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We have started a computer company! If you haven’t yet, read Jess’s account of us being born in a garage and Bryan’s on the soul of our new computer company. Also, see the perspectives of some of our founding engineers: Robert Mustacchi on joining Oxide, Joshua Clulow on the need for a new machine, and Patrick Mooney on everything he sees aligning at Oxide (and in particular, on the importance of Oxide’s principles!). If it needs to be said, starting a computer company is an ambitious endeavor; we are thrilled to have investment led by Eclipse Ventures and joined by an incredible group of institutional and angel investors. Our investors see what we see: the potential to integrate hardware and software together to bring hyperscaler-class infrastructure to everyone. To use the machine as metaphor, Oxide is at the earliest stages of boot: the power is on, and the first instructions have been executed – but we have a long way to go before we’re fully operational! If you are interested in...
over a year ago

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More from Oxide Computer Company Blog

Oxide’s Compensation Model: How is it Going?

How it started Four years ago, we were struggling to hire. Our team was small (~23 employees), and we knew that we needed many more people to execute on our audacious vision. While we had had success hiring in our personal networks, those networks now felt tapped; we needed to get further afield. As is our wont, we got together as a team and brainstormed: how could we get a bigger and broader applicant pool? One of our engineers, Sean, shared some personal experience: that Oxide’s principles and values were very personally important to him — but that when he explained them to people unfamiliar with the company, they were (understandably?) dismissed as corporate claptrap. Sean had found, however, that there was one surefire way to cut through the skepticism: to explain our approach to compensation. Maybe, Sean wondered, we should talk about it publicly? "I could certainly write a blog entry explaining it," I offered. At this suggestion, the team practically lunged with enthusiasm: the reaction was so uniformly positive that I have to assume that everyone was sick of explaining this most idiosyncratic aspect of Oxide to friends and family. So what was the big deal about our compensation? Well, as a I wrote in the resulting piece, Compensation as a Reflection of Values, our compensation is not merely transparent, but uniform. The piece — unsurprisingly, given the evergreen hot topic that is compensation — got a ton of attention. While some of that attention was negative (despite the piece trying to frontrun every HN hater!), much of it was positive — and everyone seemed to be at least intrigued. And in terms of its initial purpose, the piece succeeded beyond our wildest imagination: it brought a surge of new folks interested in the company. Best of all, the people new to Oxide were interested for all of the right reasons: not the compensation per se, but for the values that the compensation represents. The deeper they dug, the more they found to like — and many who learned about Oxide for the first time through that blog entry we now count as long-time, cherished colleagues. That blog entry was a long time ago now, and today we have ~75 employees (and a shipping product!); how is our compensation model working out for us? How it’s going Before we get into our deeper findings, two updates that are so important that we have updated the blog entry itself. First, the dollar figure itself continues to increase over time (as of this writing in 2025, $207,264); things definitely haven’t gotten (and aren’t getting!) any cheaper. And second, we did introduce variable compensation for some sales roles. Yes, those roles can make more than the rest of us — but they can also make less, too. And, importantly: if/when those folks are making more than the rest of us, it’s because they’re selling a lot — a result that can be celebrated by everyone! Those critical updates out of the way, how is it working? There have been a lot of surprises along the way, mostly (all?) of the positive variety. A couple of things that we have learned: People take their own performance really seriously. When some outsiders hear about our compensation model, they insist that it can’t possibly work because "everyone will slack off." I have come to find this concern to be more revealing of the person making the objection than of our model, as our experience has been in fact the opposite: in my one-on-one conversations with team members, a frequent subject of conversation is people who are concerned that they aren’t doing enough (or that they aren’t doing the right thing, or that their work is progressing slower than they would like). I find my job is often to help quiet this inner critic while at the same time stoking what I feel is a healthy urge: when one holds one’s colleagues in high regard, there is an especially strong desire to help contribute — to prove oneself worthy of a superlative team. Our model allows people to focus on their own contribution (whatever it might be). People take hiring really seriously. When evaluating a peer (rather than a subordinate), one naturally has high expectations — and because (in the sense of our wages, anyway) everyone at Oxide is a peer, it shouldn’t be surprising that folks have very high expectations for potential future colleagues. And because the Oxide hiring process is writing intensive, it allows for candidates to be thoroughly reviewed by Oxide employees — who are tough graders! It is, bluntly, really hard to get a job at Oxide. It allows us to internalize the importance of different roles. One of the more incredible (and disturbingly frequent) objections I have heard is: "But is that what you’ll pay support folks?" I continue to find this question offensive, but I no longer find it surprising: the specific dismissal of support roles reveals a widespread and corrosive devaluation of those closest to customers. My rejoinder is simple: think of the best support engineers you’ve worked with; what were they worth? Anyone who has shipped complex systems knows these extraordinary people — calm under fire, deeply technical, brilliantly resourceful, profoundly empathetic — are invaluable to the business. So what if you built a team entirely of folks like that? The response has usually been: well, sure, if you’re going to only hire those folks. Yeah, we are — and we have! It allows for fearless versatility. A bit of a corollary to the above, but subtly different: even though we (certainly!) hire and select for certain roles, our uniform compensation means we can in fact think primarily in terms of people unconfined by those roles. That is, we can be very fluid about what we’re working on, without fear of how it will affect a perceived career trajectory. As a concrete example: we