System Architecture

A standard infrastructure abstraction layer is needed to enable consistent control over multi-cloud and bespoke on-premises environments.

Adding site-wide configuration with a Rails model can be quite easy to do with Administrate.

GraphQL APIs go from being gateways to backends to being gateways for applications to do magic.

These acronyms represent ways to quantify your commitments to system uptime and measure how successfully your site reliability engineering team is meeting them.

Most dev teams struggle with inconsistent configuration and a lack of transparency. Open source project Score tackles these problems.

A control-plane-based architecture gives you a declarative approach to managing resources, eliminating configuration drift and enforcing policy.

GNU complexity is a command line tool that computes a complexity measure of C source code, similar to pmccabe, but with a different method of calculating

The high-frequency-trading (HFT) industry is rather tight-lipped about what it does and how it does it, but PJ Waskiewicz of Jump Trading came to the Netdev 0x16 conference to try to demystify some of that, especially with respect to its use of networking. He wanted to contrast the needs of HFT with those of the traditional networking as it is used outside of the HFT space. He also has some thoughts on what the Linux kernel could do to help address those needs so that HFT companies could move away from some of the custom code that is currently being developed and maintained by multiple firms in the industry.

Intel’s deepfake detector analyzes ‘blood flow’ in video pixels to return results in milliseconds with 96% accuracy.

This post is part of a series on Mastodon and the fediverse. We also have a post on why the fediverse will be great—if we don't screw it up, and more are on the way.With so many users migrating to Mastodon as their micro-blogging service of choice, a lot of questions are being raised about the...

Block 3rd-party trackers lurking in your apps with DuckDuckGo's App Tracking Protection, now in open beta!

How much computing power is needed at the edge? How much memory and storage are enough for AI at the edge?

Zero-knowledge proofs allow researchers to prove their knowledge without divulging the knowledge itself.

Learn the Fundamentals of Programming.

We build products and offer services that help protect organizations from software supply chain attacks and vulnerabilities.

A lightweight, ultra-fast tool for building observability pipelines

I am perpetually working on what I consider to be the essential API dimensions that ground how we talk about APIs. While having a common definition of the API lifecycle, as well as a clear list of roles and stakeholders involved across the API lifecycle is essential–these dimensions or focused on how we “see” and invest specifically in our APIs. In my experience, there are many ways we talk past each other and introduce friction into our discussions about how to do APIs well. While there are other dimensions not reflected here, these reflect on the areas I find myself talking with enterprises about the most, and that I am getting more opinionated on to help ground my conversations.

EIDF has combined Spectra Logic tape with Cerebras wafer-scale AI so archived datasets can be mined for insights.

Even talking about building a monolith today, is a bit taboo. It is all about microservices at the moment, and has been for a few years. But they aren’t a silver bullet…

Whether an API was built from scratch or integrated from a third-party source, securing it requires organized and active end-to-end visibility.

Companies need to consider both how fast they can put edge applications into action and update them, and how quickly they can process incoming data.

Today, I am publishing the Distributed Computing Manifesto, a canonical document from the early days of Amazon that transformed the architecture of Amazon's ecommerce platform. It highlights the challenges we were facing at the end of the 20th century, and hints at where we were headed.

Taking time to understand the tradeoffs could mean big savings for the organization and fewer surprises for teams that manage cloud infrastructure.