It’s the start of the new year, and it’s traditional to make predictions – right? But predicting the future of the datacenter has been hard lately. There have been and continue to be so many changes in flight that possibilities spin off in different directions. Fractured visions through a kaleidoscope. Changes are happening in the businesses behind datacenters, the scale, the tasks and what is possible to accomplish, the value being monetized, and the architectures and technologies to enable all of these.
A few months ago I was asked to describe the datacenter in 2020 for some product planning purposes. Dave Vellante of Wikibon & John Furrier of SiliconANGLE asked me a similar question a few weeks ago. 2020 is out there – almost 7 years. It’s not easy to look into the crystal ball that far and figure out what the world will look like then, especially when we are in the midst of those tremendous changes. For some context I had to think back 7 years – what was the datacenter like then, and how profound have the changes been over the past 7 years?
And 7 years ago, our forefathers…
It was a very different world. Facebook barely existed, and had just barely passed the “university only” membership. Google was using Velcro, Amazon didn’t have its services, cloud was a non-existent term. In fact DAS (direct attach storage) was on the decline because everyone was moving to SAN/NAS. 10GE networking was in the future (1GE was still in growth mode). Linux was not nearly as widely accepted in enterprise – Amazon was in the vanguard of making it usable at scale (with Werner Vogels saying “it’s terrible, but it’s free, as in free beer”). Servers were individual – no “PODs,” and VMware was not standard practice yet. SATA drives were nowhere in datacenters.
An enterprise disk drive topped out at around 200GB in capacity. Nobody used the term petabyte. People, including me, were just starting to think about flash in datacenters, and it was several years later that solutions became available. Big data did not even exist. Not as a term or as a technology, definitely not Hadoop or graph search. In fact, Google’s seminal paper on MapReduce had just been published, and it would become the inspiration for Hadoop – something that would take many years before Yahoo picked it up and helped make it real.
Analytics were statistical and slow, and you had to be very explicitly looking for something. Advertising on the web was a modest business. Cold storage was tape or MAID, not vast pools of cheap disks in the cloud at absurdly low price points. None of the Chinese web-cloud guys existed… In truth, at LSI we had not even started looking at or getting to know the web datacenter guys. We assumed they just bought from OEMs…
No one streamed mainstream media – TV and movies – and there were no tablets to stream them to. YouTube had just been purchased by Google. Blu-ray was just getting started and competing with HD-DVD (which I foolishly bought 7 years ago), and integrated GPS’s in your car were a high-tech growth area. The iPhone or Android had not launched, Danger’s Sidekick was the cool phone, flip phones were mainstream, there was no App store or the billions of sales associated with that, and a mobile web browser was virtually useless.
Dell, IBM, and HP were the only real server companies that mattered, and the whole industry revolved around them, as well as EMC and NetApp for storage. Cisco, Lenovo and Huawei were not server vendors. And Sun was still Sun.
7 years from now
So – 7 years from now? That’s hard to predict, so take this with a grain of salt… There are many ways things could play out, especially when global legal, privacy, energy, hazardous waste recycling, and data retention requirements come into play, not to mention random chaos and invention along the way.
Compute-centric to dataflow-centric
Major applications are changing (have changed) from compute-centric to dataflow architectures. That is big data. The result will probably be a decline in the influence of processor vendors, and the increased focus on storage, network and memory, and optimized rack-level architectures. A handful of hyperscale datacenters are leading the way, and dragging the rest of us along. These types of solutions are already being deployed in big enterprise for specialized use cases, and their adoption will only increase with time. In 7 years, the main deployment model will echo what hyperscale datacenters are doing today: disaggregated racks of compute, memory and storage resources.
The datacenter is now being viewed as a profit growth enabler, rather than a cost center. That implies more compute = more revenue. That changes the investment profile and the expectations for IT. It will not be enough for enterprise IT departments to minimize change and risk because then they would be slowing revenue growth.
