Introduction dates of commercial driverless trucks are increasingly coming into focus. Daimler Trucks has – for the first time – set a date for commercialization of their self-driving trucks. Meanwhile, Aurora has provided a fresh data dump of their plans to put driverless trucks on the road next year, as well as updated metrics. Both companies have provided business projections. Waymo is taking a contrary approach.

In the automated driving world, vehicle manufacturers move on different timescales than startups. They don't have to be in a hurry because they’re selling huge quantities of cars and trucks every year. Compare this to the startup world, where venture investors are looking to see an investment return, creating a “get to market really fast” mentality. In between are the publicly traded companies with similar pressures, but the investor base is much broader (and very fickle). Publicly traded Aurora and venture-funded Kodiak Robotics both aim to release their first fully driverless truck to customers in 2024. As a perfect example of these dynamics, Daimler’s trucks will come a few years later.

There’s plenty to unpack, let’s get at it.

Daimler’s Boston Truck Party

Daimler Trucks spun off from Mercedes-Benz about a year ago. The first-year anniversary was commemorated by a capital markets day in Boston last month, where CEO Martin Daum covered a wealth of issues, including EV, AV, recurring revenue streams, and their ESG approach. Not surprisingly, his overall outlook was optimistic. This Daimler deck from the event offers fascinating insights.

Daum announced that their autonomous trucking product could come “as soon as” 2027. Previously, neither Daimler, nor their subsidiary Torc Robotics, had stated a specific launch date, only referring “the last half of this decade.”

Here's what’s cool: not only did Daum announce their planned commercialization date for automated trucks, he laid out a four-phase deployment approach encompassing where they will deploy and in what sequence. Phase 1 will encompass California, Arizona, New Mexico, and Texas on interstate highways I-10 and I-40. The I-40 route will continue into Arkansas and on to Memphis. Oklahoma City to St Louis on I-44 is also included. Phases 2 and 3 will add more Texas routes, as well as continuing eastward from Memphis on I40, connecting to I-95 on the Eastern seaboard. I-10 plays prominently coast to coast, and in Florida there’s a tie-in with I-75 to reach Atlanta. I-95 and the major interstate highways nationally come online in Phase 4.

As you can see from the image below, next to the four-phase map is a bar chart indicating mileage added each year from 2027 to 2030. This is just conceptual, as the vertical axis is unlabeled. There’s no explicit statement that the map phases match with these four years, but with the two charts side by side that’s my hunch.

Daum also reiterated Daimler’s “open” go-to-market plan, in that they will sell customers their homegrown robotic driving system via Torc Robotics, at the same time supplying vehicles that customers can equip with autonomous driving technology from other vendors. The latter is very important for the broader automated driving industry, as this stimulates competition across the ADS space.

Daum offered an interesting projection on the business side too. He said that in 2030, the company expects to generate over 3 billion euros ($3.30 billion) in revenue and 1 billion euro earnings (before interest and taxes) from automated truck operations.

What do Daimler’s revenue numbers mean in the real world? To answer this question, I turned to my go-to trucking expert Lee White, who spent decades at UPS and after retirement worked for TuSimple as VP of Strategy until late last year. At UPS he was very involved in their evaluations of automated driving tech and setting a path forward for eventual adoption.

I asked Lee, who now runs LM White Consulting, about the Daimler numbers. He came back to me immediately (I think he did the math in his head): “Breaking down the $3B Euros into trucking math, it would mean more than 6,000 trucks driving 1,000 miles a day.” He assumed $2 per mile with the trucks running five days per week.

In North America, Daimler Trucks sells around 70,000 Class 8 trucks per year via their Freightliner brand. Using White’s number of 6000 trucks, this works out to 1500 per year.

White sees the information shared by Daimler as very encouraging to the AV trucking industry. “We have the leading OEM communicating definitive plans on when they will enter the market, as well as the expected revenue stream. It gives us some commercial handles we can hold on to for the future of AV trucking. That is a very bright north star for the industry!” He also noted that Daimler did not communicate the business model or details of how they will generate that $3B Euros. At some point I expect we’ll be hearing about this, but not anytime soon.

One of the strongest plays in automated trucking is Torc Robotics, 51% of which is owned by Daimler Trucks. I recently had an opportunity to experience the Torc automated driving system on freeways near their operations center in Albuquerque. From knowing the team for some time and having many discussions over the years, I expected their truck would run well on the highway. I was not disappointed. The vehicle operated as well or better than an alert professional truck driver, handling lane changes, merging traffic, and freeway-to-freeway interchanges. Their in-vehicle monitor showed vehicle data, relative lane position, and the presence of nearby vehicles, much like one sees in a robotaxi ride. Their “lane bias”technique was particularly effective, moving laterally a few feet to create more space between the host truck and another vehicle passing or merging. This is illustrated in the image below. As another truck was starting to pass the Torc truck on the left, the Torc system checked lane occupancy on the right. See that the right lane had no traffic, the vehicle moved towards the right-side of its lane, creating more space between the passing truck and the Torc truck. The image shows the latter stage of the passing maneuver, at about the time the Torc vehicle would move back to the center of the lane, i.e. the default position.

If you’ve ever driven a large vehicle (like the RV I used to have) on the highway while passing a truck, you’ll know that there can be squirrelly wind and air pressure between these two large bodies with significant air passing between them. Controlling the vehicle can be a bit challenging. This is why the Torc vehicle creates space when possible, as just one more aspect of reducing risk.

Torc also demonstrated their capability to run on surface streets near the freeway. More on this in an upcoming article.

Aurora Raises the Stakes, Death Vigil Postponed?

Aurora, another leader in the automated trucking space, provided their 2Q23 report last month. It was upbeat yet they backed up their assertions with data and metrics which I’ll discuss here, along with some industry context.

Aurora said they are now logging over 17,000 commercial miles per week. So far this year they have delivered 2,290 loads for customers including FedEx, Werner, Schneider, and Uber Freight, driving more than 630,000 commercial miles with nearly 100% on-time performance. The Aurora driverless-intent vehicles are being operated under the supervision of vehicle operators.

With all this activity and promising performance indicators, one might think all is rosy. But the doomsayers have long been holding a vigil for Aurora’s demise, due to the company burning through cash at a fast pace. “Aurora can’t survive at this spending pace and will run out of money long before they generate any substantial revenue!,” has been the typical refrain. My recent articles have pushed back on this view, simply because I couldn't imagine Aurora’s Board and leadership blithely trundling along until the bank account hits zero. My position has been: “I don't know what the plan is, but they’ve got to have a plan. It’s just not public.”

Aurora’s burn rate has been going in the right direction. The company said it narrowed its net loss for the 2Q23 to $218 million compared with a loss of $1.1 billion in the same quarter last year. “Still much too high,” my colleagues would say.

But then, in July, Aurora unveiled their plan, raising $853 million of total gross proceeds through a public offering, which included “very strong support from key institutional and strategic investors” according to their press release. Aurora said their beefed-up total liquidity is now $1.6B “which will fund us through our planned Commercial Launch and into the second half of 2025.”

Problem solved? Not yet. Given their cost structure, revenues by mid-2025 may be substantial but far short of profitability. Once they have a mature self-driving product, they may reduce staff to lower the cash burn. Still, another funding infusion will almost certainly be needed in a couple of years.

But there’s more! In researching this article, I discovered a June 30 SEC 8-K filing on June 30 in which the company estimated they will need “$1.6 billion to $1.7 billion in incremental capital beyond its cash, cash equivalents and short term investments as of June 30, 2023 to become free cash flow positive on a run-rate basis by the end of 2027.” The $885M raised in July was roughly half this amount. Therefore, they “have a plan” to again raise funds at some point in the future. The ability for Aurora or any other company to raise funds in a few years cannot be known now. This gives the death-vigil-keepers an excuse to proclaim eventual doom if they want, but I suggest they shift their dooming to other more-likely players.

In Lee White’s view, “the biggest issue for Aurora will be the speed and path to commercialization in order to get to cash flow positive and offset the over $200M per quarter spend. This won't be done by 20 trucks running between Dallas and Houston or any sort of in-house truck build out. Aurora will need more than 1500 trucks running with the Aurora Driver 1,000 miles per day to create revenue offsetting the ongoing staffing and R&D expenses at Aurora: that is the challenge in the next 24 months.” He also pointed to a key item not in Aurora’s control: sourcing 1500 driverless-ready tractors from their manufacturing partners, which require specialized levels of redundancy and other fail-safe features.

Aurora has strong partnerships with PACCAR and Volvo, but the pace at which these companies will produce driverless-ready trucks, and the number that will be allocated to Aurora, has not been discussed publicly. Aurora’s 2Q23 report discussed recent progress in this regard. During 2Q23 PACCAR completed a 1.5 million equivalent mile durability test of a Kenworth cab with the Aurora Driver hardware installed. The company said the Aurora Driver hardware remained fully functional at the end of the test. Regarding Volvo Autonomous Solutions, Aurora expects to begin testing a prototype Volvo VNL, powered by the Aurora Driver, in the first quarter of 2024.

The Aurora Scoreboard

Meanwhile, Aurora has released a new software version (Aurora Horizon Beta 7.0) and continues to add substance to their go-to-market narrative. Their premise goes like this: “The Aurora Driver will be ready to launch when we have a closed Safety Case for our Dallas to Houston lane. Our Safety Case is a comprehensive, evidence-based approach to confirming our self-driving vehicles are acceptably safe to oper­ate on public roads. It goes beyond just ensuring the vehicle drives well enough for a demo; rather, it demonstrates that our product, and our company, are holistically and sustainably safe.”

Key to this process is the Aurora’s Autonomy Readiness Measure (ARM), which they explain as “a weighted measure of completeness across all claims of our Safety Case for the launch lane, which reflects the percentage of work needed to move from Feature Complete to our next critical milestone — Aurora Driver Ready.” The ARM is the progress tracker, which reached 65% at the end of the second quarter, a 21-point increase from the previous quarter. Aurora continues to be very bullish, stating that “we are on track to achieve Aurora Driver Ready later this year” and “we continue to expect to be contracted for commercial launch by the end of the year.”

While the ARM is a safety metric, Aurora’s Autonomy Performance Indicator (API) measures the operational performance of the Aurora Horizon service in real-world conditions. “This metric allows us to track not just the state of our tech­nology, but the maturity of our processes and procedures in operating our business,” Aurora says. In particular, any need for on-site support will severely erode profitability – imagine the cost of dozens of support vehicles on standby along the route, complete with dispatchers and highly trained technicians. So, the indicator penalizes the use of on-site support. The API also considers autonomous miles driven which require remote input from the Aurora Services Platform. Aurora says that for 2Q23, the API was 97%, a slight increase from the previous quarter.

Compared to performance in the first quarter, about half of the 2Q loads had an API of 100% and nearly 75% of the loads had an API greater than or equal to 99%.

What about the conditions that required support? Aurora emphasized that none of the support their vehicles received was required to keep the vehicles operat­ing safely: “In over 100,000 commercially-representative miles driven on the launch lane in 2023, including over 65,000 commercial miles during the second quarter, we experienced zero safety-critical interventions.”

Again, I turned to Lee White for a trucking professional’s perspective. What does this 97% API level mean to a trucking fleet? He said, “When I receive these updates, I evaluate them on a path to deployment. Translating Aurora’s 97% Autonomy Performance Indicator of 97% to trucking reality, this means one out of every 33 loads would have needed some type of ‘assistance’ - and that could be as basic as the truck would have called the mission oversight center for help, or perhaps Aurora would have sent out a recovery driver if there was deeper intervention required. On-Road assistance issues for trucking fleets results in potential service failures for customers and a much higher cost for the maintenance issue. The trucking fleets have invested in their maintenance programs to 'de-risk’ on-road breakdowns as much as possible. For example, OEMs and fleets use preventive maintenance schedules and advanced telematics information to predict and schedule maintenance to be done in their shops, to minimize the chance of a breakdown on road. The Best-in-Class fleets are at one breakdown per 1,000 truck days on road – so they have achieved success in limiting the on-road exposure both in service and in cost.” Lee provides a very sobering reference point: how long will it take for Aurora, or any other driverless truck provider, to achieve this level of performance?

Is Waymo Via Out For Good?

