I started working years ago to engage large datacenters, learn what their problems are and try to craft solutions for their problems. It’s taken years, but we engaged them, learned, changed how we thought about storage and began creating solutions that are being deployed at scale.
We’ve started to do the same with the Chinese Internet giants. They’re growing at an incredible rate. They have similar problems, but it’s surprising how different their solution approaches are. Each one is unique. And we’re constantly learning from these guys.
So to wrap up the blog series on my interview with CIO & CEO magazine, here are the last two questions to explain a bit more.
CEO & CIO: Please use examples to tell the stories about the forward-looking technologies and architectures that LSI has jointly developed with Internet giants.
While our host bus adapters (HBAs) and MegaRAID® solutions have been part of the hyperscale Internet companies’ infrastructure since the beginning, we have only recently worked very closely with them to drive joint innovation. In 2009 I led the first LSI engagement with what we then called “mega datacenters.” It took a while to understand what they were doing and why. By 2010 we realized there were specialized needs, and began to imagine new hardware products that worked with these datacenters. Out of this work came the realization that flash was important for efficiency and capability, and the “invention” of LSI® Nytro™ product portfolio. (More are in the pipeline). We have worked closely with hyperscale datacenters to evolve and tune these solutions, to where Nytro products have become the backbone of their main revenue platforms. Facebook has been a vitally important partner in evolving our Nytro platform – teaching us what was truly needed, and now much of their infrastructure runs on LSI products. These same products are a good fit for other hyperscale customers, and we are slowly winning many of the large ones.
Looking forward, we are partnered with several Internet giants in the U.S. and China to work on cold storage solutions, and more importantly shared DAS (Distributed DAS: D-DAS) solutions. We have been demonstrating prototypes. These solutions enable pooled architectures and rack scale architecture, and can be made to work tightly with software-defined datacenters (SDDCs). They simplify management and resource allocation – making task deployment more efficient and easier. Shared DAS solutions increase infrastructure efficiency and improves lifecycle management of components. And they have the potential to radically improve application performance and infrastructure costs.
Looking further into the future, we see even more radical changes in silicon supporting transport protocols and storage models, and in rack scale architectures supporting storage and pooled memory. And cold storage is a huge though, some would say, boring problem that we are also focused on – storing lots of data for free and using no power to do it… but I really can’t talk about any of that.
CEO & CIO: LSI maintains good contact with big Internet companies in China. What are the biggest differences between dealing with these Internet enterprises and dealing with traditional partners?
Yes, we have a very good relationship with large Chinese Internet companies. In fact, I will be visiting Tencent, Alibaba and Baidu in a few weeks. One of the CTOs I would like to say is a friend. That is, we have fun talking together about the future.
These meetings have evolved. The first meetings LSI had about two years ago were sales calls, or support for OEM storage solutions. These accomplished very little. Once we began visiting as architects speaking to architects, real dialogs began. Our CEO has been spending time in China meeting with these Internet companies both to learn, and to make it clear that they are important to us, and we want a chance to solve their problems. But the most interesting conversations have been the architectural ones. There have been very clear changes in the two years I have traveled within China – from standard enterprise to hyperscale architectures.
We’ve received fascinating feedback on architecture, use, application profiles, platforms, problems and goals. We have strong engagement with the U.S. Internet giants. At the highest level, the Chinese Internet companies have similar problems and goals. But the details quickly diverge because of revenue per user, resources, power availability, datacenter ownership and Internet company age. The use of flash is very different.
The Chinese Internet giants are at an amazing change point. Most are ready for explosive growth of infrastructure and deployment of cloud services. Most are changing from standard OEM systems and architectures to self-designed hyperscale systems after experimenting with Scorpio and microserver deployments. Several, like JD.com (an Amazon-like company) are moving from hosted to self-built infrastructure. And there seems to be a general realization that the datacenter has changed from a compute-centric model to a dataflow model, where storage and network dictate how much work gets done more than the CPU does. These giants are leveraging their experience and capability to move very quickly, and in a few cases are working to create true pooled rack level architectures much like Facebook and Google have started in the U.S. In fact, Baidu is similar to Facebook in this approach, but is different in its longer term goals for the architecture.
The Chinese companies are amazingly diverse, even within one datacenter, and arguments on architectural direction are raging within these Internet giants – it’s healthy and exciting. However, the innovations that are coming are similar to those developed by large U.S. Internet companies. Personally I have found these Internet companies much more exciting and satisfying to work with than traditional OEMs. The speed and cadence of advancement, the recognition of problems and their importance, the focus on efficiency and optimization have been much more exciting. And the youthful mentality and view to problems, without being burdened by “the way we’ve always done this” has been wonderful.
Also see these blogs of mine over the past year, where you can read more about some of these changes:
“Postcard from Shenzhen: China’s hyperscale datacenter growth, mixed with a more traditional approach”
“China in the clouds, again”
“China: A lot of talk about resource pooling, a better name for disaggregation”
Or see them (and others) all here.
