS or NFS v4.1, but I would like to highlight some of the painful lessons my team has learned implementing EFS for a fairly hefty CMS-based project.

Today while I was running a particularly large Ansible playbook about the 15th time in a row, I was wondering why this playbook seemed to run quite a bit slower than most other playbooks, even though I was managing a server that was in the same datacenter as most of my other infrastructure.

I have had pipelining = True in my system /etc/ansible/ansible.cfg for ages, and initially wondered why the individual tasks were so delayed—even when doing something like running three lineinfile tasks on one config file. The only major difference in this slow playbook's configuration was that I had a local ansible.cfg file in the playbook, to override my global roles_path (I wanted the specific role versions for this playbook to be managed and stored local to the playbook).

So, my curiosity led me to a more thorough reading of Ansible's configuration documentation, specifically a section talking about Ansible configuration file precedence:

Pi Hole is a nifty open source project that allows you to offload the task of blocking advertisements and annoying (and often malicious) trackers to a Raspberry Pi. The installation is deceptively simple (a curl | bash affair), but I wanted to document how I set up mine headless (just plugging the Pi into power and the network).

Set up Raspbian Lite

I bought a Raspberry Pi model 2 B along with the official Raspberry Pi foundation Case. Then I bought a Samsung Evo+ 32GB microSD card (which comes with a full-size SD card adapter), and did the following steps on my MacBook Pro to set up the Pi's OS:

XHProf, a PHP extension formerly created and maintained by Facebook, has for many years been the de-facto standard in profiling Drupal's PHP code and performance issues. Unfortunately, as Facebook has matured and shifted resources, the XHProf extension maintenance tailed off around the time of the PHP 7.0 era, and now that we're hitting PHP 7.1, even some sparsely-maintained forks are difficult (if not impossible) to get running with newer versions of PHP.

Enter Tideways.

Tideways has basically taken on the XHProf extension, updated it for modern PHP versions, but also re-branded it to be named 'Tideways' instead of 'XHProf'. This has created a little confusion, since Tideways also offers a branded and proprietary service for aggregating and displaying profiling information through Tideways.io. But you can use Tideways completely independent from Tideways.io, as a drop-in replacement for XHProf. And you can even browse profiling results using the same old XHProf UI!

File this under the "it's a very bad idea, but sometimes absolutely necessary" category: I was working on a site that wanted to use a particular font for headlines throughout the site, but the client detested one particular character (an ampersand), and requested any time that character were to occur in the page title, it would be swapped out for a different font.

If at all possible, you should avoid doing what I'm about to describe—but in the off chance you need to have an automated way to scan a string of text and change the font family for one particular character, this is what to do:

First, you need to create a special CSS class that you can apply to the individual character, so in your theme's CSS, add something like: