Cloud Hosting

What does the metaverse the set of interconnected 3D environments that is poised to revolutionize the way people interact on the internet mean for cloud computing?

The answer is anyone's guess, given that the metaverse remains a somewhat fuzzy concept and that we're still in the very early stages of actually building a metaverse.

Related: DevOps Teams to Play Big Role in Tackling Metaverse Challenges

Still, the ideas behind the metaverse are sufficiently well-formed at this point to facilitate informed guesses about how the rise of the metaverse may change the way we use and manage the cloud.

Toward that end, here's a look at five main ways that the metaverse whatever form it ends up taking is likely to affect the cloud.

Related: 10 Ways IT Can Get Ready for the Metaverse

First and foremost, the rise of the metaverse is likely to increase demand for cloud computing services even further.

The reason why is simple: Hosting 3D environments requires a lot of compute and storage resources, and it's a safe bet that few businesses that want to run a metaverse environment will be purchasing their own hardware to do so. Instead, they'll turn to the cloud to host the metaverse, as they already do for a majority of other workloads.

So, add the metaverse to the list of reasons why cloud computing providers are likely to become even richer in coming years.

That said, the profits that the metaverse drives for cloud computing platforms may not flow primarily to the major generic public cloud providers namely Amazon, Google, and Microsoft.

Instead, we may see alternative clouds emerge that specialize in metaverse hosting. That's especially true given that the infrastructure necessary to run metaverse environments may require specialized hardware such as GPUs that are not currently a major focus of large public cloud providers. AWS, Microsoft Azure, and Google Cloud Platform (GCP) offer some GPU-enabled VM instances, but they don't specialize in that market, which creates an opportunity for smaller cloud providers to fill the gap.

To the extent that the large public clouds do invest in metaverse hosting, I suspect they will do it by launching managed services that will amount to metaverse-as-a-service which means fully hosted and managed offerings that enable customers to deploy their own, custom metaverse environments with little effort.

It's possible the cloud providers will build these metaverse services entirely from scratch just as AWS built its ECS container orchestration service by scratch, for example. Or, they may leverage open source metaverse platforms, like Vircadia, as the foundation for metaverse-as-a-service offerings in a fashion very similar to what they have done with Kubernetes.

One of the major technical challenges that may arise as the metaverse expands is ensuring that bandwidth limitations or internet connectivity disruptions don't disrupt users' ability to experience the metaverse seamlessly.

Another challenge may be securing personal data that users store or create within the metaverse. Although it remains to be seen how regulators will define or treat personal information in the metaverse, there is already good reason to believe that it will need to be protected in the same way that personally identifiable information is protected in a conventional cloud environment.

Both of these challenges the need for better performance and the need for high data security are likely to result in demand for hybrid cloud architectures as a means of hosting metaverse environments. Hybrid cloud can boost performance and availability by placing hosting resources closer to end users. It can also improve data security by allowing data to stay on private servers instead of exposing it to the public cloud.

Expect at least some metaverse entities, then, to be hosted in hybrid cloud environments.

Getty Images

Another way to improve performance and availability for the metaverse is to push metaverse hosting and analytics to the "edge." In other words, users' own devices instead of cloud data centers and servers will be responsible for running at least some of the software that powers the metaverse. That approach will allow organizations to sidestep performance problems associated with relying on the internet as the only means of delivering metaverse connectivity.

Thus, expect edge computing however you define it to become even more important thanks to the metaverse. By extension, we'll likely see more investing in edge computing management platforms, like Kubernetes, that can help businesses keep track of the distributed edge infrastructure that hosts their metaverse environments.

Again, it's too early to say definitively how the metaverse will reshape cloud computing. But if I had to make early bets, they'd center on increased use of the cloud overall, and of hybrid and edge cloud architectures in particular. I also think we'll see cloud providers start building their own metaverse-as-a-service offerings, and there may be an opening for alternative cloud providers to serve the metaverse market in a way that the large public clouds won't.

Originally posted here:
Why the Metaverse Will Be a Boon for Cloud Computing - ITPro Today

In our latest round of VPN testing, ExpressVPN came out as the overall winner - once again. The provider beat its competitors on pretty much all the fronts, desereving its place once again at the top of our list.

If you're not yet a subscriber, but like the idea of getting the benefit of all the privacy tools and unblocking smarts ExpressVPN has to offer, then you should ensure that you take advantage of its current offer that bundles in not one, but two freebies.

TechRadar readers that want to sign up to its best value one-year plan, will enjoy three extra months of protection for free together with a whole year of cloud backup from Backblaze without any added cost.

Ready to protect your digital privacy? Read on to discover how to benefit from this tempting deal as well as what makes ExpressVPN our favorite provider right now.

There are several reasons why ExpressVPN keeps scoring a five-star rating every time we test it out.

One of those is that the service keeps improving. As our last check shows, the company's router app has seen a notable upgrade. In fact, you can now sort your devices into groups, while connecting each of those to a different location.

The provider has also fully open-sourced its speedy Lightway protocol, making it available on all platforms. This technology is a key contributor to the service's excellent and stable performance. As our cybersecurity specialist Mike Williams wrote: "ExpressVPN's Lightway protocol more than doubled OpenVPN performance to 570-580Mbps in the UK.

If you are looking for a good streaming VPN, Express won't let you down as it unlocks more than 25 platforms - these include Netflix, BBC iPlayer and Amazon Prime. Plus, during our tests, its live support has always been helpful on the rare occasions there have been issues.

When we looked at its privacy features, we couldn't have been more happy. As Mike Williams highlighted: "The company doesn't just tell you how great it is it also has an impressively lengthy list of features to help justify every word."

Among those, its DNS support is worth a mention. In fact, alongside a DNS leak protection, Express also runs its own private, zero-knowledge, 256-bit encrypted DNS on each of its own servers.

Check out our full ExpressVPN review to discover all its features in more detail.

Today's best ExpressVPN deals

Continue reading here:
ExpressVPN deal: Get the world's best VPN with free cloud backup from Backblaze - TechRadar

Sharing is caring!

Also, if the past events like the unhurriedly subsiding pandemic are any indicator, its not enough to have an IT setup. You also need to adapt rapidly or die just as fast. Not forgetting security, redundancy, backup, and the other nitty-gritty that your tech team emphasises.

Do you have your vital corners covered, or is your IT infrastructure putting your business at risk? Heres what you need to know.

The corona pandemic was a wake-up call in many ways. It limited movement and forced people to work remotely, which caused other challenges, especially for businesses operating on-premise IT infrastructure. They include:

Colo, too, makes for a great alternative to on-premise IT infrastructure. You get all the advantages of owning private servers, including privacy, customizability, and compliance, while enjoying better security, tech support, cost-saving, and scalability.

For instance, a colocation hosting provider such as Safehosts would offer you state-of-the-art premises with excellent security and the optimal environment for your servers. You would also get a redundant network and power infrastructure that guarantees uptime and scalability.

As for accessibility, your IT team may operate your servers physically or remotely. The best colocation hosts will usually have a team of experts 24/7/365 on-site to help you keep things running even if you cant get to your servers in time.

The more you take your staff and data online, the more hackers can get into your system. Businesses often get crippled after even the slightest data breaches. For example, Talk Talk recently lost half its profits following a cyber-attack. You cant afford to compromise!

Hackers will get to your data if they are determined, no matter how good your security is. You should always have a great backup and disaster recovery plan.

Custom-building everything might seem cool and unique, but standard protocols and APIs save you from many future headaches. They allow you to run updates as required and without any limitations. Moreover, open APIs are less subject to back doors and security risks.

This option can significantly help you keep your IT infrastructure up to date. It also helps you avoid relying too much on a small internal IT department that may have limited skills and resources. Consequently, your IT team gets more freedom to deal with strategic objectives in the house.

In any case, popular cloud server hosts such as OCI have comprehensive teams of some of the most qualified experts in IT. Using their services lets you tap into various skills you would otherwise be unable to stock within your company.

The only caveat with cloud hosting is that it may raise compliance concerns, especially when dealing with sensitive data. It may also be difficult to scale up beyond a certain point when your business requires a more complicated data exchange and storage model.

