Startup Oxide has delivered a rack-level system providing cloud-style computing on premises as its first commercial product.

Oxide was founded in September 2019 by datacenter heavyweights CTO Bryan Cantrill, CPO Jessie Frazzelle, and CEO Steve Tuck. It has had three funding rounds to date: A $20 million seed round in 2019; a $30 millionA-round in September 2022; and a $44 million continuation A-round this month that coincides with its first product launch. All the rounds were led by Eclipse Ventures.

Cantrill was CTO at Joyent and distinguished engineer at Sun Microsystems/ Oracle before that. Frazelle, who left in July 2022 to co-found KittyCAD, was a software engineer at Docker, Mesosphere, Google, Microsoft, and GitHub. Tuck was president and COO at software and services company Joyent, also SVP worldwide sales, and held sales roles at Dell before that.

Oxides purpose is to build what it calls a commercial cloud computer, a cloud-scale and cloud-style rack-level, on-premises computing system.

The Oxide cloud computer combines compute, storage, and networking elements as sleds in a plug-and-play rack. It includes the open source software needed to build, run, and operate a cloud-like infrastructure.

This software includes a Propolis hypervisor, a Nexus control plane, Crucible distributed block storage system, IAM (Identity and access management), and OPTE (Oxide Packet Transformation Engine) self-service network fabric. The software is anchored to a hardware root of trust.

The distributed block storage is based on OpenZFS and has configurable capacity and IOPS per volume. Volume size can be scaled upon demand. It has redundancy for high availability. It can integrate with external storage across a network link. Crucible provides instantaneous, point-in-time virtual snapshots for recovery and off-rail backup.

Oxide says OpenZFS checksums and scrubs all data for early failure detection. Virtual disks constantly validate the integrity of user data, correcting failures as they are discovered. There is automated rebalancing of data to preserve redundancy in the event of drive or sled removal.

Pools of resources are available either through APIs, a CLI, or a web-based UI.

Each sled contains an AMD processor, DRAM, and NVMe SSD storage. Each sled is slid into place and needs no wiring, were told. There can be 16, 24, or 32 sleds in a delivered rack. A compute sledhas an AMD Milan EPYC 64-core CPU, 16 x DDR4 DIMM slots providing 512GiB or 1TiB of memory, and up to 10 x U.2 NVMe 3.2TB (2.91 TiB) SSDs. That provides a maximum of 32 x 32 TB 1,024 TB of raw storage capacity. There is 100 GbE link to the racks network switch.

There are two network switches. Each has an Intel Tofino 2 processor with 6.4 Tbps throughput and 232 x 40/100/200 GBASE QSFP-28 uplink ports and 32 x 100 GBASE-KR4 backplane ports.

The rack switch has parts for three networks: An up to 12 Tbps programmable Ethernet ASIC, a secondary GigE switch ASIC, and an FPGA driving a proprietary low-level protocol for board control of other systems in the rack. It is connected via a PCIe link to a compute node for management.

The rear of the rack has a DC busbar and a cabled backplane with blindmated networking. This means self-aligning connectors slide or snap into position as a sled is installed in the rack. There are no power or network cables to plug or unplug.

A blog by Cantrill says:

In his view, the rental-only model for the cloud is not sustainable. A cloud computer has to be rack-scale and one must break out of the shackles of the 1U or 2U server, and really think about the rack as the unit of design.

That helps explain the blindmating. This is a domain in which we have leapfrogged the hyperscalers, who (for their own legacy reasons) dont do it this way, he says.

Oxide claims its rack is up to 35 percent more energy efficient than traditional server racks.

The Oxide rack ships with everything installed and can be set up in around four hours. Customers can use Kubernetes or cloud software tools like Terraform to deploy and configure workloads.

Customers are said to include a US federal agency, the Idaho National Laboratory, and a financial services business. Several Fortune 1,000 companies are said to be interested.

In effect Oxide wants to replace Dell, HPE, and Supermicro on-premises racks with its own hyperconverged infrastructure rack with built-in public cloud facilities. The Oxide rack uses less power and is far easier to own, operate, and run from a hardware and a software sense than traditional server and HCI racks, Oxide says.

Download a specification sheet here.