While Daimler Trucks and Aurora have been revving their engines, Waymo is downshifting. Waymo has been more in the news regarding its robotaxi operations, but their long-running truck AV program, called Waymo Via, has resulted in a very strong pre-commercial offering. However, early this year Waymo greatly reduced operations of their driverless trucking commercialization activities. In July, they put the whole thing on ice, repurposing many of their trucking staff to robotaxi operations. As Waymo co-CEOs Tekedra Mawakana and Dmitri Dolgov noted in a blog post, “With our decision to focus on ride-hailing, we’ll push back the timeline on our commercial and operational efforts on trucking, as well as most of our technical development on that business unit.”

Interestingly, though, in July both Waymo and Daimler Trucks re-affirmed that their long-running partnership to develop a driverless-ready tractor will continue.

Did Waymo get it backwards? Back to Lee White, my truck business sensei, for more truck math: “I am disappointed with Waymo Via's announcement. I am very impressed with what Waymo and Cruise are doing with the passenger cars from a commercialization standpoint – they are adding cities and demonstrating that AV vehicles can be deployed safely at scale! My disappointment is on the economics; a 3% penetration into the trucking market is worth more than a 50% capture of the robotaxi total addressable market. That 3% penetration can be achieved in the lanes where Waymo Via and the other AV trucking companies are currently testing. From my viewpoint, Waymo Via has the potential to provide a faster ROI on trucking lanes than the passenger side. And Waymo Via already has the OEM secured with Daimler, which is critical to scaling. Let's hope this is a short pause, with Waymo’s return powered by the economics of AV trucking.”

Why would Waymo step away from such a straightforward revenue play on the trucking side?

I can (facetiously) imagine the Alphabet Board saying to Waymo, “You’ve had years of fun with your people-moving sandbox and your freight-moving sandbox. Times have changed and now you have to pick one. Which will it be?”

It’s important to remember that at a fundamental level, Waymo was founded to “change the world” in personal mobility. After an early exploratory phase examining highway driving and personal vehicles, they zeroed in on robotaxis, which have immense potential to revolutionize the way people travel. This has always been their Big Audacious Dream and now they’re of one mind with a single offering. For Waymo to step away from robotaxi and retain trucking could have sent shockwaves through their investor base and cause a revolt from the tech team.

Indeed, Waymo has a very strong offering in the driverless trucking space. If they hold on to this and decide to re-energize it in a couple of years, Waymo Via will be a major player (and could even come to market sooner than Daimler/Torc). For now, there are some strong synergies at play in their new approach. I have long said that robotaxis must be able to travel on freeways as well as surface streets to fully scale up and generate the revenues they need. The Waymo Via team has been living and breathing highways for years. I’m confident that the highway-level autonomy smarts from their former truck developers are quickly being applied to a “Gen2” Waymo robotaxi that can travel on all the types of roads that we are able do on a daily basis. Waymo has already noted in recent press they are now testing on highways in preparation for commercial launch beyond streets only.

Where Are We Now?

Along with their deployment partners, we’re now down to five major players developing commercial autonomous trucks operating long-haul on highways: Aurora, Kodiak, Plus, Torc, and Waabi.

Lee White and I are both upbeat about recent developments. In particular, he notes, “This is fantastic news that Aurora completed this recent fundraising in this challenging capital market. It is a very positive sign for the entire AV Trucking industry.” I would add that, though they would never admit it, Aurora in particular is probably very happy to see their major competitor, Waymo, exit the stage.

I can’t stress enough the critical role of the truck manufacturers. We are now in a world where four major truck OEMs are deep into the platform development for truck autonomy: Daimler, Iveco, PACCAR, and Volvo. Traton is the big question mark. They were a significant player when their partnership with TuSimple was underway from late 2020 to the end of last year. Traton dissolved the partnership due to safety mishaps and management turmoil at TuSimple. They developed significant autonomy expertise on the manufacturer side of this relationship, and I surmise they have been industriously looking for a new partner during 2023. If/when an announcement is made, it could be one of the most significant developments of the year.

In September 2014, the Mercedes Benz truck division enthralled bleachers-full of industry luminaries and journalists at a test track in Germany by introducing their Future Truck (FT). Automated Class 8 trucks were zooming around the loop at full speed, pulling trailers emblazoned with “FT 2025” (see picture below.) I highly recommend the accompanying video, which presented the concept of the driver turning over control to the autonomy and then swiveling around to do other work on his computer. While the press release did not state that the company had “set a date” for introduction, the 2025 timing was a subtle message of their ambitions. I suspect that the management and engineers of Mercedes had no clear idea at the time how they would proceed to achieve full commercial autonomy by 2025, but a vision was set. Mercedes, now Daimler Trucks, has been continuously working toward the now announced 2027 date ever since then, with forays into truck platooning, developing increasingly sophisticated Advanced Driver Assistance Systems, and eventually acquiring Torc Robotics and ramping up significant internal resources to now have a definitive launch date.

Yeah, Daimler is late by two years. At least according to the brave announcement of yesteryear. While they may not be first to market, Daimler’s entry will be a definitive marker. If all happens as planned for the companies discussed here, the real-deal launch of driverless trucking – at scale – is not far away.

Disclosure: I am a strategic advisor and/or hold equity in companies named in this article, including Aurora, Daimler Trucks, and Plus.

Gideon Lichfield: If I were a cynic, which of course I'm not at all …

Mustafa Suleyman: [Chuckle] Not at all.

Lauren Goode: Not Gideon.

Gideon Lichfield: I might say that you and the AI companies are setting up a pretty sweet deal for yourselves, because you're getting to say to government, “Look, you, government, can't possibly understand this stuff well enough to regulate it, so we're going to voluntarily set some guardrails, we're gonna drive the agenda, we're gonna decide how precautionary the precautionary principle needs to be.” And so I think the question I'm asking is, what is the incentive of the private sector which leads the conversation because it has the know-how to set standards that are actually good for society?

Mustafa Suleyman: If we could get formal regulation passed, I think that would be a good start. But you're right, good regulation, I think, is a function of very diverse groups of people speaking up and expressing their concerns and participating in the political process. And at the moment we are sort of overwhelmed by apathy and anger and polarization. And yet now is the critical moment, I think, where there's plenty of time, we have many years to try to get this right. I think we have a good decade where we can have the popular conversation, and that's partly what I'm trying to do with the book and partly what others are trying to do with the voluntary commitments too.