You may also have a hybrid setup, such that you store your primary servers with a colocation provider and still use cloud hosting, either private or public.

This arrangement leaves room for future migration to the cloud. At the same time, you retain control over your main servers and most sensitive data operations.

Continued here:
Is Your Business at Risk With Your Current IT Infrastructure? - Mighty Gadget

Frustrated by the limitations of Ethernet, Google has taken the best ideas from InfiniBand and Crays Aries interconnect and created a new distributed switching architecture called Aquila and a new GNet protocol stack that delivers the kind of consistent and low latency that the search engine giant has been seeking for decades.

This is one of those big moments when Google does something thatmakes everyone in the IT industry stop and think.

The Google File System in 2003. The MapReduce analytics platform in 2004. The BigTable NoSQL database in 2006. Warehouse-scale computing as a concept in 2009. The Spanner distributed database in 2012. The Borg cluster controller in 2015 and again with the Omega scheduler add-on in 2016. The Jupiter custom datacenter switches in 2015. The Espresso edge routing software stack in 2017. The Andromeda virtual network stack in 2018. Google has never done a paper on its Colossus or GFS2 file system, the successor to GFS and the underpinning of Spanner, but it did mention it in the Spanner paper above and it did give a video presentation during the coronavirus pandemic last year about Colossus to help differentiate Google Cloud from its peers.

Two asides: Look at where the problems are. Google is moving out from data processing and the systems software that underpins it and through scheduling and into the network, both in the datacenter and at the edge, as it unveils its handiwork and technical prowess to the world.

The other interesting thing about Google now is that it is not revealing what it did years ago, as in all of those earlier papers, but what it is doing now to prepare for the future. The competition for talent in the upper echelon of computing is so intense that Google needs to do this to attract brainiacs who might otherwise go to a startup or one of its many rivals.

In any event, it has been a while since the search engine and advertising behemoth dropped a big paper on us all, but Google has done it again with a paper describing Aquila, a low-latency datacenter fabric that it has built with custom switch and interface logic and a custom protocol called GNet that provides low latency and more predictable and substantially lower tail latencies than the Ethernet-based, datacenter-wide Clos networks the company has deployed for a long time now.

With Aquila, Google seems to have done what Intel might have been attempting to do with Omni-Path, if you squint your eyes a bit as you read the paper, which was published during the recent Network Systems Design and Implementation (NSDI) conference held by the USENIX Association. And specifically, it borrows some themes from the Aries proprietary interconnect created by supercomputer maker Cray and announced in the Cascade CX30 machines back in November 2013.

You will remember, of course, that Intel bought the Aries interconnect from Cray back in April 2012, and had plans to merge some of its technologies with its Omni-Path InfiniBand variant, which it got when it acquired that business from QLogic in January 2012. Aries had adaptive routing and a modicum of congestion control (which sometimes got flummoxed) as well as a dragonfly all-to-all topology that is distinct from the topologies of Clos networks used by the hyperscalers and cloud builders and the Hyper-X networks sometimes used by HPC centers instead of dragonfly or fat tree topologies. It is harder to add capacity to dragonfly networks without having to rewire the whole cluster, but if you are podding up machines, then it is perfectly fine. The Clos all-to-all network allows for machines to be added fairly easy, but the number of hops between machines and therefore the latency is not as consistent as with a dragonfly network.

Steve Scott, the former chief technology officer at Cray who led the design of its SeaStar and Gemini and aforementioned Aries interconnects, which were at the heart of the Cray XT3, XT4, and XC machines, joined Google back in 2013 and stayed through 2014 before rejoining Cray to lead its supercomputing resurgence with the Rosetta Slingshot interconnect. Scott told us that being a part of Googles Platform Group made him really appreciate the finer points of tail latency in networks, but it looks like Scott impressed upon them the importance of proprietary protocols tuned for specific work, high radix switches over absolute peak bandwidth, the necessity of congestion control and adaptive routing that is less brittle than the stuff used by the Internet giants, and the dragonfly topology. (Scott joined Microsoft Azure as a Technical Fellow in June 2020, and it is reasonable to expect that the cloud giant is up to something relating to networks with Scotts help.)