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Oxide on-prem cloud computer reinvents the server rack Blocks ... - Blocks and Files

Pune, India, Nov. 01, 2023 (GLOBE NEWSWIRE) -- The global cloud workload protection platform market size was valued at USD 2.77 billion in 2022 and is expected to reach USD 12.10 billion by 2030 with a CAGR of 20.5% during the forecast period. Fortune Business Insights, in its report titled, Cloud Workload Protection Platform Market Forecast, 2023-2030.

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Key Takeaways

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Companies leading the Cloud Workload Protection Platform Market are Trend Micro Incorporated. (Japan), Palo Alto Networks (U.S.), VMware, Inc. (U.S.), SentinelOne (U.S.), Microsoft (U.S.), Musarubra US LLC (Trellix) (U.S.), Lacework (U.S.), Orca Security (U.S.), Sysdig (U.S.), Check Point Software Technologies Ltd. (Israel), Cisco Systems, Inc. (U.S.)

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Drivers and Restraints

Integration and Need for Cloud Compliance to Drive Market Trajectory

Integration and the need for cloud compliance are anticipated to drive the global cloud workload protection platform market growth. Cloud storage offers various benefits such as agility, speed, and flexibility and provides security measures to protect data. Key market players have been integrating these solutions to develop strong cloud security compliance solutions.

However, the integration of CWPP faces challenges due to an increased number of misconfigurations resulting from user errors, which is expected to hinder market development in cloud workload protection platforms.

SEGMENTATION

By Component

By Deployment

By Enterprise Type

By End-User

By Region

Regional Insights

With the Presence of Various Cloud Service Providers, North America is Expected to Lead the Market Share

North America is projected to lead the cloud workload protection platform market share, with the market valued at USD 1.25 billion in 2022. The U.S. is one of the prominent countries in the region due to the presence of various cloud service providers. Canada is also expected to show appreciable growth due to the adoption of the cloud in workloads and business models.

Europe is expected to hold a prominent market share in the cloud workload protection platform industry during the study period due to the adoption of the cloud and the integration of cloud security practices for complex cloud environments.

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Competitive Landscape

Leading Players in the Market Expanding Offerings to Attract Diverse Customer Base

The global cloud workload protection platform market includes key players such as Trend Micro Incorporated, Palo Alto Networks, VMware, Inc., Microsoft, Musarubra US LLC, Lacework, Orca Security, and others. The key players are focused on expanding their presence by launching specific solutions and new products to attract a vast customer base.

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Cloud Workload Protection Platform Market?

Cloud Workload Protection Platform Market size was USD 2.77 billion in 2022.

How fast is the Cloud Workload Protection Platform Market growing?

The Cloud Workload Protection Platform Market will exhibit a CAGR of 20.5% during the forecast period, 2023-2030.

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Data-Centric Security Market Size, Share, Trends 2030

Digital Transformation Market Size, Share, Trends and Growth

Cloud Security Market Size, Share, Growth, Analysis

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A new photo series created by the governments cybersecurity agency wants to make people more wary of scamming. It got Shanti Mathias thinking about how limited we are in illustrating and imagining the systems that produce scams.

When the crime happens, theres no broken glass, no loud noises, no neighbourhoods cordoned off. Theres just flatness: a voice on the telephone, black letters on a screen, tapping keys, replying, trusting until it is suddenly clear that what you thought you were doing wasnt happening at all.

Its hard to write about scams, even though they happen all the time; even though thousands of people are targeted each month. New Zealand loses about $20m a year to scams, and thats just what gets reported. Its difficult to imagine the magnitude of the small losses, or the money that is able to be recovered, or the thousands of missed calls and dubious Facebook messages and other near misses that dissolve, back into the ether of ones and zeroes.

Difficult to imagine: yes. Difficult to image, too, and thats part of the problem. Ive written several stories about scams this year, and finding imagery that fits the tone of the stories is challenging. There are endless stock images of people, often older people, looking angry or confused at their laptop, surrounded by credit cards. Then there are the scammers themselves: lit up by rows of binary blue digits, always wearing hoodies, faces shadowed.

These images dont convey the banal malevolence of scams. Theyre not a threat because we are confused about technology, while scammers are experts in manipulating the internet. Scams are a threat because we have to engage with technology. Our society requires us to trust banks and authenticating text messages, trust RealMe, trust the websites we give our address and phone number and credit card details to when we shop. Pictures of people perplexed by the internet fail to illuminate the everywhere-ness of technology, part of all we do.

Cert NZ, the governments cyber security agency, clearly struggles with finding imagery that can help people care about scams, too. A few days ago, I trotted along to an event they were hosting at central Auckland creative venue The Tuesday Club. Scams like an art exhibit: big photos on the wall and little labels. A library of scams: romance and impersonation scams, social media traps and investment scams, job scams and unauthorised access scams. The photos were taken of real scam victims, through webcams on phones and computers. The images were then treated to look pixelated and blurred, uncomfortable. Its called EXPOSED.

The photos are a reminder of all the ways our devices see us: present as we do press ups in time with the woman on YouTube, call our friends, pick our nose, wonder when the work day will be over. And scams come from that place of inattention and ubiquity. My phone is my key to my bank account, my family group chat, my archive of good days with good friends and yet simultaneously, it is the same place where I am in danger from 15 texts telling me I need to pay for a toll road, from message requests accompanied by ersatz pictures of beautiful women.

Everyone is a target, every demographic if you have an email address, a cellphone, social media. One moment of distraction is enough, says Sam Leggett, Cert NZs senior threat analyst. The imagery is highlighting this idea that [being scammed] can happen at any time its a powerful way to understand how exposed your information might be.

Cert NZ has lots of advice for avoiding scams, but this threat happens in the privacy of our own devices what stock images would make it more visible? One that comes to mind is tables of lists of passwords, the backend of a phishing campaign people dont realise that websites all around the world have data breaches including information like email and passwords, Leggett says. Ah, theres the rub often, theres nothing you can do about being targeted by scams, because the information is gone already.

Another image idea, this one conceptual: Someone is knocking at your house, and theyre wearing a mask, so they look exactly like someone you know. The person in the mask asks for the keys to your house maybe theyre your landlord, you let them in to fix something. And then a hacker is inside, now they have your logins, they can access your stuff.

Thats figuratively exactly what happened to William Chen. He used to be an art director, managing photo shoots for magazines so he knows that while the image of himself used in Cert NZs exhibition, distracted and eating breakfast, isnt exactly flattering, thats not the point. Ive put others through it, so its my turn, he says. If a photo of him makes it less likely that other people will fall for a scam, hes willing to be public with it.

A few years ago, Chen was visiting family in Malaysia when he got a message from a Filipino friend, saying that he had been mugged in Manila and lost his passport and needed money urgently. It was an impersonation scam. All the tell-tale signs were there, Chen says ruefully. The scammer wouldnt answer detailed questions, for example, and wanted money paid through Western Union. Over a period of only a few hours, Chen received message after message with harrowing descriptions of his friends misery, and the urgency of help; he eventually went to the local Western Union to send money as instructed, then told his sister about the situation. She immediately told him hed been scammed.

I wasnt sharp enough, he says now. He feels guilty about it and still paranoid that messages he receives on social media might not be legitimate. Its good that [Cert NZ] is raising awareness, but I dont think the government can do much about scams it all boils down to personal responsibility.

Maybe Chen is right, but its not that big institutions are doing nothing about scams. Take the man in the news recently for losing $400,000 to an investment scam. He was repeatedly called by his bank, to warn him that it was a scam. The outgoing government announced a new anti-scam team a few weeks before the election; since the issue isnt highly politicised (or on the ambitious 100 day hit list), the new government hopefully will continue to support this initiative. Banks, especially, will keep putting safety measures in place; an obvious one is payee verification on transfers, so its clear when youre not paying who you think you are.

Pictures of scamming can show victims as human beings: distracted and vulnerable, their information ripe for the picking. The Cert NZ photo series goes some way towards making these images more compassionate, more diverse, less victim-blaming. Theres a deeply complex, psychological element to being scammed the urge to believe that something is true, that someone is trustworthy but in the imagery of scams and the focus on victims, we fail to imagine who is on the other side of the phone.

Taking photos of victims is obvious, if important. Its so much harder to picture the people carrying out the scams, and the systems that enable them. For instance, how do you photograph the thousands of forms with your address or birthday or phone number that you fill out every time you make a useful account on the internet? How do you visualise the profits of a company that didnt hire an extra data engineer and thereby releases your information and thousands of others to potential hackers and scammers via a data breach?