had a large customer that wanted to put in place a program for some of the additional work they wanted to see in the product. The complexity of their needs required dedicated program management resources that we couldn’t spare, and in another more static company we would have perhaps looked to hire. But in our case, two folks came together — CJ from operations, and Izzy from support — and did something together that was in some regards new to both of them (and was neither of their putative full-time jobs!) The result was indisputably successful: the customer loved the results, and two terrific people got a chance to work closely together without worrying about who was dotted-lined to whom. It has allowed us to organizationally scale. Many organizations describe themselves as flat, and a reasonable rebuttal to this are the "shadow hierarchies" created by the tyranny of structurelessness. And indeed, if one were to read (say) Valve’s (in)famous handbook, the autonomy seems great — but the stack ranking decidedly less so, especially because the handbook is conspicuously silent on the subject of compensation. (Unsurprisingly, compensation was weaponized at Valve, which descended into toxic cliquishness.) While we believe that autonomy is important to do one’s best work, we also have a clear structure at Oxide in that Steve Tuck (Oxide co-founder and CEO) is in charge. He has to be: he is held accountable to our investors — and he must have the latitude to make decisions. Under Steve, it is true that we don’t have layers of middle management. Might we need some in the future? Perhaps, but what fraction of middle management in a company is dedicated to — at some level — determining who gets what in terms of compensation? What happens when you eliminate that burden completely? It frees us to both lead and follow. We expect that every Oxide employee has the capacity to lead others — and we tap this capacity frequently. Of course, a company in which everyone is trying to direct all traffic all the time would be a madhouse, so we also very much rely on following one another too! Just as our compensation model allows us to internalize the values of different roles, it allows us to appreciate the value of both leading and following, and empowers us each with the judgement to know when to do which. This isn’t always easy or free of ambiguity, but this particular dimension of our versatility has been essential — and our compensation model serves to encourage it. It causes us to hire carefully and deliberately. Of course, one should always hire carefully and deliberately, but this often isn’t the case — and many a startup has been ruined by reckless expansion of headcount. One of the roots of this can be found in a dirty open secret of Silicon Valley middle management: its ranks are taught to grade their career by the number of reports in their organization. Just as if you were to compensate software engineers based on the number of lines of code they wrote, this results in perverse incentives and predictable disasters — and any Silicon Valley vet will have plenty of horror stories of middle management jockeying for reqs or reorgs when they should have been focusing on product and customers. When you can eliminate middle management, you eliminate this incentive. We grow the team not because of someone’s animal urges to have the largest possible organization, but rather because we are at a point where adding people will allow us to better serve our market and customers. It liberates feedback from compensation. Feedback is, of course, very important: we all want to know when and where we’re doing the right thing! And of course, we want to know too where there is opportunity for improvement. However, Silicon Valley has historically tied feedback so tightly to compensation that it has ceased to even pretend to be constructive: if it needs to be said, performance review processes aren’t, in fact, about improving the performance of the team, but rather quantifying and stack-ranking that performance for purposes of compensation. When compensation is moved aside, there is a kind of liberation for feedback itself: because feedback is now entirely earnest, it can be expressed and received thoughtfully. It allows people to focus on doing the right thing. In a world of traditional, compensation-tied performance review, the organizational priority is around those things that affect compensation — even at the expense of activity that clearly benefits the company. This leads to all sorts of wild phenomena, and most technology workers will be able to tell stories of doing things that were clearly right for the company, but having to hide it from management that thought only narrowly in terms of their own stated KPIs and MBOs. By contrast, over and over (and over!) again, we have found that people do the right thing at Oxide — even if (especially if?) no one is looking. The beneficiary of that right thing? More often than not, it’s our customers, who have uniformly praised the team for going above and beyond. It allows us to focus on the work that matters. Relatedly, when compensation is non-uniform, the process to figure out (and maintain) that non-uniformity is laborious. All of that work — of line workers assembling packets explaining themselves, of managers arming themselves with those packets to fight in the arena of organizational combat, and then of those same packets ultimately being regurgitated back onto something called a review — is work. Assuming such a process is executed perfectly (something which I suppose is possible in the abstract, even though I personally have never seen it), this is work that does not in fact advance the mission of the company. Not having variable compensation gives us all of that time and energy back to do the actual work — the stuff that matters. It has stoked an extraordinary sense of teamwork. For me personally — and as I relayed on an episode of Software Misadventures — the highlights of my career have been being a part of an extraordinary team. The currency of a team is mutual trust, and while uniform compensation certainly isn’t the only way to achieve that trust, boy does it ever help! As Steve and I have told one another more times that we can count: we are so lucky to work on this team, with its extraordinary depth and breadth. While our findings have been very positive, I would still reiterate what we said four years ago: we don’t know what the future holds, and it’s easier to make an unwavering commitment to the transparency rather than the uniformity. That said, the uniformity has had so many positive ramifications that the model feels more important than ever. We are beyond the point of this being a curiosity; it’s been essential for building a mission-focused team taking on a problem larger than ourselves. So it’s not a fit for everyone — but if you are seeking an extraordinary team solving hard problems in service to customers, consider Oxide!

2 months ago 13 votes
dtrace.conf(24)

Sometime in late 2007, we had the idea of a DTrace conference. Or really, more of a meetup; from the primordial e-mail I sent: The goal here, by the way, is not a DTrace user group, but more of a face-to-face meeting with people actively involved in DTrace — either by porting it to another system, by integrating probes into higher level environments, by building higher-level tools on top of DTrace or by using it heavily and/or in a critical role. That said, we also don’t want to be exclusionary, so our thinking is that the only true requirement for attending is that everyone must be prepared to speak informally for 15 mins or so on what they are doing with DTrace, any limitations that they have encountered, and some ideas for the future. We’re thinking that this is going to be on the order of 15-30 people (though more would be a good problem to have — we’ll track it if necessary), that it will be one full day (breakfast in the morning through drinks into the evening), and that we’re going to host it here at our offices in San Francisco sometime in March 2008. This same note also included some suggested names for the gathering, including what in hindsight seems a clear winner: DTrace Bi-Mon-Sci-Fi-Con. As if knowing that I should leave an explanatory note to my future self as to why this name was not selected, my past self fortunately clarified: "before everyone clamors for the obvious Bi-Mon-Sci-Fi-Con, you should know that most Millennials don’t (sadly) get the reference." (While I disagree with the judgement of my past self, it at least indicates that at some point I cared if anyone got the reference.) We settled on a much more obscure reference, and had the first dtrace.conf in March 2008. Befitting the style of the time, it was an unconference (a term that may well have hit its apogee in 2008) that you signed up to attend by editing a wiki. More surprising given the year (and thanks entirely to attendee Ben Rockwood), it was recorded — though this is so long ago that I referred to it as video taping (and with none of the participants mic’d, I’m afraid the quality isn’t very good). The conference, however, was terrific, viz. the reports of Adam, Keith and Stephen (all somehow still online nearly two decades later). If anything, it was a little too good: we realized that we couldn’t recreate the magic, and we demurred on making it an annual event. Years passed, and memories faded. By 2012, it felt like we wanted to get folks together again, now under a post-lawnmower corporate aegis in Joyent. The resulting dtrace.conf(12) was a success, and the Olympiad cadence felt like the right one; we did it again four years later at dtrace.conf(16). In 2020, we came back together for a new adventure — and the DTrace Olympiad was not lost on Adam. Alas, dtrace.conf(20) — like the Olympics themselves — was cancelled, if implicitly. Unlike the Olympics, however, it was not to be rescheduled. More years passed and DTrace continued to prove its utility at Oxide; last year when Adam and I did our "DTrace at 20" episode of Oxide and Friends, we vowed to hold dtrace.conf(24) — and a few months ago, we set our date to be December 11th. At first we assumed we would do something similar to our earlier conferences: a one-day participant-run conference, at the Oxide office in Emeryville. But times have changed: thanks to the rise of remote work, technologists are much more dispersed — and many more people would need to travel for dtrace.conf(24) than in previous DTrace Olympiads. Travel hasn’t become any cheaper since 2008, and the cost (and inconvenience) was clearly going to limit attendance. The dilemma for our small meetup highlights the changing dynamics in tech conferences in general: with talks all recorded and made publicly available after the conference, how does one justify attending a conference in person? There can be reasonable answers to that question, of course: it may be the hallway track, or the expo hall, or the after-hours socializing, or perhaps some other special conference experience. But it’s also not surprising that some conferences — especially ones really focused on technical content — have decided that they are better off doing as conference giant O’Reilly Media did, and going exclusively online. And without the need to feed and shelter participants, the logistics for running a conference become much more tenable — and the price point can be lowered to the point that even highly produced conferences like P99 CONF can be made freely available. This, in turn, leads to much greater attendance — and a network effect that can get back some of what one might lose going online. In particular, using chat as the hallway track can be more much effective (and is certainly more scalable!) than the actual physical hallways at a conference. For conferences in general, there is a conversation to be had here (and as a teaser, Adam and I are going to talk about it with Stephen O’Grady and Theo Schlossnagle on Oxide and Friends next week, but for our quirky, one-day, Olympiad-cadence dtrace.conf, the decision was pretty easy: there was much more to be gained than lost by going exclusively on-line. So dtrace.conf(24) is coming up next week, and it’s available to everyone. In terms of platform, we’re going to try to keep that pretty simple: we’re going to use Google Meet for the actual presenters, which we will stream in real-time to YouTube — and we’ll use the Oxide Discord for all chat. We’re hoping you’ll join us on December 11th — and if you want to talk about DTrace or a DTrace-adjacent topic, we’d love for you to present! Keeping to the unconference style, if you would like to present, please indicate your topic in the #session-topics Discord channel so we can get the agenda fleshed out. While we’re excited to be online, there are some historical accoutrements of conferences that we didn’t want to give up. First, we have a tradition of t-shirts with dtrace.conf. Thanks to our designer Ben Leonard, we have a banger of a t-shirt, capturing the spirit of our original dtrace.conf(08) shirt but with an Oxide twist. It’s (obviously) harder to make those free but we have tried to price them reasonably. You can get your t-shirt by adding it to your (free) dtrace.conf ticket. (And for those who present at dtrace.conf, your shirt is on us — we’ll send you a coupon code!) Second, for those who can make their way to the East Bay and want some hangout time, we are going to have an après conference social event at the Oxide office starting at 5p. We’re charging something nominal for that too (and like the t-shirt, you pay for that via your dtrace.conf ticket); we’ll have some food and drinks and an Oxide hardware tour for the curious — and (of course?) there will be Fishpong. Much has changed since I sent that e-mail 17 years ago — but the shared values and disposition that brought together our small community continue to endure; we look forward to seeing everyone (virtually) at dtrace.conf(24)!

7 months ago 83 votes
Advancing Cloud and HPC Convergence with Lawrence Livermore National Laboratory

Oxide Computer Company and Lawrence Livermore National Laboratory Work Together to Advance Cloud and HPC Convergence Oxide Computer Company and Lawrence Livermore National Laboratory (LLNL) today announced a plan to bring on-premises cloud computing capabilities to the Livermore Computing (LC) high-performance computing (HPC) center. The rack-scale Oxide Cloud Computer allows LLNL to improve the efficiency of operational workloads and will provide users in the National Nuclear Security Administration (NNSA) with new capabilities for provisioning secure, virtualized services alongside HPC workloads. HPC centers have traditionally run batch workloads for large-scale scientific simulations and other compute-heavy applications. HPC workloads do not exist in isolation—there are a multitude of persistent, operational services that keep the HPC center running. Meanwhile, HPC users also want to deploy cloud-like persistent services—databases, Jupyter notebooks, orchestration tools, Kubernetes clusters. Clouds have developed extensive APIs, security layers, and automation to enable these capabilities, but few options exist to deploy fully virtualized, automated cloud environments on-premises. The Oxide Cloud Computer allows organizations to deliver secure cloud computing capabilities within an on-premises environment. On-premises environments are the next frontier for cloud computing. LLNL is tackling some of the hardest and most important problems in science and technology, requiring advanced hardware, software, and cloud capabilities. We are thrilled to be working with their exceptional team to help advance those efforts, delivering an integrated system that meets their rigorous requirements for performance, efficiency, and security. — Steve TuckCEO at Oxide Computer Company Leveraging the new Oxide Cloud Computer, LLNL will enable staff to provision virtual machines (VMs) and services via self-service APIs, improving operations and modernizing aspects of system management. In addition, LLNL will use the Oxide rack as a proving ground for secure multi-tenancy and for smooth integration with the LLNL-developed Flux resource manager. LLNL plans to bring its users cloud-like Infrastructure-as-a-Service (IaaS) capabilities that work seamlessly with their HPC jobs, while maintaining security and isolation from other users. Beyond LLNL personnel, researchers at the Los Alamos National Laboratory and Sandia National Laboratories will also partner in many of the activities on the Oxide Cloud Computer. We look forward to working with Oxide to integrate this machine within our HPC center. Oxide’s Cloud Computer will allow us to securely support new types of workloads for users, and it will be a proving ground for introducing cloud-like features to operational processes and user workflows. We expect Oxide’s open-source software stack and their transparent and open approach to development to help us work closely together. — Todd GamblinDistinguished Member of Technical Staff at LLNL Sandia is excited to explore the Oxide platform as we work to integrate on-premise cloud technologies into our HPC environment. This advancement has the potential to enable new classes of interactive and on-demand modeling and simulation capabilities. — Kevin PedrettiDistinguished Member of Technical Staff at Sandia National Laboratories LLNL plans to work with Oxide on additional capabilities, including the deployment of additional Cloud Computers in its environment. Of particular interest are scale-out capabilities and disaster recovery. The latest installation underscores Oxide Computer’s momentum in the federal technology ecosystem, providing reliable, state-of-the-art Cloud Computers to support critical IT infrastructure. To learn more about Oxide Computer, visit https://oxide.computer. About Oxide Computer Oxide Computer Company is the creator of the world’s first commercial Cloud Computer, a true rack-scale system with fully unified hardware and software, purpose-built to deliver hyperscale cloud computing to on-premises data centers. With Oxide, organizations can fully realize the economic and operational benefits of cloud ownership, with access to the same self-service development experience of public cloud, without the public cloud cost. Oxide empowers developers to build, run, and operate any application with enhanced security, latency, and control, and frees organizations to elevate IT operations to accelerate strategic initiatives. To learn more about Oxide’s Cloud Computer, visit oxide.computer. About LLNL Founded in 1952, Lawrence Livermore National Laboratory provides solutions to our nation’s most important national security challenges through innovative science, engineering, and technology. Lawrence Livermore National Laboratory is managed by Lawrence Livermore National Security, LLC for the U.S. Department of Energy’s National Nuclear Security Administration. Media Contact LaunchSquad for Oxide Computer oxide@launchsquad.com

7 months ago 79 votes
Remembering Charles Beeler

We are heartbroken to relay that Charles Beeler, a friend and early investor in Oxide, passed away in September after a battle with cancer. We lost Charles far too soon; he had a tremendous influence on the careers of us both. Our relationship with Charles dates back nearly two decades, to his involvement with the ACM Queue board where he met Bryan. It was unprecedented to have a venture capitalist serve in this capacity with ACM, and Charles brought an entirely different perspective on the practitioner content. A computer science pioneer who also served on the board took Bryan aside at one point: "Charles is one of the good ones, you know." When Bryan joined Joyent a few years later, Charles also got to know Steve well. Seeing the promise in both node.js and cloud computing, Charles became an investor in the company. When companies hit challenging times, some investors will hide — but Charles was the kind of investor to figure out how to fix what was broken. When Joyent needed a change in executive leadership, it was Charles who not only had the tough conversations, but led the search for the leader the company needed, ultimately positioning the company for success. Aside from his investment in Joyent, Charles was an outspoken proponent of node.js, becoming an organizer of the Node Summit conference. In 2017, he asked Bryan to deliver the conference’s keynote, but by then, the relationship between Joyent and node.js had become…​ complicated, and Bryan felt that it probably wouldn’t be a good idea. Any rational person would have dropped it, but Charles persisted, with characteristic zeal: if the Joyent relationship with node.js had become strained, so much more the reason to speak candidly about it! Charles prevailed, and the resulting talk, Platform as Reflection of Values, became one of Bryan’s most personally meaningful talks. Charles’s persistence was emblematic: he worked behind the scenes to encourage people to do their best work, always with an enthusiasm for the innovators and the creators. As we were contemplating Oxide, we told Charles what we wanted to do long before we had a company. Charles laughed with delight: "I hoped that you two would do something big, and I am just so happy for you that you’re doing something so ambitious!" As we raised seed capital, we knew that we were likely a poor fit for Charles and his fund. But we also knew that we deeply appreciated his wisdom and enthusiasm; we couldn’t resist pitching him on Oxide. Charles approached the investment in Oxide as he did with so many other aspects: with curiosity, diligence, empathy, and candor. He was direct with us that despite his enthusiasm for us personally, Oxide would be a challenging investment for his firm. But he also worked with us to address specific objections, and ultimately he won over his partnership. We were thrilled when he not only invested, but pulled together a syndicate of like-minded technologists and entrepreneurs to join him. Ever since, he has been a huge Oxide fan. Befitting his enthusiasm, one of his final posts expressed his enthusiasm and pride in what the Oxide team has built. Charles, thank you. You told us you were proud of us — and it meant the world. We are gutted to no longer have you with us; your influence lives on not just in Oxide, but also in the many people that you have inspired. You were the best of venture capital. Closer to the heart, you were a terrific friend to us both; thank you.