In short, Intel, which spent $265 million buying those networking assets from QLogic and Cray and heaven only knows how much more developing and marketing Omni-Path before selling it off to Cornelis Networks, is probably now wishing it had invented something like Aquila.

There are a lot of layers to this Aquila datacenter fabric, which is in a prototype phase right now, and it is not at all clear how this will interface and interleave with the Mount Evans DPU that Intel designed in conjunction with Google and that the hyperscaler is presumably already deploying in its server fleet. It could turn out that the converged switch/network device that is at the heart of the Aquila fabric and the Mount Evans DPU have a common destination on their respective roadmaps, or they drive on parallel roads until one gets a flat tire.

Aquila, which is the Latin word for eagle, explicitly does not run on top of or in spite of the Ethernet, IP, or TCP and UDP protocols that underpin the Internet. (For a great image of the differences between these nested protocols, here is a great explanation: Imagine one of those pneumatic tube message systems. Ethernet is the tube used to send the message, IP is an envelope in the tube, and TCP/UDP is a letter in the envelope.

Forget all that. Google threw it all out and created what it calls a cell-based Layer 2 switching protocol and related data format that is not packets. A cell in fact, is smaller than a packet, and this is one of the reasons why Google can get better deterministic performance and lower latency for links between server nodes through the Aquila fabric. The cell format is optimized for the small units of data commonly used in RDMA networks, and with the converged network functionality of a top of rack switch ASIC and a network interface card, across the 1,152 node scale of the Aquila interconnect prototype, it can do an RMA read in an average of 4 microseconds.

This converged switch/NIC beast, the cell data format, the GNet protocol for processing it very efficiently with its own variant of RDMA called 1RMA, the out-of-band software-defined networking fabric, and the dragonfly topology create a custom, high speed interconnect that bears a passing resemblance to what would happen if Aries and InfiniBand had a lovechild in a hyperscale datacenter and that child could speak and hear Ethernet at its edges where necessary.

Lets start with the Aquila hardware and then work our way up the stack. First off, Google did not want to spend a lot of money on this.

To sustain the hardware development effort with a modest sized team, we chose to build a single chip with both NIC and switch functionality in the same silicon, the 25 Google researchers who worked on Aquila explain in the paper. Our fundamental insight and starting point was that a medium-radix switch could be incorporated into existing NIC silicon at modest additional cost and that a number of these resulting NIC/switch combinations called ToR-in-NIC (TiN) chips could be wired together via a copper backplane in a pod, an enclosure the size of a traditional Top of Rack (ToR) switch. Servers could then connect to the pod via PCIe for their NIC functionality. The TiN switch would provide connectivity to other servers in the same Clique via an optimized Layer 2 protocol, GNet, and to other servers in other Cliques via standard Ethernet.

There is a lot of stuff on this torrinic chip. Amin Vahdat, who is the engineering fellow and vice president who runs the systems and services infrastructure team at Google and who led the network infrastructure team for a long time before that, told us this time last year that the SoC is the new motherboard and the focus of innovation, and it comes as no surprise to us that each Aquila chip is in fact a complex with two of these TiNs in the same package (but not necessarily on the same doe, mind you). Vahdat is one of the authors of the Aquila paper, and no doubt drove the development effort.

As you can see, there are a pair of PCI-Express 3.0 x16 slots coming out of the device, which allows for one fat 256 Gb/sec pipe into a single server or two 128 Gb/sec half-fat pipes for two servers. Sitting on the other side of this PCI-Express switch is a pair of network interface circuits one that speaks 100 Gb/sec IP and can pass through the chip to speak Ethernet and another that speaks the proprietary 1RMA protocol and that hooks into the GNet cell switch.