Gideon Lichfield: What are some of the scenarios that you predict that most people probably can't even imagine that might happen if we don't manage to keep these technologies under control?

Mustafa Suleyman: Well, I think in sort of 15 or 20 years' time, you could imagine very powerful non-state actors. So think drugs cartels, militias, organized criminals, just an organization with the intent and motivation to cause serious harm. And so if the barrier to entry to initiating and carrying out conflict, if that barrier to entry is going down rapidly, then the state has a challenging question, which is, How does it continue to protect the integrity of its own borders and the functioning of its own states? If smaller and smaller groups of people can wield state-like power, that is essentially the risk of the coming wave.

Lauren Goode: I'm so intrigued by what you're doing with Inflection, because when I think about your background, you've worked in politics, you've worked in social good, you, of course, ended up cofounding DeepMind and then worked at Google. But you also, you wrote a book and you seem to have these diplomatic intentions, you believe in collaboration. Why are you a startup founder?

Mustafa Suleyman: I'm happiest when I'm making things. Really what I love doing is deeply understanding how something works, and I like doing that at the micro level. I love going from micro to macro, but I can't stay just at macro. I am obsessed with doing on a daily basis, and I guess that's the entrepreneurial part of me. I love “What are we gonna ship tomorrow? What are we gonna make? What are we gonna build?” If I had to choose between the two, that's what makes me happiest, and that's what I like to do most of the time.

Microsoft Surface Laptop 5
Over the past couple of years, Apple has stirred up the notebook market with its M1 and M2 processors. While Apple’s new silicon has given its competitors a kick in the pants, there is still a lot of functionality to be desired from Apple’s new M1 and M2-based MacBooks.
In my last comparison of the MacBook Air M2, I compared it to the Surface Laptop 4 at the same price point, with as similar as possible specifications. I highly recommend practicing the comparison, which you can find here. I make a very similar argument in my comparison of the Surface Laptop 4 and the MacBook Air M2 and reference that comparison throughout this comparison, noting the upgrades and enhancements that the Microsoft Surface Team made to the Surface 5. While the MacBook Air M2 has disruptive raw performance and performance per watt (PPW) within the notebook market, it has inferior gaming, productivity, web, and connectivity experience to that of the Surface Laptop 5.
I have compared the MacBook Pro and the Surface Laptop Studio, the Surface Laptop 3 and the MacBook Air M1, the Surface Book and the MacBook Pro, and the Surface Laptop 4 and the MacBook Air M2. Now I want to compare the Surface Laptop 5 to the MacBook Air M2.
Preface
As I did with the other MacBook Air M2 comparison, I want to preface it with my expectations of the benchmarks and why I am comparing both systems.
I expect the Arm-based Apple Silicon to outperform the x86-based Intel Core processor and Intel Iris GPU benchmarks. Apple’s silicon is more efficient and is based on a smaller node; the M2 is based on “5nm” technology, while the 12^th Gen Core processor is based on Intel 7. However, Intel has changed the architecture of its 12th Gen Intel Core processors to have performance (P-cores) and efficiency (E-cores) cores. In my comparison of the Zephyrus m16 and the Apple MacBook Pro, the Zephyrus m16 with an 11^th Gen Intel Core processor and NVIDIA graphics won out in raw performance but tanked in battery life. The change in architecture should offer a better PPW, especially for these small, ultra-mobile form factors. Although I do not do a battery test and none of my benchmarks are on battery, I believe the Surface Laptop 5 has sufficient enough battery life to make a battery test unnecessary.
Both devices target a very similar audience. The Surface Laptop 5 and MacBook Air M2 target folks who want a smaller form factor laptop, don’t need a significant amount of performance, and are looking to be productive. I would even throw in some light gaming as I believe both devices have the raw performance to play the most strenuous games.
Benchmarking methodology
My goal with these benchmarks is for my testing and experience to be easily replicable with benchmarks that are easily accessible. Benchmarking is not my full-time job and is used to show each device’s performance under specific parameters—whether that is API, GPU or CPU, etc. Each benchmark has been chosen to express the capabilities of each device.
My methodology has not changed. Both systems have default settings and are exactly how they came out of the box, except for sleep settings. Both systems are run on AC and connected to their out-of-the-box charges rather than running on DC and using the battery. Both systems were also in the same room running the same test side-by-side, and each benchmark was run three times back-to-back. The results are the average of those three runs.
I have split this comparison into three parts—Creativity, productivity, and gaming. I believe all three categories are important to the target audience of these systems.
Device Specifications
The Surface Laptop 5 and MacBook Air configurations have been chosen based on price and model. Both systems are priced at around $1,699.99, but the Surface Laptop 5 is currently on sale for $1,399.99, saving $300. Both devices are configured to have their highest respective processors and 16GB of memory, and 512GB of storage. Below are the full specifications of both devices:
Apple MacBook Air M2 2022