Customers and vendors
We are in the early stages of a customer revolt. Whether it’s deserved or not is immaterial, though I believe it’s partially deserved. Large customers have decided (and I’m doing broad brush strokes here) that OEMs are charging them too much and adding “features” that add no value and burn power, that the service contracts are excessively expensive and that there is very poor management interoperability among OEM offerings – on purpose to maintain vendor lockin. The cost structures of public cloud platforms like Amazon are proof there is some merit to the argument. Management tools don’t scale well, and require a lot of admin intervention. ISVs are seen as no better. Sure the platforms and apps are valuable and critical, but they’re really expensive too, and in a few cases, open source solutions actually scale better (though ISVs are catching up quickly).
The result? We’re seeing a push to use whitebox solutions that are interoperable and simple. Open source solutions – both software and hardware – are gaining traction in spite of their problems. Just witness the latest Open Compute Summit and the adoption rate of Hadoop and OpenStack. In fact many large enterprises have a policy that’s pretty much – any new application needs to be written for open source platforms on scale-out infrastructure.
Those 3 OEMs are struggling. Dell, HP and IBM are selling more servers, but at a lower revenue. Or in the case of IBM – selling the business. They are trying to upsell storage systems to offset those lost margins, and they are trying to innovate and vertically integrate to compensate for the changes. In contrast we’re seeing a rapid increase planned from self-built, self-architected hyperscale datacenters, especially in China. To be fair – those pressures on price and supplier revenue are not necessarily good for our industry. As well, there are newer entrants like Huawei and Cisco taking a noticeable chunk of the market, as well as an impending growth of ISV and 3rd party full rack “shrink wrapped” systems. Everybody is joining the party.
Storage, cold storage and storage-class memory
Stepping further out on the limb, I believe (but who really knows) that by 2020 storage as we know is no longer shipping. SMB is hollowed out to the cloud – that is – why would any small business use anything but cloud services? The costs are too compelling. Cloud storage is stratified into 3 levels: storage-class memory, flash/NVM and cool/cold bulk disk storage. Cold storage is going to be a very, very important area. You need to save that data, but spend zero power, and zero $ on storing it. Just look at some of the radical ideas like Facebook’s Blu-ray jukebox to address that, which was masterminded by a guy I really like – Gio Coglitore – and I am very glad is getting some rightful attention. (http://www.wired.com/wiredenterprise/2014/02/facebook-robots/)
I believe that pooled storage class memory is inevitable and will disrupt high-performance flash storage, probably beginning in 2016. My processor architect friends and I have been daydreaming about this since 2005. That disruption’s OK, because flash use will continue to grow, even as disk use grows. There is just too much data. I’ve seen one massive vendor’s data showing average servers are adding something like 0.2 hard disks per year and 0.1 SSDs per year – and that’s for the average server including diskless nodes that are usually the most common in hyperscale datacenters. So growth in spite of disruption and capacity growth.
Data will be pooled, and connected by fabric as distributed objects or key/value pairs, with erasure coding. In fact, Object store (key/value – whatever) may have “obsoleted” block storage. And the need for these larger objects will probably also obsolete file as we’re used to it. Sure disk drives may still be block based, though key/value gives rise to all sorts of interesting opportunities to support variable size structures, obscure small fault domains, and variable encryption/compression without wasting space on disk platters. I even suspect that disk drives as we know them will be morphing into cold store specialty products that physically look entirely different and are made from different materials – for a lot of reasons. 15K drives will be history, and 10K drives may too. In fact 2” drives may not make sense anymore as the laptop drive and 15K drive disappear and performance and density are satisfied by flash.
Enterprise becomes private cloud that is very similar structurally to hyperscale, but is simply in an internal facility. And SAN/NAS products as we know them will be starting on the long end of the tail as legacy support products. Sure new network based storage models are about to emerge, but they’re different and more aligned to key/value.
Rack-scale architectures will have taken over clustered deployments. That means pooled resources. Processing will be pools of single socket SoC servers enabling massive clusters, rather than lots of 2- socket servers. These SoCs might even be mobile device SoCs at some point or at least derived from that – the economics of scale and fast cadence of consumer SoCs will make that interesting, maybe even inevitable. After all, the current Apple A7 in the iphone 5S is a dual core, 64-bit V8 ARM at 1.4GHz and the whole iPhone costs as much as mainstream server processor chips. In a few years, an 8 or 16 core equivalent at 1.5GHz or 2GHz is not hard to imagine, and the cost structure should be excellent.