That cell switch has 32 ports running at 28 Gb/sec not that many ports as switches go and not that fast as ports go, as Google pointed out above. With encoding overhead taken off, these GNet cell switch lanes run at 25 Gb/sec, which is the same speed as IBMs Bluelink OpenCAPI ports on the Power9 processor and as the lanes in the NVLink 3.0 pipes in the Ampere A100 GPU and related NVSwitch switches. There are 24 of these 25 Gb/sec lanes that are used to link all of the server nodes in pod over copper links, and there are eight links that can be used to interconnect up to 48 pods into a single GNet fabric, called a clique, using optical links. The Dragonfly topology used at Cray and now at Google is designed explicitly to limit the number of optical transceivers and cables need to do long-range linking of pods of servers. Google has apparently also designed its own GNet optical transceiver for these ports.

The Aquila TiN has input and output packet processing engines that can interface with the IP NIC and the Ethernet MAC if the data from the cell switch needs to leave the Aquila fabric and reach out into the Ethernet networks at Google.

Google says that the single chip design of the Aquila fabric was meant to reduce chip development costs and also to streamline inventory management. Anyone who has been waiting for a switch or NIC delivery during the coronavirus pandemic knows exactly what Google is talking about. The dearth of NICs is slowing down server sales for sure. It was so bad a few months ago that some HPC shops we heard about through resellers were turning to 100 Gb/sec Omni-Path gear from Intel because it was at least in stock.

The main point of this converged network architecture is that Google is nesting a very fast dragonfly network inside of its datacenter-scale Clos network, which is based on a leaf/spine topology that is not an all-to-all network but does allow for everything to be interlinked in a cost-effective and scalable fashion.

Google says that the optical links, allows for the Aquila pods to be up to 100 meters apart and impose a 30 nanosecond Google said nanosecond per hop latency between the interconnected pods, and that is with forward error correction reducing the noise and creating some latency.

These days, most switches have compute built in, and Google says that most switches have a multicore, 64-bit processor with somewhere between 8 GB and 16 GB of main memory of its own. But by having an external SDN controller and by using the local compute on the Aquila chip package as an endpoint local processor for each TiN pair, the Aquila package can get by with a 32-bit single-core Cortex-M7 processor with 2 MB of dedicated SRAM to handle the local processing needs of the SDN stack. The external servers running the GNet stack were not divulged, but this is a common design for Google.

The SDN software is written in C and C++ and is comprised of around 100,000 lines of code; the Aquila chip runs the FreeRTOS real-time operating system and the lwIP library. The software exposes all of the low-level APIs up to the SDN controller, which can reach in and directly manipulate the registers and other elements of the device. Google adds that having the firmware for Aquila distributed and most of it on the controller, and not the device was absolutely intentional, and that the idea is that the TiN device can bring up the GNet and Ethernet links and attempt to link to the DHCP server on the network and await further configuration orders from the central Aquila SDN controller.

One interesting bit about the Aquila network is that because it is a dragonfly topology, you have to configure all of the nodes in the network from the get-go or you have to recable every time you add machines to get the full bandwidth of the network. (This is the downside of all-to-all networks.) So Google does that and then adds servers as you need them. Here is what the schematic of the servers and network look like all podded up:

The Aquila setup has two 24-server pods in a rack and 24 racks in a clique. Google is using its standard server enclosures, which have NICs on adapter cards, in this case a PCI adapter card that links to a switch chassis that has a dozen of the T1N ASICs on six adapter cards. The first level of the dragonfly network is implemented on the chassis backplane, and there are 96 optical GNet links coming out of the pod to connect the 48 pods together, all-to-all, with two routes each.

One side effect of having many ASICs implementing the network is that the blast radius for any given ASIC is pretty small. If two servers share a T1N and the T1N package has two ASICs, then the failure of one package only knocks out four servers. If a top of rack switch in a rack of 48 servers burns up, then 48 servers are down. If a whole Aquila switch chassis fails, it is still only 24 machines that get knocked out.

Looking ahead, Google is investigating adding more compute to the TiN device in future Aquila devices, on the order of a Raspberry Pi to each NIC, so that it can run Linux. This would allow Google to add a higher-level P4 programming language abstraction layer to the network, which it most definitely wants to do.

In early tests, the Aquila fabric was able to have tail latencies of under 40 microseconds for a fabric round trip time (RTT in the network lingo), and had a remote memory access of under 10 microseconds across 500 host machines on a key-value store called CliqueMap. This tail latency is 5X smaller compared to an existing IP network, even under high load.