7 months ago 66 votes
How Oxide Cuts Data Center Power Consumption in Half

Here’s a sobering thought: today, data centers already consume 1-2% of the world’s power, and that percentage will likely rise to 3-4% by the end of the decade. According to Goldman Sachs research, that rise will include a doubling in data center carbon dioxide emissions. As the data and AI boom progresses, this thirst for power shows no signs of slowing down anytime soon. Two key challenges quickly become evident for the 85% of IT that currently lives on-premises. How can organizations reduce power consumption and corresponding carbon emissions? How can organizations keep pace with AI innovation as existing data centers run out of available power? Figure 1. Masanet et al. (2020), Cisco, IEA, Goldman Sachs Research Rack-scale design is critical to improved data center efficiency Traditional data center IT consumes so much power because the fundamental unit of compute is an individual server; like a house where rooms were built one at a time, with each room having its own central AC unit, gas furnace, and electrical panel. Individual rackmount servers are stacked together, each with their own AC power supplies, cooling fans, and power management. They are then paired with storage appliances and network switches that communicate at arm’s length, not designed as a cohesive whole. This approach fundamentally limits organizations' ability to maintain sustainable, high-efficiency computing systems. Of course, hyperscale public cloud providers did not design their data center systems this way. Instead, they operate like a carefully planned smart home where everything is designed to work together cohesively and is operated by software that understands the home’s systems end-to-end. High-efficiency, rack-scale computers are deployed at scale and operate as a single unit with integrated storage and networking to support elastic cloud computing services. This modern archietecture is made available to the market as public cloud, but that rental-only model is ill-fit for many business needs. Compared to a popular rackmount server vendor, Oxide is able to fill our specialized racks with 32 AMD Milan sleds and highly-available network switches using less than 15kW per rack, doubling the compute density in a typical data center. With just 16 of the alternative 1U servers and equivalent network switches, over 16kW of power is required per rack, leading to only 1,024 CPU cores vs Oxide’s 2,048. Extracting more useful compute from each kW of power and square foot of data center space is key to the future effectiveness of on-premises computing. At Oxide, we’ve taken this lesson in advancing rack-scale design, improved upon it in several ways, and made it available for every organization to purchase and operate anywhere in the world without a tether back to the public cloud. Our Cloud Computer treats the entire rack as a single, unified computer rather than a collection of independent parts, achieving unprecedented power efficiency. By designing the hardware and software together, we’ve eliminated unnecessary components and optimized every aspect of system operation through a control plane with visibility to end-to-end operations. When we started Oxide, the DC bus bar stood as one of the most glaring differences between the rack-scale machines at the hyperscalers and the rack-and-stack servers that the rest of the market was stuck with. That a relatively simple piece of copper was unavailable to commercial buyers — despite being unequivocally the right way to build it! — represented everything wrong with the legacy approach. The bus bar in the Oxide Cloud Computer is not merely more efficient, it is a concrete embodiment of the tremendous gains from designing at rack-scale, and by integrating hardware with software. — Bryan Cantrill The improvements we’re seeing are rooted in technical innovation Replacing low-efficiency AC power supplies with a high-efficiency DC Bus Bar This eliminates the 70 total AC power supplies found in an equivalent legacy server rack within 32 servers, two top-of-rack switches, and one out-of-band switch, each with two AC power supplies. This power shelf also ensures the load is balanced across phases, something that’s impossible with traditional power distribution units found in legacy server racks. Bigger fans = bigger efficiency gains using 12x less energy than legacy servers, which each contain as many as 7 fans, which must work much harder to move air over system components. Purpose-built for power efficiency less restrictive airflow than legacy servers by eliminating extraneous components like PCIe risers, storage backplanes, and more. Legacy servers need many optional components like these because they could be used for any number of tasks, such as point-of-sale systems, data center servers, or network-attached-storage (NAS) systems. Still, they were never designed optimally for any one of those tasks. The Oxide Cloud Computer was designed from the ground up to be a rack-scale cloud computing powerhouse, and so it’s optimized for exactly that task. Hardware + Software designed together By designing the hardware and software together, we can make hardware choices like more intelligent DC-DC power converters that can provide rich telemetry to our control plane, enabling future feature enhancements such as dynamic power capping and efficiency-based workload placement that are impossible with legacy servers and software systems. Learn more about Oxide’s intelligent Power Shelf Controller The Bottom Line: Customers and the Environment Both Benefit Reducing data center power demands and achieving more useful computing per kilowatt requires fundamentally rethinking traditional data center utilization and compute design. At Oxide, we’ve proven that dramatic efficiency gains are possible when you rethink the computer at rack-scale with hardware and software designed thoughtfully and rigorously together. Ready to learn how your organization can achieve these results? Schedule time with our team here. Together, we can reclaim on-premises computing efficiency to achieve both business and sustainability goals.