Content creation
If there is one category that the MacBook excels at, it is content creation. Most people buy Mac devices for their ability to create content, and Apple has made it clear that content creation is its target market. However, Apple targets a very niche category of content creation and a large chunk of content creation, like CAD and product design tools are left out of the question. In a study done this year (April 2022) by Principled Technology, “the Windows-based Surface Laptop Studio models we tested were compatible with all 31 Rhino®, Autodesk, Dassault Systemes, and Siemens professional CAD apps and the macOS-based MacBook Pro models we tested were only compatible with 10.”
While the MacBook Air targets a very mobile audience, I believe Apple is still pulling toward its audience of video and graphic design with the MacBook Air M2. It definitely has the performance.
I have chosen the Cinebench 23 benchmark to show off the 3D rendering capabilities of the Surface Laptop 5 and the MacBook Air M2. Cinebench 23 has two benchmarks, a multi-thread (MT) benchmark and a single-thread (ST) benchmark. According to Maxon’s website, “Cinebench is a real-world cross-platform test suite… providing a more accurate measurement of Cinema 4D’s ability to take advantage of multiple CPU cores and modern processor features available to the average user.”
I believe Cinebench 23 should deliver us a good idea of how well these systems handle 3D computer animation, modeling, simulation, and rendering using the CPU of both systems. I chose it over other considerable benchmarks like Blender to get an idea of CPU performance rather than GPU performance.
Cinebench R23 MT and ST benchmark
It is worth noting that the 12^th Gen Core i7-1255U has 2 P-cores and 8 E-cores. Hyper-Threading is only available on the P-cores, making for a total of 12 threads. The M2 chip has 4 performance cores and 4 efficiency cores with one thread per core. As we will see with the benchmarks, I believe this is why the Surface Laptop 5 scored lower than the MacBook Air in multi-threading. Although it has more threads, it has half of the performance cores.
The Surface Laptop 5 wins out for ST performance, while the MacBook Air keeps its distance for MT performance. While the MacBook Air is still more powerful than the Surface Laptop 5, this shows that the M2 chip is not out of reach of its competitors like many would think.
As I said in the previous comparison of the MacBook Air, I believe this is at the lower end of importance because people who need a laptop for video editing and rendering will look for more powerful and performant devices. Content creation categories that I believe users will use these systems for would be for podcasts, video calling events, and writing. These categories appeal more to a matter of preference—Microsoft 365 or iWork—than to device performance.
I do believe versatility plays a considerable role in choosing these devices. Most content creators would be doing this light content creation on the go, where versatile tools like a touch screen and would be more beneficial than slightly more multi-threaded performance.
On top of having a touch screen, the Surface Laptop 5 has support for the Surface Slim Pen and Pen2. While Pen usage is slightly more awkward than on a Surface Pro or Surface Studio device, it works flawlessly. I would not call it a replacement for a Surface Pro or Studio, especially considering it does not have the G6 processor and haptic feedback. For the MacBook Air M2, its most redeeming qualities with respect to versatility is that it is slightly lighter, has more battery, and performs better than the Surface Laptop 5.
Productivity
For the productivity category, I wanted to measure each device’s ability to get things done efficiently and productively. Not only are we looking to get things done, but we are also looking to see the quality and quickness of the outcome. Anyone can write a page essay, but not everyone can do it productively and efficiently. Like content creation, where small form-factor notebooks rely on versatility as much as performance, productivity relies on the quality and versatility of the tools provided. With that said, I want to compare how both systems handle web browsing performance and productivity performance and then look at each system’s productivity and multitasking experience.
I used Web XRPT4 on two different browsers to measure web browsing performance. WebXRPT 4 is a benchmark created by the folks at Principled Technology (PT). In the words of PT:
“WebXPRT 4 is a browser benchmark that compares the performance of almost any web-enabled device. It contains HTML5, JavaScript, and WebAssembly-based scenarios created to mirror the tasks you do every day: Photo Enhancement, Organize Album Using AI, Stock Option Pricing, Encrypt Notes and OCR Scan using WASM, Sales Graphs, and Online Homework.”
I ran both systems on their respective default browsers and then both on Chrome. The MacBook Air uses Safari 16.1, and the Surface Laptop 5 uses Edge (Chromium) 108.0.1462.42.
Web XRPT4 benchmarks on in Chrome and default browsers
The MacBook Air M2 maintained its lead over the Surface Laptop 5, but the difference could be considered nominal and, in most cases, are unnoticeable to the everyday user. It is no surprise that the Surface Laptop 5 works equally well on Chrome as it does Edge. Chrome and Edge are built on the same Chromium browser. Out of the three browsers, Chrome, Safari, and Edge. I believe Edge offers more to the productivity experience.
My assessment of the Edge browser holds true as it did about two years ago and then some. Since that assessment, Microsoft has added vertical tabs, Collections, and, recently Workspaces for a collaborative web browsing experience. While I was initially hesitant to use vertical tabs, it is a feature I cannot live without and is a complete game changer.
Yes, the Edge browser is available on macOS, but vertical tabs are not as useful on the MacBook Air M2 since it cannot snap the browser window next to my Word document. A core value proposition for the vertical tabs feature is that it saves room while giving a better place to manage tabs. This lack of window snapping brings me to my next point: Windows is so much better at multitasking hands-down.
I will quote myself from my last comparison to relieve the tension of what meaningful multitasking consists of:
“Multitasking on a laptop is where the device is multitasking and providing a service for the user that makes the person’s task more productive or efficient.”
While the MacBook Air M2 is marginally more performant in the web browser, its productivity and multitasking experience is lacking compared to the Surface Laptop 5.
If Stage Manager is Apple’s solution for those who want better multitasking on macOS, it should stick to iPhones. Not only would Stage Manager be more useful for a touch screen device since you could grip the display and select the group, it is also inefficient. Aesthetically, the thumbnails look great, but the thumbnails take up a significant amount of screen real estate for a task that Apple users already used with a three-finger touchpad gesture. Yes, the thumbnails contract when the window is close to it, but it adds little value for multitasking. Another aspect of Stage Manager is that it must be turned on from the settings, adding an extra step to multitasking that I believe is unnecessary. It shows that the MacBook’s ability to multitask is not a center point (surprise) to the MacBook when it should be.
CrossMark is another benchmark that I used to measure the productivity of each device. Business Applications Performance Corporation (BAPco), the creator of the benchmark, says, “CrossMark measures the overall system performance and system responsiveness using models of real-world applications.” It measures a system in three areas: productivity, creativity, and responsiveness. I believe this is a sufficient benchmark to show how each system is handling a workflow with word processing, document editing, practicing and writing files, and editing photos and videos. I will deliver the overall CrossMark score and highlight the Productivity score which looks at office-specific workloads.
The CrossMark benchmarking shows the overall score and the Productivity score per system
The MacBook Air M2 scores higher than the Surface Laptop 5 in both the overall and productivity scores. Again, I was not expecting the Surface Laptop 5 to surpass the MacBook Air M2 in any performance benchmarks, but I believe this shows that the Surface Laptop 5 can keep up with the MacBook Air M2 by a margin of about 10%. Where the Surface Laptop 5 lacks in performance, I believe it makes up for with versatile features.
The Surface Laptop 5’s multi-touch display with pen support allows it to do more on the go than the MacBook Air M2, which lacks touch. The pen support enables the user to sign documents directly from the Surface Laptop 5 without needing to switch devices. It also has more functionality with Android apps than the MacBook Air with iOS and iPadOS apps because of its touch support. The touch screen is also more useful in scenarios with less room, like an airplane. There have been countless times when I use the touch display on my notebook because it is easier to use in my limited space on an airplane.
The Surface Laptop 5 is more versatile in the office as well. Its Thunderbolt 4 support makes it great for hot desking. Rather than connecting multiple dongles, the Surface Laptop 5 is able to connect up to two 4K monitors at 60Hz. The Surface Laptop 5 TB4 is also backward compatible with earlier generations of Thunderbolt devices, making it an optimal upgrade for existing setups. On the other hand, the MacBook Air M2 only has Thunderbolt 3 and has a limited number of supported Thunderbolt docks, none of which support external multi-monitor setups. Apple says the MacBook Air supports “one external display with up to 6K resolution at 60Hz.”