One last thought. The scale of the Aquila network is not all that great, and to scale the compute more will mean scaling up the T1N ASICs with more ports and possibly but not necessarily with higher signaling rates to increase the bandwidth to match PCI-Express 5.0 speeds. (This was a prototype, after all.) We think Google will choose higher radix over higher bandwidth, or at least split the difference.

There is another performance factor to consider, however. When Google was talking about Borg seven years ago, it had 10,000 to 50,000 servers in a pod, which is a lot. But the servers that Google was using had maybe a handful to a dozen cores per socket and probably two sockets per machine. Aim high and call it an average of 20 cores. But today, we have dozens of cores per server socket and we are on the verge of several hundred cores per socket, so it may only take a few thousand nodes to run all but the biggest jobs at Google. And even the big jobs can be chunked across Aquila pods and then aggregated over regular Ethernet links. There is a factor of 10X improvement in core count along with about a 2X factor increase in instructions per clock (IPC) for integer work over that time; floating point performance has gone up by even more. Call it a 20X factor of improvement in performance per node. For all we know, the pod sizes at Google dont need to be stretched all that far.

More importantly, (O)1000 clusters, as technical papers abbreviate clusters on the order of thousands of nodes, are big enough to do important HPC and AI workloads, even if they cannot run the largest models. It will be interesting to see what jobs fit into an Aquila fabric and what ones do not, and interestingly, this technology might be perfect for the scale of many startups, enterprises, academic, and government enterprises. So even if Aquila doesnt scale far now, it could be the foundation of a very high performance HPC and AI service on Google cloud where (O)1000 is just right.

See the original post:
With Aquila, Google Abandons Ethernet To Outdo InfiniBand - The Next Platform

Who, Us? Atlassian has published an account of what went wrong at the company to make the data of 400 customers vanish in a puff of cloudy vapor. And goodness, it makes for knuckle-chewing reading.

The restoration of customer data is still ongoing.

Atlassian CTO Sri Viswanath wrote that approximately 45 percent of those afflicted had had service restored but repeated the fortnight estimate it gave earlier this week for undoing the damage to the rest of the affected customers. As of the time of writing, the figure of customers with restored data had risen to 49 per cent.

As for what actually happened well, strap in. And no, you aren't reading another episode in our Who, Me? series of columns where readers confess to massive IT errors.

"One of our standalone apps for Jira Service Management and Jira Software, called 'Insight Asset Management,' was fully integrated into our products as native functionality," explained Viswanath, "Because of this, we needed to deactivate the standalone legacy app on customer sites that had it installed."

Two bad things then happened. First, rather than providing the IDs of the app marked for deletion, the team making the deactivation request provided the IDs of the entire cloud site where the apps were to be deactivated.

The team doing the deactivation then took that incorrect list of IDs and ran the script that did the 'mark for deletion magic.' Except that script had another mode, one that would permanently delete data for compliance reasons.

You can probably see where this is going. "The script was executed with the wrong execution mode and the wrong list of IDs," said Viswanath, with commendable honesty. "The result was that sites for approximately 400 customers were improperly deleted."

Yikes.

The good news is that there are backups, and Atlassian retains them for 30 days. The bad news is that while the company can restore all customers into a new environment or roll back individual customers that accidentally delete their own data, there is no automated system to restore "a large subset" of customers into an existing environment, meaning data has to be laboriously pieced together.

The company is moving to a more automated process to speed things up, but currently is restoring customers in batches of up 60 tenants at a time, with four to five days required end-to-end before a site can be handed back to a customer.

"We know that incidents like this can erode trust," understated Viswanath.

Viswanath's missive did not mention compensation for businesses suffering a lengthy outage other than stating he and his team were committed to "doing what we can to make this right for you."

The Register contacted the company to clarify what this includes and will update should Atlassian respond.

With many other companies not being this transparent, especially at the point while the problem is still ongoing, it's commendable to get a proper explanation.

Read more from the original source:
Atlassian comes clean on what data-deleting script behind outage actually did - The Register