8 months ago 74 votes

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7 hours ago 3 votes
Desktop UI frameworks written by a single person

Less known desktop UI frameworks Writing desktop software is hard. The UI technologies of Windows or MacOS are awful compared to web technology. What can trivially be done with HTML/CSS/JavaScript in few minutes can take hours using Windows’s win32 APIs or Mac’s Cocoa. That’s why the default technology for desktop apps, especially cross-platform, is Electron: a Chrome browser combined with Node runtime. The problem is that it’s bloaty: each app is a unique build of Chrome with a little bit of application code. Chrome is over 100MB so many apps ship less than 1MB of code in a 100M wrapper. People tried to address the problem of poor OS APIs by writing UI frameworks, often meant to be cross-platform. You’ve heard about QT, GTK, wxWindows. The problem with those is that they are also old, their APIs are not the greatest either and they are bloaty as well. There just doesn’t seem to be a good option. Writing your own framework seems impossible due to the size of task. But is it? I’ll show a couple of less-known UI frameworks written mostly be a single person, often done simply to enable writing an application. SWELL in WDL WDL is interesting. Justin Frankel, the guy who created Winamp, has a repository of C++ code he uses in different projects. After selling Winamp to AOL, a side quest of writing file sharing application, getting fired from AOL for writing file sharing application, he started a company building Reaper a digital audio workstation software for Windows. Winamp is a win32 API program and so is Reaper. At some point Justin decided to make a Mac version but by then he had a lot of code heavily using win32 APIs. So he did what anyone in his position would: he implemented win32 APIs for Mac OS and Linux and called it SWELL - Simple Windows Emulation Layer. Ok, actually no-one else would do it. It was an insane idea but it worked. It’s important to not over-state SWELL capabilities. It’s not Wine. You can’t take any win32 program and recompile for Mac with SWELL. Frankel is insanely pragmatic and so is his code. SWELL only implements the subset of APIs he uses in Reaper. At the same time Reaper is a big app so if SWELL works for Reaper, it could work for your app. WDL is open-source using permissive MIT license. Sublime Text For a few years Sublime Text was THE programmer’s editor. It was written by a single developer in C++ and he wrote a custom UI toolkit for it. Not open source but its existence shows it can be done. RAD Debugger RAD Debugger is an open-source Windows debugger for C/C++ apps written in C by mostly a single person. It implements a custom UI framework based on 3D renderer. The UI is integral part of the the app but the code is well structured so you probably can take just their UI / render code and use it in your own C / C++ app. Currently the app / UI is only for Windows but it’s designed to be cross-platform and they are working on porting the renderer to Mac OS / Linux. They use permissive MIT license and everything is written in C. Dear ImGUI Dear ImGui is a newer cross-platform, UI framework in C++. Open source, permissive MIT license. Written by mostly a single person. Ghostty Ghostty is a cross-platform terminal emulator and UI. It’s written in Zig by mostly a single person and uses it’s own low-level GPU renderer for the UI. You too can write your own UI framework At first the idea of writing your own UI framework seems impossibly daunting. What I’m hoping to show is that if you’re ambitious enough it’s possible to build cross platform desktop apps that are not just bloated 100MB Chrome wrappers around few kilobytes of custom code. I’m not saying it’s a simple thing, just that enough people did it that it’s possible. It shouldn’t be necessary but both Microsoft and Apple have tragically dropped the ball on providing decent, high-performance UI libraries for their OS. Microsoft even writes their own apps, like Teams, in web technologies. Thanks to open source you’re not at the staring line. You can just use Dear ImGUI or WDL’s SWELL. Or you can extract the UI code from RAD Debugger or Ghostty (if you write in Zig). Or you can look at how their implementation to speed up your own design and implementation.