Rapidly evolving open source applications will have morphed into eventually consistent dataflow tasks. Or they will be emerging in-memory applications working on vast data structures in the pooled storage class memory at the rack or larger scale, which will add tremendous monetary value to businesses. Whatever the evolutionary paths – the challenge for the next 10 years is optimizing dataflow as the amount used continues to exponentially grow. After all – data has value in aggregate, so why would you throw anything away, even as the amount we generate increases?
Clusters will be autonomous. Really autonomous. As in a new term I love: “emergent.” It’s when you can start using big data analytics to monitor the datacenter, and make workload/management and data placement decisions in real time, automatically, and the datacenter begins to take on un-predicted characteristics. Deployment will be autonomous too. Power on a pod of resources, and it just starts working. Google does that already.
Layer 2 datacenter network switches will either be disappearing or will have migrated to a radically different location in the rack hierarchy. There are many ways this can evolve. I’m not sure which one(s) will dominate, but I know it will look different. And it will have different bandwidth. 100G moving to 400G interconnect fabric over fiber.
So there you have it. Guaranteed correct…
Different applications and dataflow, different architectures, different processors, different storage, different fabrics. Probably even a re-alignment of vendors.
Predicting the future of the datacenter has not been easy. There have been, and are so many changes happening. The businesses behind them. The scale, the tasks and what is possible to accomplish, the value being monetized, and the architectures and technologies to enable all of these. But at least we have some idea what’s ahead. And it’s pretty different, and exciting.
Tags: 10 gigabit ethernet, 2020, Amazon, Apple, China, Cisco, cloud storage, cold storage, datacenter, Dell, EMC, Facebook, flash, Google, Hadoop, HP, Huawei, hyperscale datacenter, IBM, iPhone, kaleidoscope, Lenovo, NAS, NetApp, non-volatile memory, NVM, Open Compute, OpenStack, rack scale architecture, SAN, SoC, Sun, VMware, YouTube
No, you are not about to read some Luddite rant about how smart phones are destroying our society. I love smart phones and most of you do too. It’s remarkable how quickly we have gone from arguing over the definition of a smart phone to not being able to live without them. In fact, the rapid adoption of smart phones has led to the problem I am going to talk about: smart phones can overwhelm dumb wireless networks.
Many of the networks that carry the wireless data to and from our smart phones are built with chips that were designed before Apple announced the first iPhone® in June of 2007. It takes a year or two to get a new semiconductor chip designed and built. Then another year or two for network equipment manufacturers to get their products into the market. By the time that new equipment has been deployed into networks around the world, five or six years have passed since chip designers decided what features their networking chips would have.
Even the latest 4G networks are built with chips that were designed before Apple invited everyone to store their music libraries in the cloud and before Vine enabled every kid with a phone to create and distribute videos. Today’s networks were not designed with these wireless data applications in mind and they are struggling to keep up.
Making dumb networks smarter
The problem is proving hard to solve because data traffic is growing faster than the obvious ways to cope with it. Network operators can’t simply deliver more network capacity. Available spectrum is limited as is the capital to invest in expanded networks. The seemingly inevitable improvements in technology performance aren’t enough to solve the problem either. Demand for data traffic is growing faster than Moore’s law can answer. Doing more of the same thing or doing the same thing faster isn’t enough. Networking companies need to figure out new ways to handle data. We need to make dumb networks smarter.
When I say “dumb networks,” I am referring to the fact that most of the existing wireless data networks were designed to move a packet of data from point A to point B in a reasonably short time. That’s a fine approach when wireless networks can easily carry occasional stock updates and photo uploads from a few million early adopters. But now, when 90% of handset sales are iPhones or Android® phones, the networks have become overwhelmed with data. Treating data packets with equal importance – whether they are part of a VOIP phone call, business critical data or the 40 thousandth download of a cute panda video – doesn’t make sense anymore.
Prioritizing data for higher speed
As networks get smarter, they will be able to triage data – for example, identifying voice packets to maintain call quality. Smart networks will know if the same video has been downloaded 5 times in the last minute, and will store it locally to speed the next download. Smart networks will know if a business user has contracted for a guaranteed level of service and prioritize those packets accordingly. Smart networks will know if an application update can wait until times of the day when the volume of network traffic is lower. Smart networks will know if a flow of packets contains virus software that could damage your phone or the network itself.
