Igalia celebrates “Twenty-Five Years Upstream”

Post Syndicated from jake original https://lwn.net/Articles/1095723/

The open-source consulting firm Igalia has put out an
announcement celebrating 25 years of working on upstream FOSS projects
for its clients. The list of projects the company has worked on is rather
eye-opening: WebKit, mobile-browser rendering (on Maemo, Moblin, MeeGo, and
Tizen), the Linux kernel (CPU and GPU scheduling), 3D graphics drivers, the
Orca screen reader,
GStreamer, and lots more. Beyond that, the company, which is a
worker-owned cooperative, does its work in ways that benefit the community
as well as its clients:

None of this is charity. Igalia is a consultancy, and most of the work above was paid for by someone with a product to ship: a device maker who needs the web to run well on their hardware, a platform that needs a feature its users keep asking for, a company whose roadmap depends on something deep in the stack working better than it does today. What they get from us is not a patch to carry forever. We do the work upstream, in the project itself, so it arrives in the next release and keeps working long after the contract ends. Our customers ship products built on code that nobody has to maintain alone, and everyone else gets the same code. That has been the arrangement from the start.

AWS Weekly Roundup: AWS Builder Center mobile apps, Amazon Connect Talent GA, Amazon Corretto 27, and more (September 21, 2026)

Post Syndicated from Esra Kayabali original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-aws-builder-center-mobile-apps-amazon-connect-talent-ga-amazon-corretto-27-and-more-september-14-2026/

Living in the Netherlands, I spend a fair amount of time on trains, and that is usually where I catch up on what the builder community is writing. Until now, that meant opening a laptop or squinting at a browser tab on my phone. This week I found myself scrolling through trending articles and checking a workshop from the AWS Builder Center mobile app while waiting for a delayed train, and it made those spare twenty minutes very useful. That is why I am glad to open this week with the Builder Center mobile app.

AWS Builder Center is now available as a mobile app on iOS and Android, extending the experience beyond desktop and web. Using your AWS Builder ID, you stay signed in across sessions and can browse trending articles, access 600+ AWS Skill Builder courses, and manage hands-on workshops with free sandbox environments from your mobile device. You can follow AWS Heroes, Community Builders, and User Group Leaders, check Builder Loft event calendars on the go, and receive push notifications for subscribed topics and communities. The app also supports the Wishlist feature for submitting product feedback directly to AWS teams. It is available worldwide on the Apple App Store and Google Play Store.

Builder Center also added two features this week. Polls give you a way to ask the community a question from the Home feed: write a question, add 2 to 5 answer options, set a deadline, and people vote, with results updating live and discussion happening in the comments. Votes are anonymous, and creators see aggregate counts and percentages only. Separately, the Zero to Shipped hackathon is open from September 18 to October 2. You connect your coding agent to AWS, build a real application, and ship it live on AWS for a chance to win a share of a $28,000 prize pool. Five winning projects each receive $5,000 in AWS credits and an AWS Builder swag bundle.

Last week’s launches

Here is what else happened this week.