Another feature that I would like to compare for both systems is how quickly each device is able to unlock. In my testing, Windows Hello was able to unlock the Surface Laptop 5 faster than the TouchID on the MacBook Air M2. I found this to be the case consistently and reliably, even in dim and unlit environments. Opening up both systems takes less time for Windows Hello to recognize me and unlock the device than for me to put on my finger on TouchID.
For organizations that are still considering the MacBook Air M2, keep in mind that storage is soldered on and, therefore, not upgradeable. The Surface Laptop 5 has upgradeable storage post-purchase, and the ability to remove it is for security purposes when being discarded.
Gaming
While gaming is not as important as productivity for me, it is a very considerable category. Like content creators, I doubt the target audience will be looking for ultra-portable notebooks for AAA gaming. However, both these laptops have the performance to run AAA games if the desire is there, but only one is capable of playing most, if not all, AAA games. Before I jump into compatibility, let’s run through some gaming benchmarks. Keep in mind the MacBook Air M2 is equipped with the upgraded 10-core GPU, not the base 8-core GPU.
The first game is Sid Meier’s Civilization 6 (Civ6). I have chosen Civ 6 because it has an Artificial intelligence benchmark that measures the time it takes for the NPCs of the game to take calculated turns. Although it may not be as graphically intensive of a game compared to other AAA games, it is very fitting for this type of laptop. I do not expect either laptop to run something like Cyberpunk 2022 very well for a long period.
I decided to opt-out of including the Civ 6 graphics benchmark since it is not a graphically intensive game and so that I do not overwhelm the reader with redundant benchmarks.
The Civ 6 AI benchmark is measured in milliseconds
The benchmarks were close for both systems, but the Surface Laptop 5 outperformed the MacBook Air on average by two milliseconds. Interestingly, I found that the Surface Laptop 4 actually performs about the same as the Surface Laptop 5, which is why I included it in the last comparison.
While this difference is not enough for any gamer to notice, it still follows what I said in my Surface Laptop 4 and MacBook Air M2 comparison.
“The M2 has a 14-core NPU for specializing in AI processing. I am not certain whether Civ 6’s AI uses the 14- core NPU, but if it does, it is quite underwhelming, and if it doesn’t, then it shows the lack of support for M2. If the lack of AAA games for Apple silicon did not tell you how Apple doesn’t care about gaming, this should.”
The next game I chose was Counter Strike: Global Offensive (CS:GO). Like Civ 6, CS:GO runs very well on the MacBook Air M2 through Rosetta 2, and I believe it shows the superior graphics of the 10-core M2 chip over the Intel Iris Xe. CS:GO is played competitively, so having the right frames per second (fps) is an important aspect of the game. Anything under 60 fps is not a passing score but remember that these systems should not be considered gaming replacements.
The CS:GO community benchmark courtesy of uLLitecaL
The MacBook Air M2 performs well over 60 fps and doubles the fps of the Surface Laptop 5 at 49 fps on average. I believe this leaves a lot to be desired from the Surface Laptop 5 and shows the potential of gaming on the MacBook.
These next two benchmarks show what I believe to be the state of gaming for the MacBook and how the Microsoft and the Surface team have little to worry about in terms of gaming, no matter how good Apple’s silicon gets.
I tested the Surface Laptop 5 and MacBook Air M2 in 3D Mark’s Wild Life Extreme Unlimited cross-platform benchmark. There is not a 3D Mark macOS application, and so the MacBook Air is only limited to the 3D Mark benchmarks that are available through iPadOS and iOS, the 3D Mark Wild Life Extreme Unlimited benchmark. It has a graphics benchmark and a stress test to measure how well each system maintains its performance over time. It is important to have a stable gaming device considering video game sessions last over five hours on average.
The 3D Mark Stress Test.
The MacBook Air M2 had trouble maintaining its performance over time. I believe this is due to the thermal throttling issues that the MacBook Air M2 has faced since its launch. While the Surface Laptop 5 did not pass the 97% threshold for 3D Mark to consider it a passing stress test, it was much closer than the MacBook Air M2.
The 3D Mark graphics benchmark
The MacBook Air M2 doubles the score of the Surface Laptop 5 in the 3D mark Wild Life Extreme Unlimited benchmark. While the 3D Mark Wild Life Extreme Unlimited test looks amazing for the MacBook Air M2, I believe it is only half of the answer. While the MacBook Air M2 is able to achieve such a higher score in the confines of the 3D Mark benchmark, these results are not as practical for the MacBook Air M2. The 3D Mark benchmark gives an anchor.
The 3D Mark benchmark has a calculation of estimated gaming performance by game. It gives an estimated gaming performance for Apex Legends, Battlefield V, GTA V, and Red Dead Redemption 2. Out of these four games, which are very popular games and franchises, only three are playable through Crossover and Parallels, and only one is considered “perfect,” according to AppleGameWiki.com. 3D Mark estimates that the Surface Laptop 5 is capable of reaching 45+ fps on 1080p. The MacBook Air M2 then should be capable of reaching well over 45+ fps and double that if the scores are linear.
However, like most of the games on the Apple Game Wiki website, it is played using either CrossOver, which creates Wine bottles, or Parallels, which creates a Windows virtual machine. While these methods allow the user to play the game, it comes at a cost. Firstly, both Parallels ($99) and CrossOver ($74) cost money. Secondly, these methods come at a loss in performance. I benchmarked both systems using the same Battlefield sequence that Notebookcheck.net uses here. For the MacBook Air, I used Parallels which allowed me to also use FRAPS to record the fps average.
Battlefield V was benchmarked using the same benchmarking sequence as Notebookcheck
Battlefield V struggled on the MacBook Air M2 to stay consistently above 30 fps while consistently having lag spikes and rarely reaching above 50 fps. The Surface Laptop 5, which runs the game natively on the Direct X11 and Direct X12 API, reached 45 fps, meeting the estimates of 3D Mark.
The Surface Laptop 5 on the left and the MacBook Air on the right showing the explosion scene from … [+] the story Tirailleur in Battlefield V.
The Surface Laptop 5 on the left and the MacBook Air on the right showing the explosion scene from the story Tirailleur in Battlefield V. Source Jacob Freyman
On top of this, there were countless graphics inaccuracies. In the example above a massive explosion occurred, and the MacBook Air M2 could not render the lighting correctly, making the scene unwatchable. Yes, Battlefield V is only one example and it is because of the hoops we have to jump through in Parallel. However it sets the expectation for franchise games and the most popular games from publishers like EA, Microsoft, Activision Blizzard, and Epic Games.
Out of the consistently updated list of M1 and M2 compatible games master list on Applegamingwiki.com, only 52% of the 1269 games listed are playable either natively or using Rosetta. There is also little incentive for game developers to port over there games, especially older games, to Apple’s new silicon.
Apple has deprecated OpenCL in favor of its Metal API. This means that developers would have to port there games to Metal, adding time and money to the development of the game. Not to mention, game developers may be hesitant to support macOS when Apple is actively threatening Epic games, the creators of Unreal Engine.
Wrapping up
I did not expect the Surface Laptop 5 to outperform the MacBook Air M2 in any of those benchmarks, but it did hold its ground and created less distance with respect to raw performance. I do believe the MacBook Air M2 offers unrivaled battery efficiency and an unbeatable PPW. However, the Surface Laptop 5 has shown itself to offer arguably a better experience for content creation, productivity, and gaming with its small form factor audience.
The Surface Laptop 5’s touch display and pen support allow it to be versatile in more scenarios and environments. The touch display offers a better experience for content creators on the go with the Surface Slim Pen and allows users to sign documents without switching devices. It also provides a better Android app experience with its touch display than Apple with its iOS and iPadOS apps.
The Surface Laptop 5 also has a better productivity experience with preloading Office 365 apps and using Window Snaps on Windows 11 22H2. I believe Windows has a better productivity and multitasking experience than macOS Ventura with Stage Manager.
Once more, the Surface Laptop 5 is shown to be better than the MacBook Air M2 in AAA gaming. Although the Surface Laptop 5 cannot handle every game thrown at it, it can run demanding games at reasonable graphics settings with support for most, if not all, AAA titles. Net-net, the Surface Laptop 5 has more to offer than the MacBook Air M2, even though the M2 chip outperforms Intel’s processors in most benchmarks.

