fidzu : Drupal

DrupalCon brings love in every drop

Rachel Tue, 10/06/2026 - 21:19

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06 Oct 2026 8:19pm GMT

Meet Dashi, the 'new' multilingual demo for Drupal CMS

Gábor Hojtsy Tue, 10/06/2026 - 17:17

06 Oct 2026 2:17pm GMT

Introduction

Adopting AI can feel overwhelming, so I am sharing a few tales from my experience creating, maintaining, and assisting with contributed Drupal modules. AI can do a decent job building a "greenfield" Drupal module from scratch, so my first tale is about using AI to build and contribute a module. For my next tale, I want to talk about using AI to maintain an existing "brownfield" Drupal module.

Growing up in NYC, I found brownfields often intimidating, with some so toxic that it can take years for backhoes and dump trucks to remove the contaminated topsoil before construction can begin. With code, a brownfield can contain technical debt, orphaned code, missing tests, etc. Simply put, a brownfield contains unknowns, which means more things can go wrong while working on it. Sometimes a brownfield is so big you need heavy machinery to maintain it, and that is exactly how I felt about using AI on the Schema.org Blueprints module.

Maintaining a large module using AI

Gradually, I have been experimenting with AI to help maintain the Schema.org Blueprints. At first, I would just throw a one-shot prompt at the AI to address a single issue, and it would do a decent job diagnosing and resolving the problem. As I became more confident steering the AI, I started asking it to create issue forks, commits, pushes, and even MRs. As I previously stated in my AGENTS.md I always have "Require me to review all changes before committing and pushing code." and most models respect this rule.

My comfort level reached a point where I am creating {module}-issue-maintenance agent skills that extend my drupalorg-issue-maintenance skills. These maintenance skills have agents to track remote issues in...Read More

06 Oct 2026 9:40am GMT

Drupal 12 and the End of Legacy Debt: A Forced Modernization for Enterprise Engineering bhavinhjoshi Tue, 10/06/2026 - 14:02

06 Oct 2026 8:32am GMT

The National Center for Family Philanthropy worked with DevCollaborative to reimagine their website, CRM, and other communications channels to effectively manage and scale their network of over 500 philanthropic families representing more than 3,000 individuals.

06 Oct 2026 6:53am GMT

The tools around Drupal have become simpler, complementing Drupal. Read our take on how Canvas, components, Drupal CMS, and AI are changing Drupal work.

06 Oct 2026 5:39am GMT

AI is becoming part of almost every software platform, and content management systems are no exception. Drupal is no different. But there is an important question that often gets lost in the excitement around AI: if Drupal already manages content so well, what exactly does AI add?

06 Oct 2026 2:41am GMT

TL;DR

macOS Docker provider performance has improved significantly over the years, and now all the providers seem to be performing about equivalently. So OrbStack, Docker Desktop, Lima, Colima, and Rancher Desktop are fast and working well.

Introduction

Back in November 2023 we published a hand-run comparison of macOS Docker providers. It was a snapshot: one laptop, one afternoon, one set of versions, and a Google Sheet. It answered the question people were asking, and then it started going stale the moment it was published.

That post is gone now, and this one replaces it, because the way we answer the question has changed. DDEV now runs the same benchmark battery every night, unattended, on every platform and Docker provider we support, and publishes the accumulated history.

Table of Contents

Where to see the numbers

The nightly results live at the DDEV performance history dashboard.

The easiest way to find it (and everything else the DDEV GitHub organization publishes) is to start at github.com/ddev/ddev.github.io and follow the "Performance History" link. That repo's README is the index of DDEV's GitHub Pages sites - bookmark it and you don't have to remember any of the other URLs.

The dashboard has two views. Trend over time plots one line per leg so you can see regressions and improvements as they land. Compare environments (latest) gives you a sorted bar chart of each environment's recent median, which is the view that most directly replaces the 2023 post's charts.

Which metric to compare

The harness collects six metrics per run. The one that lines up with the 2023 post is drupal_install_s: Puppeteer drives the Drupal web install wizard end-to-end, in a real browser, through the DDEV router, the web server, and PHP-FPM.

I think it's important that it uses a web-intensive install process for studying web server performance. The interactive installer deliberately breaks each batch step into its own HTTP request and page reload, so every one of those round trips exercises exactly the layer where Docker provider differences show up - bind mount vs. Mutagen, gRPC-FUSE vs. virtiofs, and so on. It's the closest thing in the suite to "what does it feel like to actually use this."

The companion metric drush_install_s runs the same install non-interactively via ddev drush si, which never touches the router or web server at all. If the two track together, filesystem I/O dominates; if they diverge, the gap isolates router/web server overhead. The perf/README.md describes all six metrics and why each one is there.

macOS results

Medians of the nightly runs from 2026-08-31 through 2026-09-30, drupal_install_s in seconds, fastest first. All legs are Apple Silicon (ARM64), all with Mutagen enabled except where noted.