  • Amazon Connect Talent is now generally available – Amazon Connect Talent is an AI-powered hiring solution for talent acquisition teams managing hiring at scale. Informed by decades of Amazon hiring science, it uses AI agents to conduct structured voice interviews, administer evidence-based assessments, and score candidates consistently, so recruiters can focus on final decisions. Candidates interview 24/7 from any device, and recruiters review scores, transcripts, and detailed evaluations the next morning. All candidate data is anonymized during AI evaluation, each competency is scored against a rubric with every score tied to specific evidence from the interview, and recruiters keep final decision authority over every hire. General availability includes competency-based assessments, AI-led voice interviews with adaptive questioning, a brand-customizable mobile-first candidate portal, and admin onboarding tools.
  • Amazon Corretto 27 is now generally available – Amazon Corretto 27, a Feature Release version of the no-cost, multi-platform distribution of OpenJDK, is now available for download on Linux, Windows, and macOS, with support through April 2027. Notable features include G1 as the default garbage collector across all environments (JEP 523), post-quantum hybrid key exchange for TLS 1.3 (JEP 527), compact object headers by default for a smaller memory footprint (JEP 534), and JFR in-process data redaction to remove sensitive data from Java Flight Recorder recordings before they leave the JVM (JEP 536). It also continues previews of enhanced pattern matching, structured concurrency, and lazy constants, along with the Vector API incubator.
  • Kimi K3 by Moonshot AI is now generally available on Amazon Bedrock – Kimi K3 is now available on Amazon Bedrock for coding and knowledge work. According to Moonshot AI, Kimi K3 is its most capable model and the first open model to reach 2.8 trillion parameters. It combines native vision capabilities with a 1-million-token context window, making it well suited to long-running coding sessions across large repositories, multi-document analysis, and extended agent workflows. Moonshot AI reports an approximate 2.5x improvement in scaling efficiency over Kimi K2. Kimi K3 is the first open-weight model on Amazon Bedrock to support explicit prompt caching, which helps reduce latency and input costs when reusing context across model calls.
  • AWS reimagines the getting started experience – We announced a new simplified experience for builders starting a new project. Instead of completing configuration tasks first, you start with sensible defaults: sign up using an existing identity from providers including Google, GitHub, and Apple, and for most new customers no credit card is required, with $100 in free credits as part of the AWS Free Tier. AWS organizes your work in a project, which contains an AWS account and sharing settings, and applies security controls for you. You can invite collaborators by email without setting up IAM users, set a monthly spend limit starting at $20, and activate advanced AWS features later at no additional cost with no migration. The experience is gradually rolling out to new customers.
  • New low-cost burstable Amazon EC2 T8i instances are generally available – Amazon EC2 T8i instances, powered by custom sixth-generation Intel Xeon Scalable processors (Granite Rapids), are among the lowest-cost EC2 instances and deliver up to 30% better price performance over previous-generation T3 instances. They are designed for low-to-moderate CPU utilization workloads such as microservices, low-traffic websites, development and testing environments, and small databases. T8i instances deliver up to 70% higher compute performance, up to 1.25x higher network bandwidth, and up to 2.4x higher Amazon EBS bandwidth compared to T3, and they use the same CPU credit system, so upgrading from T3 is straightforward.
  • AWS Elastic Beanstalk introduces Cluster Mode – AWS Elastic Beanstalk Cluster Mode is a new fully managed option for teams running a portfolio of applications on shared infrastructure powered by Amazon EKS. Instead of operating each application in isolation, you run multiple applications through one experience with a single operational baseline, so per-application cost decreases as your portfolio grows. You can upload source code in Java, .NET, Python, Node.js, PHP, Ruby, or Go, and Elastic Beanstalk handles containerization automatically through Cloud Native Buildpacks when needed. Cluster Mode includes production-grade deployment strategies with automatic rollback, event-driven autoscaling, AWS Secrets Manager integration, native OpenTelemetry observability, and AI-powered troubleshooting. Standard and Cluster Mode environments run side by side within the same application, so teams can migrate one environment at a time.

For a full list of AWS announcements, be sure to keep an eye on the What’s New with AWS page.

Other AWS news

Here are some additional posts you may find useful:

  • Building in the AWS European Sovereign Cloud – Two new posts cover building on the AWS European Sovereign Cloud, an independent cloud for Europe that runs as a distinct partition with its own control plane, IAM, billing, console, and service endpoints, and its first Region in Brandenburg, Germany. The first post walks through architecting a secure landing zone, covering account structure and governance, identity as infrastructure as code, centralized logging, data protection, and partition-aware ARN construction that works across AWS partitions. The second announces the general availability of Gemma 4 open-weight models on the Amazon Bedrock next-generation inference engine in the AWS European Sovereign Cloud, with inference staying entirely within eusc-de-east-1 under a zero data retention and zero operator access model.
  • The new AgentCore runtime: elastic, optimized, and consistently fast starts – We announced a new version of the Amazon Bedrock AgentCore runtime, the managed compute layer for running agents. The new runtime reclaims memory as a session releases it rather than holding it at the peak, so the bill tracks real usage over the life of a session. It also delivers consistent cold start times regardless of container image size or concurrency by preparing the environment once, snapshotting it, and restoring that snapshot for each new instance. In testing with an empty echo agent, the new runtime delivered a P75 cold start of about 2 seconds from a 200 MB image up to 2 GB, compared to roughly 5.4 to nearly 30 seconds for the original runtime.
  • Introducing the updated AWS Well-Architected Streaming Media Lens – We published a revised Streaming Media Lens, which provides architectural best practices for video streaming workloads. The revision expands from the original 2021 version to cover five streaming scenarios, including interactive live streaming with Amazon IVS Real-Time Streaming for up to 25,000 concurrent viewers, low-latency live streaming, and ad-supported content monetization, alongside enhanced video-on-demand and live streaming guidance. It also adds new sustainability best practices focused on reducing carbon footprint, expanded observability and incident-response frameworks, and advanced content protection with multi-layered DRM and forensic watermarking. The lens whitepaper and custom lens are available now.

For a full list of AWS blog posts, be sure to keep an eye on the AWS Blogs page.

Upcoming AWS events

Check your calendar and sign up for upcoming AWS events:

  • AWS re:Invent – AWS re:Invent returns to Las Vegas from November 30 to December 4. 2, 200+ session times, locations, and speakers are live. Reserved seating for AWS re:Invent opens October 6. Register now and be ready to claim your spot in chalk talks, workshops, and builders’ sessions when reserved seating opens.
  • AWS Summits – AWS Summits are free in-person events covering cloud and AI. With re:Invent on the horizon, the Summits are coming to an end for the year. The last Summit is Dubai (September 30) at the Dubai World Trade Center, with 60+ sessions, an AWS Village, and hands-on workshops.
  • AWS Community Days – Community-led conferences planned and delivered by community leaders. Upcoming events include Lebanon (September 26), Malaysia, Kuala Lumpur (September 26), Cebu, Philippines (September 26), Davao, Philippines (September 26), ComSum Manchester, UK (October 1), and Italy, Rome (October 2).

Summer has officially given way to September, but the weather where I am has not quite caught up. The days are still unusually warm, and I suspect these are the last mild afternoons before autumn settles in for good. I am making the most of them while they last. Come back next week for more!

— Esra

Reverse-Engineering Flock Cameras

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2026/09/reverse-engineering-flock-cameras.html

Hackers captured a Flock camera and got a look (alternate link) at the software:

While much of the automatic license plate reader’s (ALPR) most sensitive storage remained encrypted and inaccessible, the joint analysis of the recovered data shows that software running on the device explicitly detects people as well as vehicles, license plates, and bicycles. The camera can produce dozens of images of a single passing vehicle and, according to several weeks of recovered logs, generated more than a million images. Its computer-vision software also sometimes isolated bumper stickers and other graphics, including, in one case, an American flag patch on a motorcyclist’s saddlebag.

If you’re wondering how the hackers got by disk encryption, one of the unencrypted partitions contained the key for an encrypted partition. That’s pretty bad security engineering.

[$] Testing compat_linux on NetBSD with the Linux Test Project

Post Syndicated from jzb original https://lwn.net/Articles/1094310/

NetBSD has long had support for
running Linux binaries via its kernel-level compat_linux
feature, but test coverage for it was less complete than some might
hope. In order to provide better testing for compat_linux,
Google Summer of Code (GSoC) participant Henrique Brito opted to work
on enabling the Linux Test
Project (LTP) test suite to compile and run on NetBSD. At EuroBSDCon 2026, Brito’s
mentor, Stephen Borrill, provided a report on the project, and the
status of LTP on NetBSD. The work has already resulted in some minor
fixes, and a good list of additional problems to solve.