Theres a subgenre of YouTube videos devoted to unmasking scammers through elaborate pranks. This is a reminder that scamming is an enormous global industry, employing thousands of workers in places where the law doesnt want to look very hard for crimes that happen on the internet.

In some parts of the world, there are many more underemployed educated young people than there are well-paying jobs, which can make carrying out scams a viable, if not appealing, option. Thats a product of global inequality, but its difficult to draw a picture of. There arent compelling photos of the dreary office parks in the corners of global cities Abuja, Kolkata, Bandung, Hyderabad, So Paulo, Budapest, Karachi and the workers inside them, carrying out the dull labour of digital deceit.

I dont say this to suggest that the work of scamming is good work, that it is somehow part of global wealth redistribution. Theres no transparency to these payments; the money is unlikely to go to those who need it most, and the losses hurt people with the least financial stability. But trying to imagine what scamming people might look like from every angle is essential if we dont want these to keep happening. While artificial intelligence improves, theres every likelihood that the scams will just get more convincing.

Maybe some form of scamming will always exist, but much of the damage is preventable. The solutions involve individual wariness, as the CERT photos show. But responding to scamming also requires the government to treat it with the urgency it requires, social media companies to cooperate and private institutions to improve their processes. Maybe if all of that happens, scamming will be less profitable, and it wont be a job for people in countries whose governments are incentivised to look the other way. Maybe. Its hard to picture.

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Scams are hard to picture that's part of the problem - The Spinoff

Earn a free on-chain NFT by taking our free course,Crypto Investing: Fundamentals First. Decrypt will cover gas fees for the first 10,000 mints!

Fundamental analysis eschews the analysis of price charts (technical analysis) by looking at a broad set of indicators as well as some well reasoned but somewhat subjective judgements of industry analysts. Before introducing how fundamental analysis relates to crypto investing, lets look at how fundamental analysis is used in traditional investing spaces.

For stock market investors, fundamental analysts look for stocks that are trading below their fair market value, which means stocks that are trading for less than analysts perceive the company to be worth; this means that the current market cap (the number of stocks multiplied by the current price) is less than the analysts believe it is worth.

For example, lets say a company has 5 million shares that are trading for $20 each. This equates to a market cap of $100 million. If analysts believe the company should actually be fairly valued at $140 million, this would equate to a stock price of $28 per share and would be a buying opportunity. Or, if they determined that the fair market value was $80 million dollars, this would equate to a share price of $16. This could also be taken advantage of by shorting the stock or selling it if you already have it in your portfolio (in the belief the price will drop). Investing based on fundamental analysis assumes the market eventually realizes that a stock is not valued correctly and adjusts the price accordingly.

Fundamental analysis predicts price movements over a longer time frame, while technical analysis tends to favor short-term price movement predictions.

If fundamental analysts determine that the current stock price seems to accurately reflect the companys value (in this case they believe it is valued around $100 million), there is no actionable investing play. In this case, they would likely move on in order to see if there is an opportunity to profit off a different company that is overvalued or undervalued.

In general, fundamental analysis predicts price movements over a longer time frame (sometimes years), while technical analysis tends to favor short-term price movement predictions. When it comes to stock investing, metrics to consider include: the outlook of the industry (where the stock is), the state of the economy in general (bullish or bearish), the performance of the stock in question (earnings per share, profitability, and so on), and the quarterly and annual reports given by the company in question.

The use of hard numbers and metrics is called quantitative fundamental analysis. Using these standardized measurements is a core part of fundamental analysis, but there is another side to these longer term price predictions that utilizes what is known as qualitative fundamental analysis.

More subjective and less tangible in some respects, qualitative fundamental analysis measures the quality of a company by looking at its name recognition, leadership team, organizational structure, and other market differentiators such as more advanced or patented technology or products. While quantitative analysis is more of a science, qualitative analysis is more of an art. In general, it is often suggested to combine both types of fundamental analysis to get a clearer investing picture.