The headline is how boring this table is. Five of the six Mutagen-enabled macOS providers land within 1.4 seconds of each other on the flagship metric, and their drush_install_s numbers are within 0.6 seconds. On macOS with Mutagen, your choice of Docker provider is mostly not a performance decision anymore. Pick based on licensing, maintenance, and how the tool fits your workflow.

That is a significant change from 2023, when OrbStack was clearly ahead and Colima and Rancher Desktop looked sluggish. Those gaps have largely closed (all are now using VZ/VirtioFS).

Compared with the 2023 numbers

The 2023 test did a Drupal 10 web install with Mutagen and got OrbStack 20s, Docker Desktop 22s, Rancher Desktop 22s, Colima QEMU 33s, and Colima VZ 35s. The fastest then (OrbStack, 20s) compares with 12.0s for the fastest now (Rancher Desktop), and with 13.4s for OrbStack. The slowest providers gained the most: Rancher Desktop went from 22s to 12.0s and Colima VZ from 35s to 12.6s. The spread between providers went from 15 seconds to about 1.4 (excluding Docker Desktop).

Treat these as a rough comparison, not a like-for-like benchmark. The 2023 numbers came from one MacBook Air M1 (2020) on a single afternoon, with DDEV v1.22.5, Drupal 10.1.6, and PHP 8.1. The nightly runs use CI runner machines, and newer DDEV, Drupal, and PHP versions. Both tests drive the demo_umami install through Puppeteer. Each Docker provider has also shipped many releases since 2023, and the Colima leg now uses VZ where one of the 2023 legs used QEMU with sshfs. Some of the improvement comes from the hardware, and some from the software.

When DDEV was young, a web install with Docker Desktop took SEVEN MINUTES. You'd just watch it poke along at each section. Now you don't even see those as they flash by. Now it takes 12-17 seconds. That's progress!

Mutagen is still doing the work

The most interesting row is the last one. OrbStack with Mutagen finishes the browser install in 13.4s; the same provider without Mutagen takes 16.8s - about 25% slower. Note that the no-Mutagen leg is faster on ddev_start_cold_s (9.2s vs. 12.2s), because there's no sync session to establish, and closer on drush_install_s (11.2s vs. 10.4s), because Drush never goes through the web server. The penalty concentrates in exactly the browser-driven path, which is what you use all day.

Mutagen is on by default on macOS for this reason, and these numbers say to leave it on.

However, plenty of people are perfectly happy with turning off Mutagen. Some folks don't like the additional complexity and don't want the speed trade-off. ddev config global --performance-mode=none turns it off. (Mutagen has more benefits than just performance though; with Mutagen, the web server in the container is dealing with a Linux filesystem, more like the real deployment environment, instead of a Docker bind-mount, which is more like a network filesystem.)

:::warning[Read the hardware caveat before comparing rows] The Docker Desktop leg runs on older M1 test runner machines that have dedicated hardware. OrbStack, Rancher Desktop, Colima, Lima, and Podman share a pool of newer machines. Some of the Docker Desktop gap in the table above is that hardware difference, not the provider. We didn't normalize it - the dashboard deliberately doesn't either - so treat Docker Desktop's row as "somewhat pessimistic" rather than as a clean like-for-like comparison. :::

The other platforms, and why you shouldn't rank them against macOS

The dashboard also carries Linux, WSL2, and traditional Windows legs. They're useful for spotting regressions within a leg over time, but the cross-platform bar chart is misleading if you read it as a platform ranking:

• The Linux leg runs on ephemeral GitHub-hosted runner VMs. It provisions the Drupal codebase from scratch every night and starts with cold image, Composer, and OS page caches. Every macOS and Windows leg reuses a persistent codebase and warm caches.
• The Windows and WSL2 legs run on entirely different physical hardware from the macOS test runners.

Trends within a leg: meaningful. Bar-chart comparisons across legs: only meaningful when the machines are comparable, which across platforms they aren't.

Getting the raw data

Every chart on the dashboard has a Download CSV button that exports exactly the rows behind whatever is currently displayed - after your leg and metric selections, not the whole dataset. That's the quickest path to your own analysis.

If you want everything, the underlying dataset is one JSON object per line at history.ndjson, with one line per (commit, leg) benchmark run:

curl -sL https://ddev.github.io/ddev/perf/history.ndjson |
  jq -r 'select(.os=="darwin") | [.timestamp, .docker_provider, .metrics.drupal_install_s] | @tsv'

Running it on your own machine

The harness that replaced the old ddev-puppeteer script lives in the DDEV repository and runs locally against a standard DDEV Drupal project:

./perf/run-benchmark.sh \
  --project-dir ~/workspace/d11 \
  --site-url https://d11.ddev.site/ \
  > result.json

It needs jq and Node.js on your PATH in addition to the usual DDEV prerequisites. If your numbers look very different from the nightly legs, we'd like to hear about it.

Summary

Three years ago the answer to "which Docker provider is fastest on macOS?" was worth a blog post with charts. Today the simple answer is that, with Mutagen on, they're close enough that the question is mostly settled, and any lingering differences are small next to the hardware you're running on.