To be smart about the data being transported, networks need a higher level of real-time analytical intelligence. We are now seeing the introduction of networking chips and equipment designed in the era of the smart phone. Networks are now gaining the ability to distinguish the nature of the data contained in a packet and to make smart decisions about the way the data is delivered. Networks are, in a word, becoming smarter – better able to manage the crush of data coursing through them every day. Smart networks may soon be able to stand up to smartphones, and perhaps even outwit them.
Have you ever seen the old BBC TV show “Connections”? It’s a little old now, but I loved how it followed threads through time, and I marveled at the surprising historical depth of important “inventions.” I think we need to remember that as engineers and technologists. We get caught up in the short-term tactical delivery of technology. We don’t see the sometimes immense ripples in society from our work – even years later.
I got a flurry of emails yesterday, arranging an anniversary get-together in August at the Apple campus. Why? It’s the 20th anniversary of the Newton. Ok – so this has nothing to do with LSI really, but it does have a lot to do with our everyday lives. More than you think.
So you either know the Newton and think it was a failure (think Trudeau’s famous handwriting cartoon), or you don’t and you’re wondering what the *bleep* I’m talking about. Sometimes things that don’t seem very significant early on end up having profound consequences. And I admit, the Newton was a failure, too expensive and not quite good enough, and the world couldn’t even get the concept of a general-purpose computer in your hand.
But oh – you could smell the future and get a tantalizing hint of what it would be. Remember – we’re talking 1993 here.
First – why does Rob Ober care? It’s personal. While I didn’t remotely help create the Newton, I did help bring it to market, mature the technology, and set the stage for the future (well – it’s not the future any more – it’s now). I was at Apple wrapping up the creation of the PowerPC processor and architecture, and the first Power Macs. I have a great memory around that time of getting the first Power Mac booted. Someone had the great idea of running the beta 68K emulator (to run standard Mac stuff). That was great, it worked, and then someone else said – wait – I have an Apple II emulator for the 68K Mac. So we had the very first PowerPC Mac running 68K code as a Mac to emulate a 6502 as an Apple II … and we played for hours. I also have a very clear memory of that PowerPC Mac standing shoulder-to-shoulder with the Robotron game in the Valley Green 5 building break room. It was a state-of-the-art video game and looked like this.
Yea, that shows you it was a while ago. (But it was a good game.)
A guy named Shane Robison pulled me over (yea, the same HP CTO, now CEO of FusionIO) to come fix some things on the super-hush Newton program. In the end, I took over responsibility for the processors, custom chips, communication stacks and hardware, plastics and tooling, display, touch screen, power supply, wireless, NiMH and LiION batteries… A lot. We pushed the limits of state of the art on all those fronts. It was a really important wonderful/terrible part of my career. I learned an amazing amount.
(If you’re interested in viewing a Newton from today’s perspective, there is a fascinating review here: http://techland.time.com/2012/06/01/newton-reconsidered/)
Let me start with some boring effects. We were using the ARM processor because of its low power. But. It wasn’t perfect, and ARM itself was on the edge of insolvency. We invested a sizable chunk of money, and gave it guidance on how to transition from ARM 6 to 7 to 9. ARM is alive today because of that, and the ARM 9 is still in 100’s of millions of products. And we also worked with DEC to create the StrongARM processor family, which became XScale at Intel, then went to Marvel, and also bootstrapped Atom, and, and…
The Newton needed non-volatile storage. Disks were immense, expensive and power-hungry. 2-1/2” disk? Didn’t exist. 3-1/2” was small. The only remotely cost-effective technology was called NAND flash, which was fundamentally incompatible with program execution, and nightmarish for data storage/retrieval, and unbelievably expensive per bit. I think the early Newtons were 8 Mbytes? (that’s mega not giga…). The team figured out how to make that work. Yep – that was the first use of Toshiba NAND for program/data. (I’ve been playing with flash for storage since then.)