Fundamental analysts in the crypto sector use similar methods, but must rely on different data sets and qualitative measures. With no quarterly reports and blurred industry designations, these crypto analysts must look at other indicators. When it comes to quantitative analysis, looking at the tokenomics (covered in our previous article) is a good place to start. From there, you may want to delve into qualitative analysis by looking at the core team, early investors, the whitepaper, previous project accomplishments, and the trajectory of the upcoming roadmap and their chances of success.

Opinions can certainly be mixed when analyzing some of these characteristics. Lets take the leader or team of a project. Some analysts value a public and open team of well known individuals with past success. On the other hand, other analysts may value a leaderless project that may have a pseudonymous or anonymous team or no leader at all.

For example, Bitcoin doesnt have a headquarters, board of directors, or even a known founder. While Satoshi Nakamoto created Bitcoin, no one knows who this person or group is. For analysts that may be concerned about the legal or regulatory risks that come with a crypto company or team, this could actually be considered a positive not a negative. In keeping with this, other analysts may prefer the governance of a decentralized autonomous organization (DAO) over the centralized decision-making of a small team.

In much the same way that you wouldnt compare CocaCola with Ford or McDonalds with SpaceX (but you would compare Ford with Tesla), you need to separate crypto projects by their intended use cases and their relevant sectors. Use cases for the blockchain include: cryptocurrency, oracles, decentralized finance (DeFi), gaming, AI, decentralized storage, real-world asset (RWA) tokenization, and much more.

Once categories are established, you need to try to answer the following questions

Of course, the questions are the easy part of the test. The answers are what require some work; they get graded as time goes on and ones predictions are validated or proven wrong. When it comes to crypto, many of these sectors are expected to gain market share from centralized alternatives. Lets look at cloud storage as an example.

The cloud storage market was valued around $90 billion in 2022 and is expected to surpass $300 billion by 2028. The crypto sectors decentralized storage market is currently valued at around $4.75 billion. If you believe that decentralized cloud storage options will gain market share from centralized cloud storage alternatives in this burgeoning industry, you may want to crunch some numbers to see if investing in this sector makes sense.

Popular options for decentralized cloud storage include Filecoin, Arweave, and Storj. If you believe they are undervalued, you may want to select ones that you believe have the most promise, are undervalued relative to their competitors, or have higher market penetration. To reduce your risk, you may simply want to diversify your exposure into a number of these projects.

Likewise, many make price predictions for BTC using these questions:

Many of the longer term BTC price predictions utilize fundamental analysis to calculate a variety of prices ($100,000, $250,000, or $1,000,000/BTC) at a variety of future dates. These numbers are generally not picked out of thin air; they are backed up by fundamental analysis. Of course, the difference in how you answer some of these key questions about BTC accounts for the large price disparities in these predictions.

Oftentimes, this analysis must accurately weigh BTCs fundamental or intrinsic value. For BTC proponents, some view this technology as revolutionary and almost priceless. For crypto skeptics (Peter Schiff, Warren Buffet), many see BTC and other cryptocurrencies as being worthless and posit that they have no inherent or intrinsic value. Many fall between these two extreme viewpoints in some sort of fundamentally analysis-derived middle ground.

Knowing the core concepts about fundamental analysis can help you make more informed investing decisions. This may allow you to understand the rationale of price predictions given by experts or to even make your own rough estimations on future price movements. Ultimately, the decision is up to you on how to assess the value of this burgeoning and dynamic space. While many have predicted the fall of Bitcoin, Ethereum, and the crypto ecosystem writ large, it is still continuing to be a major economic powerhouse with a combined market cap in excess of $1 trillion (down from a high of nearly $3 trillion in 2021).

As the crypto market is still nascent and very volatile, you may want to strongly consider reading and listening to the fundamental analysis of crypto experts and analysts. While it is often quite difficult to predict the crypto prices in shorter time horizons (days, weeks, and even months), using fundamental analysis can help you predict the future price of these assets in 510 years provided the analysis is done correctly and the critical assumptions become reality.

Disclaimer: This investing series is strictly for informational and entertainment purposes. It should not be construed as financial or investment advice. Do not invest based on price prediction tools or forecasts laid out in this series. Please consult an investing professional or financial planner if you feel you need investment guidance.

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Use Fundamental Analysis in Crypto Investing: The "Get Rich Slowly" Approach - Decrypt