Note: Moor Insights & Strategy co-op Jacob Freyman contributed to this article
Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler.
Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movand

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The main features of HiringThing include job posting, résumé import, candidate matching and more. We were able to test out nearly all of them for their ease of use.

Syndicated Job Posting

It’s easy to find the “Create a New Job” button right when you log in to HiringThing. Upon clicking that, it takes you to a form where you populate all the necessary information for your job listing.

Right when you log in, the “Create a New Job” button is easy to find.

HiringThing’s new job post screen

When you’re done with the job post, you can save it as a draft to come back to later or simply hit “Publish,” and it instantly posts to free job boards, such as FlexJobs and LinkedIn Limited. The system then directs you to more job boards you can purchase access to. These job boards include but are not limited to:

• CareerBuilder
• DiversityJobs
• Indeed
• LinkedIn
• Monster
• ZipRecruiter

Unless you’re already a subscriber to these premium job boards and can simply link your account to HiringThing, the cost of adding each one through HiringThing can add up quickly. For this reason, HiringThing may not be the most cost-effective option for specialized, high-demand and hard-to-fill roles.

Résumé Import

You can import an applicant’s data through drag and drop or via email with HiringThing’s Resume Import Tool. Dragging and dropping or uploading a file from your computer’s hard drive into the system automatically converts it into an applicant file.

You can also import applicant documents via email by sending the file to the job posting’s specific email address found in the system. However, you have to go into the job itself to find the email address specific to the job posting and copy and paste it into your email, which can be cumbersome.

HiringThing’s Resume Import feature via email

The system needs about one hour to reflect the uploaded files in the system, which is a long time, making it easy to forget to check if the upload worked. We were able to add a file manually using the first method, but we did not see a new applicant file created under the applicant section of the dashboard, even after one hour had passed.

Candidate Matching

HiringThing has keyword tagging and customized pre-screening questions that help you more quickly identify the most qualified candidates for any given position.

Keyword Tagging

When creating a position, you can add a series of keywords separated by commas. HiringThing will then surface applications that best match those keywords, and you’ll see an alert displayed when there’s a match.

Form Builder

For applicants who apply directly from your career site, you can set up a customized form that poses pre-screening questions related to anything from job experience to specific certifications. This can be helpful to screen out candidates that don’t meet minimum criteria.

However, keep in mind that applicants applying from job boards won’t see this form, so you should choose the option that doesn’t allow applicants to apply from the job boards. When selecting that option, applicants will be redirected to your career site where they can proceed with their application.

You can get to the Form Builder feature either through a specific job listing’s settings or by navigating to “Account Details.”

When testing out the Form Builder, we had the option of creating a template to save time in the future. When creating the template, you can choose what types of questions to ask:

• Text-based
• Essay questions
• Multiple choice
• List of checkbox attributes
• Yes/No
• Date for applicant’s earliest start date
• Employment history
• Education history

For some question types, such as Yes/No questions, you can set a rule that automatically tags or archives an applicant based on their response. For instance, if a minimum criterion for a new Sales Associate is at least two to three years of experience, you can filter out applicants that select “no” to the question about whether they have that experience.

The employment and education history questions require applicants to type in that information manually, which can make for a frustrating job candidate experience, as the résumé usually contains this information already.

However, HiringThing gives you full control over the kind of screening questions you want applicants to fill out, so you don’t have to necessarily pose questions that require manual data entry.