yesterday 2 votes
Logic for Programmers Turns One

I released Logic for Programmers exactly one year ago today. It feels weird to celebrate the anniversary of something that isn't 1.0 yet, but software projects have a proud tradition of celebrating a dozen anniversaries before 1.0. I wanted to share about what's changed in the past year and the work for the next six+ months. The Road to 0.1 I had been noodling on the idea of a logic book since the pandemic. The first time I wrote about it on the newsletter was in 2021! Then I said that it would be done by June and would be "under 50 pages". The idea was to cover logic as a "soft skill" that helped you think about things like requirements and stuff. That version sucked. If you want to see how much it sucked, I put it up on Patreon. Then I slept on the next draft for three years. Then in 2024 a lot of business fell through and I had a lot of free time, so with the help of Saul Pwanson I rewrote the book. This time I emphasized breadth over depth, trying to cover a lot more techniques. I also decided to self-publish it instead of pitching it to a publisher. Not going the traditional route would mean I would be responsible for paying for editing, advertising, graphic design etc, but I hoped that would be compensated by much higher royalties. It also meant I could release the book in early access and use early sales to fund further improvements. So I wrote up a draft in Sphinx, compiled it to LaTeX, and uploaded the PDF to leanpub. That was in June 2024. Since then I kept to a monthly cadence of updates, missing once in November (short-notice contract) and once last month (Systems Distributed). The book's now on v0.10. What's changed? A LOT v0.1 was very obviously an alpha, and I have made a lot of improvements since then. For one, the book no longer looks like a Sphinx manual. Compare! Also, the content is very, very different. v0.1 was 19,000 words, v.10 is 31,000.1 This comes from new chapters on TLA+, constraint/SMT solving, logic programming, and major expansions to the existing chapters. Originally, "Simplifying Conditionals" was 600 words. Six hundred words! It almost fit in two pages! The chapter is now 2600 words, now covering condition lifting, quantifier manipulation, helper predicates, and set optimizations. All the other chapters have either gotten similar facelifts or are scheduled to get facelifts. The last big change is the addition of book assets. Originally you had to manually copy over all of the code to try it out, which is a problem when there are samples in eight distinct languages! Now there are ready-to-go examples for each chapter, with instructions on how to set up each programming environment. This is also nice because it gives me breaks from writing to code instead. How did the book do? Leanpub's all-time visualizations are terrible, so I'll just give the summary: 1180 copies sold, $18,241 in royalties. That's a lot of money for something that isn't fully out yet! By comparison, Practical TLA+ has made me less than half of that, despite selling over 5x as many books. Self-publishing was the right choice! In that time I've paid about $400 for the book cover (worth it) and maybe $800 in Leanpub's advertising service (probably not worth it). Right now that doesn't come close to making back the time investment, but I think it can get there post-release. I believe there's a lot more potential customers via marketing. I think post-release 10k copies sold is within reach. Where is the book going? The main content work is rewrites: many of the chapters have not meaningfully changed since 1.0, so I am going through and rewriting them from scratch. So far four of the ten chapters have been rewritten. My (admittedly ambitious) goal is to rewrite three of them by the end of this month and another three by the end of next. I also want to do final passes on the rewritten chapters; as most of them have a few TODOs left lying around. (Also somehow in starting this newsletter and publishing it I realized that one of the chapters might be better split into two chapters, so there could well-be a tenth technique in v0.11 or v0.12!) After that, I will pass it to a copy editor while I work on improving the layout, making images, and indexing. I want to have something worthy of printing on a dead tree by 1.0. In terms of timelines, I am very roughly estimating something like this: Summer: final big changes and rewrites Early Autumn: graphic design and copy editing Late Autumn: proofing, figuring out printing stuff Winter: final ebook and initial print releases of 1.0. (If you know a service that helps get self-published books "past the finish line", I'd love to hear about it! Preferably something that works for a fee, not part of royalties.) This timeline may be disrupted by official client work, like a new TLA+ contract or a conference invitation. Needless to say, I am incredibly excited to complete this book and share the final version with you all. This is a book I wished for years ago, a book I wrote because nobody else would. It fills a critical gap in software educational material, and someday soon I'll be able to put a copy on my bookshelf. It's exhilarating and terrifying and above all, satisfying. It's also 150 pages vs 50 pages, but admittedly this is partially because I made the book smaller with a larger font. ↩

2 days ago 4 votes
Implementing UI translation in SumatraPDF, a C++ Windows application

