The first IPv6 specs were published in 1995, and yet 30 years later, we still have a pretty active IETF working group focused on “developing guidelines for the deployment and operation of new and existing IPv6 networks.” (taken from the old charter; they updated it in late October 2025). Why is it taking so long, and what problems are they trying to solve?
Nick Buraglio, one of the working group chairs, provided some answers in Episode 203 of the Software Gone Wild podcast.
We are still mulling over all of the new HPC-AI supercomputer systems that were announced in recent months before and during the SC25 supercomputing conference in St Louis, particularly how the slew of new machines announced by the HPC national labs will be advancing not just the state of the art, but also pushing down the cost of the FP64 floating point operations that still drives a lot of HPC simulation and modeling work. …
Driving HPC Performance Up Is Easier Than Keeping The Spending Constant was written by Timothy Prickett Morgan at The Next Platform.
[Rewritte 12. Dec-2025]
After a Work Request Entity (WRE) is created, the UET provider generates the parameters needed by the Semantic Sublayer (SES) headers. At this stage, the SES does not construct the actual wire header. Instead, it provides the header parameters, which are later used by the Packet Delivery Context (PDC) state machine to construct the final SES wire header, as explained in the upcoming PDC section. These parameters ensure that all necessary information about the message, including addressing and size, is available for later stages of processing.
In our example, the data to be written to the remote GPU is 16 384 bytes. The dual-port NIC in figure 5-5 has a total memory capacity of 16 384 bytes, divided into three regions: a 4 096-byte guaranteed per-port buffer for Eth0 and Eth1, and an 8 192-byte shared memory pool available to both ports. Because gradient synchronization requires lossless delivery, all data must fit within the guaranteed buffer region. The shared memory pool cannot be used, as its buffer space is not guaranteed.
Since the message exceeds the size of the guaranteed buffer, it must be fragmented. The UET provider splits the 16 384-byte Continue reading
A big problem with deploying traffic engineering is configuration complexity. This has now been solved.
Typical reasons for using traffic engineering are:
In 2007, Jeff Atwood published a legendary blog post summarizing a 1997 paper by Brian Foote and Joseph Yoder.
Reading that blog post (or the original paper), the inevitable conclusion is that we haven’t made much progress in the last 20 years. Even worse, almost every single pathological architecture described in that blog post applies quite well to real-life organically grown networks.
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The Cloudflare platform is a critical system for Cloudflare itself. We are our own Customer Zero – using our products to secure and optimize our own services.
Within our security division, a dedicated Customer Zero team uses its unique position to provide a constant, high-fidelity feedback loop to product and engineering that drives continuous improvement of our products. And we do this at a global scale — where a single misconfiguration can propagate across our edge in seconds and lead to unintended consequences. If you've ever hesitated before pushing a change to production, sweating because you know one small mistake could lock every employee out of critical application or take down a production service, you know the feeling. The risk of unintended consequences is real, and it keeps us up at night.
This presents an interesting challenge: How do we ensure hundreds of internal production Cloudflare accounts are secured consistently while minimizing human error?
While the Cloudflare dashboard is excellent for observability and analytics, manually clicking through hundreds of accounts to ensure security settings are identical is a recipe for mistakes. To keep our sanity and our security intact, we stopped treating our configurations as manual point-and-click tasks and Continue reading
This year, about 45 percent of the revenues at Big Blue will come from software. …
IBM Broadens Its Enterprise Software Stack With Confluent Buy was written by Timothy Prickett Morgan at The Next Platform.
netlab release 25.12 (25.12.02 to be exact – I had a few PEBCAK moments) was published last Friday. Here are the highlights:
Note: This post was updated with additional details regarding AWS Lambda.
Last year we announced basic support for Python Workers, allowing Python developers to ship Python to region: Earth in a single command and take advantage of the Workers platform.
Since then, we’ve been hard at work making the Python experience on Workers feel great. We’ve focused on bringing package support to the platform, a reality that’s now here — with exceptionally fast cold starts and a Python-native developer experience.
This means a change in how packages are incorporated into a Python Worker. Instead of offering a limited set of built-in packages, we now support any package supported by Pyodide, the WebAssembly runtime powering Python Workers. This includes all pure Python packages, as well as many packages that rely on dynamic libraries. We also built tooling around uv to make package installation easy.
We’ve also implemented dedicated memory snapshots to reduce cold start times. These snapshots result in serious speed improvements over other serverless Python vendors. In cold start tests using common packages, Cloudflare Workers start over 2.4x faster than AWS Lambda without SnapStart and 3x faster than Google Cloud Run.
In this blog post, we’ll explain Continue reading