Security updates for Monday

Post Syndicated from jake original https://lwn.net/Articles/1095702/

Security updates have been issued by AlmaLinux (kernel, perl-Net-DNS, sudo, tomcat, and tomcat9), Debian (chromium, gimp, libde265, libevent, linux-6.12, ruby-jwt, and unbound), Fedora (asterisk, chromium, doctl, dovecot, evolution, firefox, forgejo, freeciv, freeipa, gegl04, gimp, libheif, nss, opkssh, parted, ruby, stb, thunderbird, unbound, and webkitgtk), Mageia (bind, gawk, gdk-pixbuf2.0, graphicsmagick, gstreamer1.0-plugins-base, libde265, libpcap, libssh, mpg123, ntfs-3g, ntpsec, patch, perl-YAML, postfix, python-configargparse, and python-httplib2), Oracle (.NET 10.0, .NET 8.0, .NET 9.0, firefox, image-builder, kernel, libevent, libsoup, libsoup3, perl-Net-DNS, python-lxml, sudo, tomcat, tomcat9, and unbound), Slackware (stunnel), SUSE (alloy, dovecot22, ffmpeg-8, firefox, firefox-esr, freeipmi, glibc, google-guest-agent, google-osconfig-agent, helm, ImageMagick, jq, kbd, kernel-devel, libpcap, libsoup, libzypp, zypper, NetworkManager-applet-l2tp, nginx, openCryptoki, pcre2, python311, python313-aiosmtplib, python313-litellm, rpm, and thunderbird), and Ubuntu (linux-aws, linux-aws-fips, linux-azure-5.15, linux-azure-fde-5.15, linux-azure-fips, linux-azure-5.4, linux-gcp-fips, linux-azure-fips, linux-nvidia-tegra, linux-raspi, linux-raspi-realtime, and rclone).

Python Workers are now generally available

Post Syndicated from Gyeongjae Choi original https://blog.cloudflare.com/python-workers-ga/

We introduced Python Workers two years ago, providing a way to run Python applications in the Cloudflare Workers runtime. Our goal was to make it as simple to write Workers in Python as it is in TypeScript, and to make the ecosystem of Python packages and frameworks “just work”.

Today, Python Workers are now generally available (GA).

What does GA mean? It means Python is now a first-class, fully supported language on the Cloudflare Developer Platform. You can bring the Python code, libraries, and design patterns you already know and connect them seamlessly to Workers AI, R2, D1, Hyperdrive, Durable Objects, Queues, Workflows, and the rest of the Cloudflare platform. You can also run popular Python frameworks like FastAPI, Django, and Flask inside Python Workers. You can even create a Python Worker inside another Worker using Dynamic Workers.

The journey behind Python Workers

Bringing Python to Cloudflare Workers was a natural choice. Because Workers has supported WebAssembly since 2018, it gave us the perfect environment to run a Wasm-compiled Python interpreter. By using Pyodide, we were able to quickly support a wide range of Python applications in Cloudflare Workers.

Our goal was to create the first platform for infinitely scalable Python apps, while making it as easy and performant as developing Python apps anywhere else.

The features we are highlighting today are the result of this multi-year effort. Many developers are already building applications within Python Workers; today, we are making these capabilities production-ready for everyone.