Translating user interface of SumatraPDF SumatraPDF is the best PDF/eBook/Comic Book viewer for Windows. It’s small, fast, full of features, free and open-source. It became popular enough that it made sense to translate the UI for non-English users. Currently we support 72 languages. This article describes how I designed and implemented a translation system in SumatraPDF, a native win32 C++ Windows application. Hard things about translating the UI There are 2 hard things about translating an application code for translation system (extracting strings to translate, translate strings from English to user’s language) translating them into many languages Extracting strings to translate from source code Currently there are 381 strings in SumatraPDF subject to translation. It’s important that the system requires the least amount of effort when adding new strings to translate. Every string that needs to be translated is marked in .cpp or .h file with one of two macros: _TRA("Rename") _TRN("Open") I have a script that extracts those strings from source files. Mine is written in Go but it could just as well be Python or JavaScript. It’s a simple regex job. _TR stands for “translation”. _TRA(s) expands into const char* trans::GetTranslation(const char* str) function which returns str translated to current UI language. We auto-detect language at startup based on Windows settings and allow the user to explicitly set UI language. For English we just return the original string. If a string to be translated is e.g. a part of const char* array[], we can’t use trans::GetTranslation(). For cases like that we have _TRN() which expands to English string. We have to write code to translate it at some point. Adding new strings is therefore as simple as wrapping them in _TRA() or _TRN() macros. Translating strings into many languages Now that we’ve extracted strings to be translated, we need to translate them into 72 languages. SumatraPDF is a free, open-source program. I don’t have a budget to hire translators. I don’t have a budget, period. The only option was to get help from SumatraPDF users. It was vital to make it very easy for users to send me translations. I didn’t want to ask them, for example, to download some translation software. Design and implementation of AppTranslator web app I couldn’t find a really simple software for crowd sourcing translations so I wrote my own: https://github.com/kjk/apptranslator You can see it in action: https://www.apptranslator.org/app/SumatraPDF I designed it to be generic but I don’t think anyone else is using it. AppTranslator is simple. Per https://tools.arslexis.io/wc/: 4k lines of Go server code 451 lines of html code a single dependency: bootstrap CSS framework (the project is old) It’s simple because I don’t want to spend a lot of time writing translation software. It’s just a side project in service of the goal of translating SumatraPDF. Login is exclusively via GitHub. It doesn’t even use a database. Like in Redis, changes are stored as a series of operations in an append-only log. We keep the whole state in memory and re-create it from the log at startup. Main operation is translate a string from English to language X represented as [kOpTranslation, english string, language, translation, user who provided translation]. When user provides a translation in the web UI, we send an API call to the server which appends the translation operation to the log. Simple and reliable. Because the code is written in Go, it’s very fast and memory efficient. When running it uses mere megabytes of RAM. It can comfortably run on the smallest 256 MB VPS server. I backup the log to S3 so if the server ever fails, I can re-install the program on a new server and re-download the translations from S3. I provide RSS feed for each language so that people who provide translations can monitor for new strings to be translated. Sending strings for translation and receiving translations So I have a web app for collecting translations and a script that extracts strings to be translated from source code. How do they connect? AppTranslator has an API for submitting the current set of strings to be translated in the simplest possible format: a line for each string (I ensure there are no newlines in the string itself by escaping them with \n) API is password protected because only I can submit the strings. The server compares the strings sent with the current set and records a difference in the log. It also sends a response with translations. Again the simplest possible format: AppTranslator: SumatraPDF 651b739d7fa110911f25563c933f42b1d37590f8 :%s annotation. Ctrl+click to edit. am:%s մեկնաբանություն: Ctrl+քլիք՝ խմբագրելու համար: ar:ملاحظة %s. اضغط Ctrl للتحرير. az:Qeyd %s. Düzəliş etmək üçün Ctrl+düyməyə basın. As you can see: a string to translate is on a line starting with : is followed by translations of that strings in the format: ${lang}: ${translation} An optimization: 651b739d7fa110911f25563c933f42b1d37590f8 is a hash of this response. If I submit this hash with my request and translations didn’t change on the server, the response is empty. Implementing C++ part of translation system So now I have a text file with translation downloaded from the server. How do I get a translation in my C++ code? As with everything in SumatraPDF, I try to do things in a simple and efficient way. The whole Translation.cpp is only 239 lines of code. The core of translation system is const char* trans::GetTranslation(const char* s); function. I embed the translations in exact the same format as received from AppTranslator in the executable as data file in resources. If the UI language is English, we do nothing. trans::GetTranslation() returns its argument. When we switch the language, we load the translations from resources and build an index: an array of English strings an array of corresponding translations Both arrays use my own StrVec class optimized for storing an array of strings. To find a translation we scan the first array to find an index of the string and return translation from the second array, at the same index. Linear scan seems like it would be slow but it isn’t. Resizing dialogs I have a few dialogs defined in SumatraPDF.rc file. The problem with dialogs is that position of UI elements is fixed. A translated string will almost certainly have a different size than the English string which will mess up fixed layout. Thankfully someone wrote DialogSizer that smartly resizes dialogs and solves this problem. The evolution of a solution No AppTranslator My initial implementation was simpler. I didn’t yet have AppTranslator so I stored the strings in a text file in repository in the same format as what I described above. People would download it, make changes using a text editor and send me the file via email which I would then checkin. It worked for a while but it became worse over time. More strings, more languages created more work for me to manually manage e-mail submissions. I decided to automate the process. Code generation My first implementation of C++ side used code generation instead of embedding the text file in resources. My Go script would generate C++ source code files with static const char* [] arrays. This worked well but I decided to improve it further by making the code use the text file with translations embedded in the app. The main motivation for the change was to open a possibility of downloading latest translations from the server to fix the problem of translations not being all ready when I build the release executable. I haven’t done that yet but it’s now easier to implement given that the format of strings embedded in the exe is the same as the one I can download from AppTranslator. Only utf-8 SumatraPDF started by using both WCHAR* Unicode strings and char* utf8 strings. For that reason the translation system had to support returning translation in both WCHAR* and char* version. Over time I refactored the code to use mostly utf8 and at some point I no longer needed to support WCHAR* version. That made the code even smaller and reduced memory usage. The experience I’m happy how things turned out. AppTranslator proved to be reliable and hassle free. It runs for many years now and collected 35440 string translations from users. I automated everything so that all I need to do is to periodically re-run the script that extracts strings from source code, uploads them to AppTranslator and downloads latest translations. One problem is that translations are not always ready in time for release so I make a release and then people start translating strings added since last release. I’ve considered downloading the latest translations from the server, in addition to embedding them in an executable at the time of building the app. Would I do the same today? While AppTranslator is reliable and doesn’t require on-going work, it would be better to not have to run a server at all. The world has changed since I started SumatraPDF. Namely: people are comfortable using GitHub and you can edit files directly in GitHub UI. It’s not a great experience but it works. One option would be to generate a translation text file for each language, in this format: :first untranslated string :second untranslated string :first translated string translation of first string :second translated string translation of second string Untranslated strings are listed at the top, to make it easier to find. A link would send a translator directly to edit this file in GitHub UI. When translator saves translations, it creates a PR for me to review and merge. The roads not taken But why did you re-invent everything? You should do X instead. All other X that I know about suck. Using per-language .rc resource files Traditional way of localizing / translating Window GUI apps is to store all strings and dialog definitions in an .rc file. Each language gets its own .rc file (or files) and the program picks the right resource based on a language. This doesn’t solve the 2 hard problems: having an easy way to add strings for translations having an easy way for users to provide translations XML horror show There was a dark time when the world was under the iron grip of XML fanaticism. Everything had to be an XML file even when it was the worst possible solution for the problem. XML doesn’t solve the 2 hard problems and a string storage format is an absolute nightmare for human editing. GNU gettext There’s a C library gettext that uses .po files. This is much saner solution than XML horror show. .po files are relatively simple text format. The code is already written. Warning: tooting my own horn. My format is better. It’s easier for people to edit, it’s easier to write code to parse it. This looks like many times more than 239 lines of code. Ok, gettext probably does a bit more than my code, but clearly nothing than I need. It also doesn’t solve the 2 hard problems. I would still have to write code to extract strings from source code and build a way to allow users to translate them easily.

2 days ago 3 votes