What's better than a fresh answer is a standing one. The nightly harness means the next time performance shifts - a provider regression, a Mutagen improvement, a DDEV build-layer mistake - it shows up on the dashboard within a day, instead of waiting for somebody to run the numbers by hand and write another post.

Have questions, or numbers that look different from the dashboard? Join the conversation in our Discord, open an issue, or reach out via email.

Follow our blog, Bluesky, LinkedIn, Mastodon, and join us on Discord. Sign up for the monthly newsletter.

This article was edited and refined with assistance from Claude Code.

06 Oct 2026 12:00am GMT

Beyond Bigger Servers: Keeping Websites Online Under Bot Attacks

John Locke Mon, 10/05/2026 - 15:00

Dev Corner

05 Oct 2026 10:00pm GMT

WordPal: Theme Drupal with WordPress block themes

theodore October 5, 2026

05 Oct 2026 6:30pm GMT

After Rotterdam, one part of Drupal's AI story is no longer theoretical. The Northmoor University demo brought AI search, content review, translation, editing and externally connected assistants together on the same Drupal site. That made a collection of modules feel closer to a product experience, but it also exposed the next question: whether organisations can depend on the path between those pieces in production.

The stack does not yet sit at one level of maturity. Drupal AI 1.5 and Canvas are stable and covered by Drupal's security advisory policy. Context Control Center is a release candidate, while Tool API and MCP Server remain in beta. Rotterdam showed that these parts can work together. Production teams now have to decide which combinations are mature enough to trust, govern and support.

Permissions, human review and traceability are central to that decision. The demo drafts changes rather than publishing them, leaving a person to review what the AI proposes. Tool API brings access checking into executable capabilities, while MCP can expose Drupal tools to assistants outside the site. Context Control Center moves instructions and organisational knowledge toward managed, reviewed material. Taken together, those pieces point toward a production requirement that goes beyond capability: teams need to know what an agent may read, what it may change, which tools it may invoke, what context it received and who remains accountable for the result.

Provider choice and the connection between Tool API, MCP and Canvas make the remaining maturity gap visible. Drupal's provider abstraction supports different commercial and locally operated models, but workflows still need to remain testable as model behaviour, tool calling and context limits change. The Drupal AI Initiative's follow-up also draws a clear line between what Rotterdam demonstrated and what is available today: the simplified MCP approach shown on stage remains a prototype. Canvas Tools, which lets agents manipulate Canvas through Tool API, is likewise still beta and is not covered by the security advisory policy.

That does not make Drupal AI simply ready or not ready for production. Different parts of the stack already support different kinds of real use, with different levels of risk. Rotterdam instead changes what Drupal AI now has to prove: that permissions remain enforceable, context can be governed, costs and activity can be traced, providers can change without losing control, and interfaces can survive upgrades. Productisation does not mean closing the ecosystem or putting everything inside one package. It means reaching the point where an organisation can understand what an AI system will be allowed to do before deployment, and explain what it actually did afterwards.

Follow The DropTimes on LinkedIn, X, Bluesky, and Facebook, or join #thedroptimes on Drupal Slack.

Allen Jason wrote and curated this issue of Editor's Pick.

05 Oct 2026 2:30pm GMT

A handwritten board at DrupalCon Rotterdam carried more than vacancy notices. Attendees could also recommend community members actively looking for their next Drupal role.

05 Oct 2026 1:16pm GMT

Drupal AI Context first release candidate The first release candidate (RC 1) of Drupal AI Context , also known as Context Control Center (CCC), is now available. This is a major milestone for the project. After five beta releases and months of community testing, refinement and expansion, RC 1 marks the final stage before the first stable 1.0 release. We're currently planning to release CCC 1.0 in about a month, subject to what we learn from testing the release candidate. There may also be an RC 2 release prior to 1.0. CCC helps Drupal sites provide governed, reusable context to AI-powered features, from brand voice and editorial standards to organisational knowledge, governance rules and other information that AI systems need to work effectively.

05 Oct 2026 12:00pm GMT

FlashFloodBreaker partner meeting in Metz: 1xINTERNET shares digital and regional resilience insights to help improve Europe's response to extreme flash floods.

05 Oct 2026 12:00pm GMT

Prevent the AI skills gap from becoming an expanse The rapid pace of updates, new versions and new Drupal core and contrib module functionality of the past 5 years almost feels like a crawl compared to the "high-velocity production model" guiding The Drupal AI initiative . It has screamed past beta versions and into an enterprise ecosystem boasting more than 15,000 installs, funding totaling in the $millions (USD,) as well as dedicated product streams like Inside AI and Outside AI; all in just over a year of its official launch. In addition, the community has about made it beyond the debate of if , and are now comfortably addressing the reality of how to best, (and importantly,) responsibly employ Drupal AI so that it contributes to not just efficiencies, but to improved workflows, outcomes and ultimately the bottom line; both Inside and Out . That, after all, is the measurement used in the viability of any new product or process. Astutely, the effort is grounded in the mission: " …to

05 Oct 2026 10:31am GMT

The migration launched and traffic is falling. The eight causes in the order to check them, what Search Console tells you, how long recovery takes, and when to roll back.

05 Oct 2026 7:00am GMT