Python is now a first-class language in the Cloudflare Workers runtime

Python Workers now natively support Cloudflare Developer Platform bindings. Previously, using these Cloudflare bindings in Python Workers required converting Python objects into TypeScript objects explicitly at the RPC boundary. For example, sending a Python dictionary into a Cloudflare Queue required the following glue code to work:

This required Python developers to keep the JavaScript environment and code in mind while writing Python Workers, and it was a common source of error for both humans and AI agents. To address this, we have encapsulated the entire type conversion process within the Workers runtime and the Python SDK. This allows you to utilize all Cloudflare bindings in a Pythonic way without writing a single line of JavaScript code, making the following just work:

Web frameworks: FastAPI, Django, and Flask

You can now run your favorite Python framework, such as FastAPI, Django, or Flask, to build an API server in Python Workers. We implemented a built-in connector that you can use to easily connect your web application to Python Workers.

Let’s say you have a simple FastAPI web application:

In native environments, you would use a web server such as uvicorn to run this application.

In Python Workers, you can run the same application using the workers.asgi package we provide, just by adding this snippet to your code:

Similarly, you can use workers.wsgi package to run synchronous web applications such as Django.

So, what happens under the hood?

Python has a standard contract for how web applications should communicate with web servers, known as the Web Server Gateway Interface (WSGI), or its modern asynchronous counterpart, ASGI. This standard allows developers to build applications that are completely server-agnostic. In a traditional deployment, web servers like Uvicorn or Gunicorn are responsible for handling multiple concurrent client connections and threads to scale traffic, while web frameworks like FastAPI can focus purely on the application logic.

In Cloudflare Workers, the Workers platform itself serves as the web server. Since our global network already seamlessly handles load balancing and infinite scaling, we don't need to reinvent the wheel by running a server inside Python Workers.

Instead, our workers.asgi and workers.wsgi connectors act as a thin, optimized bridge. They translate the incoming native JavaScript request into the standard WSGI/ASGI structures that Python applications expect, and seamlessly pipe the response back out with minimal overhead. By doing this, Python developers get the best of both worlds: you can write and organize code using your favorite web frameworks, while letting the Cloudflare Workers platform instantly scale your API across the globe, without ever configuring a server.

These connectors can be used not only with FastAPI, Django, or Flask, but with any Python web framework that uses the WSGI or ASGI interface.

You can find more information about using each web framework in the Python Workers documentation.

Using PostgreSQL and MySQL with Hyperdrive

If you are building a Python application using relational databases such as PostgreSQL or MySQL, you can now integrate Hyperdrive into Python Workers.

Previously, Python Workers didn’t support TCP sockets, making database drivers unavailable. To understand why this was a blocker, you need to look at how WebAssembly operates. Python database drivers like aiomysql or asyncpg rely on the standard library's socket module to establish connections. In a standard environment, this module makes POSIX system calls to the underlying operating system. Inside a WebAssembly sandbox, those POSIX networking syscalls are normally stubs that always fail. Any attempt to open a standard socket would immediately fail. To solve this problem, we implemented socket system calls using the Workers connect API.

When a database driver attempts to open a TCP connection, it goes through our custom socket syscall implementation. It translates standard Python socket operations like opening a connection and reading bytes into the corresponding JavaScript calls used by the Workers runtime. Because this translation happens at the system call level, your database drivers don't have to know about the underlying implementation at all.

This socket bridge is what makes our Hyperdrive integration possible. To use Hyperdrive in Python Workers, first connect your database with Hyperdrive and set up the binding in the Wrangler config:

Then, connect to Hyperdrive using the database drivers you are familiar with:

You can refer to the Hyperdrive Python Workers documentation to find out how you can use Hyperdrive in Python Workers, and which packages are currently supported.

Expanding the WebAssembly package ecosystem

Because Python Workers run inside a WebAssembly sandbox, any packages with native C/C++/Rust extensions must be cross-compiled to WebAssembly to run in Python Workers. However, previously, there was no standard way to cross-compile any Python packages to WebAssembly. That meant our team had to manually compile and host custom WebAssembly packages. This greatly limited the number of packages you could actually use in Python Workers.

We wanted to fix this and allow users to use a wider variety of packages. However, we didn’t want to merely build packages usable only in Python Workers, which wouldn’t benefit the community. Since Python Workers are built on top of Pyodide, we wanted the ecosystem to evolve in a way that benefits Pyodide and the entire Python-on-WebAssembly community.