HiringThing’s Form Builder

Scorecards for Candidate Evaluation

HiringThing enables you to create customized scorecards before you start evaluating candidates in order to mitigate bias in the review process. You can enter customizable text fields, called “Titles,” and those fields will appear in an applicant’s review section.

The “Title” field is misleading because it’s not the job title. Rather, it denotes the attributes by which you want to evaluate candidates. For example, if hiring for a Sales Manager position, you may want to add titles such as “integrity” or “leadership.”

We found two ways to create a scorecard. For the first method, you have to navigate to the main menu > Account Details > Feature Management, and scroll down to the “Scorecards” section. It’s important to note that once you enter titles this way, they automatically apply to all subsequent jobs that you post after creating the scorecard and cannot be applied retroactively to existing job openings.

This can be frustrating if your general criteria change over time because changes can’t be applied to current openings, and you’d have to enter them into those individual jobs manually per the second method below. It’s therefore important to settle on a general set of criteria that you’ll rarely, if ever, need to change.

The second way to create a job scorecard is to edit a specific job and expand the “Advanced Options” section, and the titles will appear in each applicant’s “Review section.” We found this method more intuitive. Plus, we like that you can add specific criteria for specific jobs.

HiringThing’s Scorecards display different pre-set attributes, and you provide a star rating and optional notes for each candidate.

Candidate Relationship Management

HiringThing facilitates candidate relationship management via email and SMS.

Managing candidate statuses and communication were some of the easiest tasks we tested out in HiringThing. You can individually change an applicant’s status or do so in bulk to save time. You can add statuses including “offer extended” and “offer accepted/rejected” in the “Workflow” section of Account Details.

It was very easy to select a pre-made email template for requesting an interview, rejecting a candidate or other typical recruiter communications. Paying customers have access to HiringThing’s SMS option as an additional communication method.

Interview Tools

HiringThing enables collaborative interview scheduling by syncing with your Outlook, Exchange, Microsoft 365, Google or iCloud calendar. You can select a specific date or time or, even better, allow the candidate to select from a range of dates and times that you deliver them.

Using a Google account will automatically use Google Meets as a videoconference tool, unless you link your account to another videoconference tool such as Zoom. Otherwise, 8×8 is the default videoconferencing solution for HiringThing.

Workflows and Automations

HiringThing helps you expedite your hiring process by automating job requisitions, candidate screening, interviewing and any other workflows you set up.

HiringThing enables you to set up a workflow for opening, approving and posting job requisitions. Rules for screening questions noted above also automate the candidate selection process by filtering out candidates who don’t meet the minimum requirements and automatically sending them a “Thanks but no thanks” email. That way, you won’t spend time sifting through résumés from unqualified candidates or sending rejection emails.

HiringThing’s new automated interviewing workflow allows you to send an automated interview invitation in one of two ways: as soon as anyone submits an application to the job or based on a change in application status.

You might want to use the former if you’re hiring for a niche position that draws few candidates, all of whom you want to interview. Otherwise, you’d more likely utilize the second workflow option that invites candidates to an interview after you change their status. However, with either option, make sure all who are involved in the process keep their calendar availability up to date.

Unfortunately, we weren’t able to try out the workflows setup in the test environment, as this feature is only available to paying customers.

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Thomas Dullien discusses how language design choices impact performance, how Google’s monorepo culture and Amazon’s two-pizza-team culture impact code efficiency, and why statistical variance is an enemy.
This article describes the journey of the migration towards a Federated GraphQL architecture. Specifically, it shows the GraphQL platform Netflix has built consisting of the Domain Graph Services framework for implementing GraphQL services in Java using Spring Boot and graphql-java, and tools for schema development. It also describes how the ecosystem has evolved at various stages of adoption.
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InfoQ Homepage News Microsoft Announces Preview of OpenAPI Specification V3 in Azure API Management
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Jan 29, 2019 2 min read
by
Eldert Grootenboer
Recently Microsoft has announced support for the OpenAPI specification v3 in Azure API Management, which is their service that enables the set up, publishing, monitoring and maintainence of APIs. Support of the OpenAPI specification has been implemented through the OpenAPI.NET SDK and allows the abstraction of the definition of APIs from their implementation.
The OpenAPI specification, previously known as Swagger, provides the means to describe RESTful web services in a language independent way. As OpenAPI is widely adopted, a diverse ecosystem is available with tools for designing, documenting, building, testing and implementing governance. The specification gets overseen by the OpenAPI Initiative, owned by the Linux Foundation, and has a wide variety of organizations driving its development, including companies such as SmartBear, Microsoft, and WSO2. Anyone can follow or even contribute to the development of the specification on the GitHub repository of the OpenAPI Initiative.
According to Tom Kerkhove, Microsoft Azure MVP and Azure Architect, the specification has an important role when exposing APIs to their consumers.
Providing clean and well-documented APIs is a must. This allows your consumers to know what capabilities you provide, what they are for and what to expect. This is where the OpenAPI specification, aka Swagger, comes in and defines how APIs should be defined across the industry, regardless of what technology is underneath it.
Version 3 of the specification has brought several changes, and as such these are now also available for Azure API Management. For instance, this new version introduced a whole new architecture with components such as headers, links, and callbacks, taking a more modular approach in the definition, as described by Guy Levin, CTO at RestCase.
Version 3.0 of the API specification format has taken a much more modular, and reusable approach to defining the surface area of an API, enabling more power and versatility when it comes to describing the request and response models, as well as providing details on the common components that make up API usage like the underlying data schema and security definitions.
Another introduced option is to include callbacks to an operation, meaning it is now possible to describe webhooks for these. Finally, linking allows defining relationships between different paths of the APIs, providing the capability to expand on its attributes.

Image source: https://blog.restcase.com/6-most-significant-changes-in-oas-3-0/
Following the announcement, it is now possible to import OpenAPI v3 definitions in Azure API Management, albeit with some restrictions. Currently, this is possible through the portal or via the REST API. Subsequently, capabilities for exporting the OpenAPI descriptions are also available, either in the developer portal or using another call to the REST API.

Source: https://azure.microsoft.com/en-us/blog/announcing-the-preview-of-openapi-specification-v3-support-in-azure-api-management/
Eventually, before these capabilities will move into general availability, and it will also become possible to use the PowerShell SDK for doing both import and export of the definitions.

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