Summary: So it’s taken years, but we engaged U.S. Internet giants, learned about their problems, changed how we thought about storage and began creating solutions that are now being deployed at scale. And we’re constantly learning from these guys. Constantly, because their problems are constantly changing.
We’ve now started to do the same with the Chinese Internet giants. They have similar problems, and will need similar solutions, but they are not the same. And just like the U.S. Internet giants, each one is unique.
Tags: Alibaba, Amazon, Baidu, CEO & CIO Magazine, China, cloud services, cold storage, D-DAS, DAS, datacenter, datacenter ecosystem, direct attached storage, distributed DAS, Facebook, flash, flash storage, Google, HBA, host bus adapter, hyperscale datacenter, Internet, JD.com, MegaRAID, OEM, original equipment manufacturer, Scorpio, Tencent
I was asked some interesting questions recently by CEO & CIO, a Chinese business magazine. The questions ranged from how Chinese Internet giants like Alibaba, Baidu and Tencent differ from other customers and what leading technologies big Internet companies have created to questions about emerging technologies such as software-defined storage (SDS) and software-defined datacenters (SDDC) and changes in the ecosystem of datacenter hardware, software and service providers. These were great questions. Sometimes you need the press or someone outside the industry to ask a question that makes you step back and think about what’s going on.
I thought you might interested, so this blog, the first of a 3-part series covering the interview, shares details of the first two questions.
CEO & CIO: In recent years, Internet companies have built ultra large-scale datacenters. Compared with traditional enterprises, they also take the lead in developing datacenter technology. From an industry perspective, what are the three leading technologies of ultra large-scale Internet data centers in your opinion? Please describe them.
There are so many innovations and important contributions to the industry from these hyperscale datacenters in hardware, software and mechanical engineering. To choose three is difficult. While I would prefer to choose hardware innovations as their big ones, I would suggest the following as they have changed our world and our industry and are changing our hardware and businesses:
Autonomous behavior and orchestration
An architect at Microsoft once told me, “If we had to hire admins for our datacenter in a normal enterprise way, we would hire all the IT admins in the world, and still not have enough.” There are now around 1 million servers in Microsoft datacenters. Hyperscale datacenters have had to develop autonomous, self-managing, sometimes self-deploying datacenter infrastructure simply to expand. They are pioneering datacenter technology for scale – innovating, learning by trial and error, and evolving their practices to drive more work/$. Their practices are specialized but beginning to be emulated by the broader IT industry. OpenStack is the best example of how that specialized knowledge and capability is being packaged and deployed broadly in the industry. At LSI, we’re working with both hyperscale and orchestration solutions to make better autonomous infrastructure.
High availability at datacenter level vs. machine level
As systems get bigger they have more components, more modes of failure and they get more complex and expensive to maintain reliability. As storage is used more, and more aggressively, drives tend to fail. They are simply being used more. And yet there is continued pressure to reduce costs and complexity. By the time hyperscale datacenters had evolved to massive scale – 100’s of thousands of servers in multiple datacenters – they had created solutions for absolute reliability, even as individual systems got less expensive, less complex and much less reliable. This is what has enabled the very low cost structures of the cloud, and made it a reliable resource.
These solutions are well timed too, as more enterprise organizations need to maintain on-premises data across multiple datacenters with absolute reliability. The traditional view that a single server requires 99.999% reliability is giving way to a more pragmatic view of maintaining high reliability at the macro level – across the entire datacenter. This approach accepts the failure of individual systems and components even as it maintains data center level reliability. Of course – there are currently operational issues with this approach. LSI has been working with hyperscale datacenters and OEMs to engineer improved operational efficiency and resilience, and minimized impact of individual component failure, while still relying on the datacenter high-availability (HA) layer for reliability.
It’s such an overused term. It’s difficult to believe the term barely existed a few years ago. The gift of Hadoop® to the industry – an open source attempt to copy Google® MapReduce and Google File System – has truly changed our world unbelievably quickly. Today, Hadoop and the other big data applications enable search, analytics, advertising, peta-scale reliable file systems, genomics research and more – even services like Apple® Siri run on Hadoop. Big data has changed the concept of analytics from statistical sampling to analysis of all data. And it has already enabled breakthroughs and changes in research, where relationships and patterns are looked for empirically, rather than based on theories.
Overall, I think big data has been one of the most transformational technologies this century. Big data has changed the focus from compute to storage as the primary enabler in the datacenter. Our embedded hard disk controllers, SAS (Serial Attached SCSI) host bus adaptors and RAID controllers have been at the heart of this evolution. The next evolutionary step in big data is the broad adoption of graph analysis, which integrates the relationship of data, not just the data itself.