To this end, we proposed PEP 783, which standardizes a platform for running Python in the browser runtimes called PyEmscripten. After over a year of discussion and refinement, this proposal was accepted, enabling package maintainers to build and publish packages for the PyEmscripten platform and make them available across all environments that implement PyEmscripten.

We also stabilized the existing Pyodide build toolchain and evolved it into a form that is accessible to all package maintainers, enabling developers to easily build packages for the PyEmscripten platform. Furthermore, we added PyEmscripten platform support to cibuildwheel, to make it easier for others to adopt support for the PyEmscripten platform.

While the ecosystem is still adopting this standard, we hope every Python package will have a wheel that works with WebAssembly in the future. We are also actively working with major package maintainers to add PyEmscripten builds. If you encounter a package that isn’t supported yet, let us know on Discord or GitHub, and our team will work to get it built.

You can also check out our EuroPython 2026 talk: “Python Everywhere: The State of Python on WebAssembly” to see how we made this possible.

Building AI agents and pipelines in Python

The large ecosystem of data science and machine learning packages makes Python the natural choice for building intelligent agents and AI pipelines. But bringing these to Python Workers historically presented a challenge: libraries such as openai and langchain rely on HTTP clients like requests or httpx to communicate with external APIs. However, because of missing low-level socket operations support in Python Workers, these HTTP clients didn’t work properly.

To solve this, we contributed upstream to ensure these HTTP clients can route requests directly through the JavaScript fetch API in WebAssembly environments. Combined with our new support for low-level socket operations as explained in the previous section, this makes the entire networking stack work seamlessly inside Python Workers.

As a result, you can now run AI libraries like openai, langchain, and mcp natively in Python Workers. You can also combine them with Workers AI to run serverless inference on GPUs in Cloudflare’s network, or proxy requests through Cloudflare AI Gateway.

The example below shows a way to run Worker AI models in langchain, using the langchain-cloudflare package:

What you can build today

We have assembled a collection of production-ready patterns in our python-workers-examples repository. Here are some ways you can combine Python Workers with the Cloudflare ecosystem.

Asynchronous AI orchestration

Building a full-stack AI application often means connecting multiple services such as storage, queuing, and inference. This example shows how to build an AI-driven image-to-image generator purely in Python Workers. It accepts user requests, drops them into a Cloudflare Queue, and uses Workflows to orchestrate the image generation step via Workers AI, and stores the image to an R2 bucket.

Real-time stream processing with Bluesky Jetstream

Consuming a firehose of real-time events usually requires a dedicated server to maintain the connection. In this example, we use a Python Worker to connect to the ATProto/Bluesky Jetstream WebSocket. By backing this connection with a Durable Object, the Python Worker can maintain long-lived state, ensuring that the WebSocket connection stays alive.

More examples to explore

Model Context Protocol (MCP) Server

Build and deploy an MCP server using the official Python MCP package to give your AI assistants access to edge data.

Retrieval-Augmented Generation (RAG) system with Vectorize

Building a RAG system using Workers AI and Vectorize, Cloudflare’s vector database.

Python code examples across the Cloudflare developer docs

We’ve updated our docs across Cloudflare products to include Python example code. Nearly everywhere where there is a code example showing how to do something in TypeScript, there’s also a code example in Python. We’re committed to continuing to include Python examples across all of our products. You can toggle code snippets between JavaScript, TypeScript, and Python throughout our developer documentation.

What’s next?

Reaching GA is just the start. We have many plans to make Python Workers better, including making Python Workers more performant and memory efficient, as well as supporting more packages.

Keep telling us what you want to build on Python Workers, and we’ll keep pushing the bounds of what is possible. Check out Python Workers documentation and start building your first Python Worker!

The collective thoughts of the interwebz