Then some more interesting things…
I wired the Apple campus with wireless LAN base stations (it would be 6 years until Wifi, and 802.11 wasn’t even dreamt up yet) and built the wireless LAN receivers into Newtons, gave them to the Apple execs and set up their mail to be forwarded. You couldn’t even do that on laptops. We could be anywhere in the campus and instantly receive and send emails. More – we could browse the (rudimentary) web. I also worked with RIM (yea – Research In Motion – Blackberry) and Metricom to use their wireless wide area net technology to give Newtons access to email and the Web anywhere in the Bay Area. Quite a few times I was driving to meetings, wasn’t sure where to go, so pulled over and looked up the meeting in my Newton calendar, then checked the address on my browser with MapQuest. 1995. Sound familiar?
We also spent time with FedEx pitching it on the idea of a Newton-based tablet to manage inventory (integrated bar code scanner), accept signatures on screen with tablet/pen (even the upside down thing to hand it to the customer), show route maps, and cellularly send all that info back and forth for live tracking. FedEx was stunned by the concept. Sound familiar? I still have the proposal book with industrial designs in my garage. Yes, another Silicon Valley garage. Here’s what it rolled out 10 years later… which is ultimately pretty similar to our proposal.
And don’t forget Object Programming. (You remember when OOPS was a high-tech term?) I’m not really a software guy – just not my thing – but I loved programming on the Newton. In 10 minutes you could actually bang out a useful, great-looking program. Personally, I think the world would have been way better off if those object libraries had been folded into the Java object library. Even so, I get a nostalgic feel when I do iOS programming.
I even built a one-off proto that had cellphone guts inside the plastic of the Newton. (OK – it was chunky, but the smallest phones at the time were HUGE). I could make phone calls from the contacts or calendar or emails, send and receive SMS messages, and rudimentary MMS messages before there was such a thing – used just like a very overweight iPhone (OK – more like the big Samsung galaxy phones). I could even, in a pinch, do data over the GSM network – email, web, etc. It was around that time Nokia came calling and asked about our UI, our OS, our ability to used data over the GSM network… Those talks fell apart, but it was serious enough I made trips to Nokia’s mothership in Helsinki and Tampere a few times. (That’s north even for a Canadian boy…)
And then years later I got a phone call from one of the key people at Apple – Mike Culbert (who, sadly, recently passed away) – to ask about cellular/baseband chipsets and solutions. He knew I knew the technology. I introduced him to my friends at Infineon (now Intel Mobile) for a discussion on a mystery project… Those parts ended up in the iPhone. A lot of the same people and technology, just way more advanced…
iPad? Sure. A lot of the same people were involved in a Newton that never saw the light of day. The BIC. Here it is with the iPad. Again – 15 years apart.
And you remember the $100 laptop (OLPC?). As a founding board member, I brought an eMate kids Newton laptop to show the team early on. And of course the debate on disk vs. flash followed the same path as it had in Newton. Here they are together, separated by more than 10 years. And then of course, OLPC has direct genetic parentage of netbooks, which then lead to Ultrabooks… (Did you know at one point Apple was considering joining OLPC and offering Darwin/OSX as the OS? Didn’t last long.)
And then there are the people. Off the top of my head there were founders or key movers of Palm, Xbox, Kindle, Hotmail, Yahoo, Netscape, Android, WebTV (think most set-top boxes), Danger phone (you remember the sidekick?), Evernote, Mercedes research and a bunch of others. And some friends who became well-known VCs. And I still have a lot of super-talented friends from that time, many of whom are still at Apple.
Sometimes things that don’t seem very significant have profound follow-on consequences. I think we need to remember that as engineers and technologists. We don’t see the sometimes immense ripples in society from our work – even years later. Today we’re planting the seeds for all those great things in the future. I admit, the Newton was a failure, but oh – you could smell the future and get a tantalizing hint of what it would be. Remember – we’re talking 1993 here.
Tags: 802.11, Android, Apple, Apple II, ARM, BIC, Blackberry, Darwin, DEC, eMate, Evernote, FedEx, FusionIO, Hotmail, HP, Intel, iPad, iPhone, Kindle, Marvel, Mercedes, Metricom, Mike Culbert, MMS, Netscape, Newton, Nokia, object programming, OLPC, Palm, Power Mac, PowerPC, Research in Motion, Robotron, Shane Robison, SMS, StrongARM, Toshiba, Ultrabook, Web TV, Wifi, Xbox, XScale, Yahoo