CEO & CIO: Due to cloud computing, mobile connectivity and big data, the traditional IT ecosystem or industrial chain is changing. What are the three most important changes in LSI’s current cooperation with the ecosystem chain? How does LSI see the changes in the various links of the traditional ecosystem chain? What new links are worth attention? Please give some examples.
Cloud computing and the explosion of data driven by mobile devices and media has and continues to change our industry and ecosystem contributors dramatically. It’s true the enterprise market (customers, OEMs, technology, applications and use cases) has been pretty stable for 10-20 years, but as cloud computing has become a significant portion of the server market, it has increasingly affected ecosystem suppliers like LSI.
Timing: It’s no longer enough to follow Intel’s ticktock product roadmap. Development cycles for datacenter solutions used to be 3 to 5 years. But these cycles are becoming shorter. Now, demand for solutions is closer to 6 months – forcing hardware vendors to plan and execute to far tighter development cycles. Hyperscale datacenters also need to be able to expand resources very quickly, as customer demand dictates. As a result they incorporate new architectures, solutions and specifications out of cycle with the traditional Intel roadmap changes. This has also disrupted the ecosystem.
End customers: Hyperscale datacenters now have purchasing power in the ecosystem, with single purchase orders sometimes amounting to 5% of the server market. While OEMs still are incredibly important, they are not driving large-scale deployments or innovating and evolving nearly as fast. The result is more hyperscale design-win opportunities for component or sub-system vendors if they offer something unique or a real solution to an important problem. This also may shift profit pools away from OEMs to strong, nimble technology solution innovators. It also has the potential to reduce overall profit pools for the whole ecosystem, which is a potential threat to innovation speed and re-investment.
New players: Traditionally, a few OEMs and ISVs globally have owned most of the datacenter market. However, the supply chain of the hyperscale cloud companies has changed that. Leading datacenters have architected, specified or even built (in Google’s case) their own infrastructure, though many large cloud datacenters have been equipped with hyperscale-specific systems from Dell and HP. But more and more systems built exactly to datacenter specifications are coming from suppliers like Quanta. Newer network suppliers like Arista have increased market share. Some new hyperscale solution vendors have emerged, like Nebula. And software has shifted to open source, sometimes supported for-pay by companies copying the Redhat® Linux model – companies like Cloudera, Mirantis or United Stack. Personally, I am still waiting for the first 3rd-party hardware service emulating a Linux support and service company to appear.
Open initiatives: Yes, we’ve seen Hadoop and its derivatives deployed everywhere now – even in traditional industries like oil and gas, pharmacology, genomics, etc. And we’ve seen the emergence of open-source alternatives to traditional databases being deployed, like Casandra. But now we’re seeing new initiatives like Open Compute and OpenStack. Sure these are helpful to hyperscale datacenters, but they are also enabling smaller companies and universities to deploy hyperscale-like infrastructure and get the same kind of automated control, efficiency and cost structures that hyperscale datacenters enjoy. (Of course they don’t get fully there on any front, but it’s a lot closer). This trend has the potential to hurt OEM and ISV business models and markets and establish new entrants – even as we see Quanta, TYAN, Foxconn, Wistron and others tentatively entering the broader market through these open initiatives.
New architectures and new algorithms: There is a clear movement toward pooled resources (or rack scale architecture, or disaggregated servers). Developing pooled resource solutions has become a partnership between core IP providers like Intel and LSI with the largest hyperscale datacenter architects. Traditionally new architectures were driven by OEMs, but that is not so true anymore. We are seeing new technologies emerge to enable these rack-scale architectures (RSA) – technologies like silicon photonics, pooled storage, software-defined networks (SDN), and we will soon see pooled main memory and new nonvolatile main memories in the rack.
We are also seeing the first tries at new processor architectures about to enter the datacenter: ARM 64 for cool/cold storage and web tier and OpenPower P8 for high power processing – multithreaded, multi-issue, pooled memory processing monsters. This is exciting to watch. There is also an emerging interest in application acceleration: general-purposing computing on graphics processing units (GPGPUs), regular expression processors (regex) live stream analytics, etc. We are also seeing the first generation of graph analysis deployed at massive scale in real time.
Innovation: The pace of innovation appears to be accelerating, although maybe I’m just getting older. But the easy gains are done. On one hand, datacenters need exponentially more compute and storage, and they need to operate 10x to 1000x more quickly. On the other, memory, processor cores, disks and flash technologies are getting no faster. The only way to fill that gap is through innovation. So it’s no surprise there are lots of interesting things happening at OEMs and ISVs, chip and solution companies, as well as open source community and startups. This is what makes it such an interesting time and industry.
Consumption shifts: We are seeing a decline in laptop and personal computer shipments, a drop that naturally is reducing storage demand in those markets. Laptops are also seeing a shift to SSD from HDD. This has been good for LSI, as our footprint in laptop HDDs had been small, but our presence in laptop SSDs is very strong. Smart phones and tablets are driving more cloud content, traffic and reliance on cloud storage. We have seen a dramatic increase in large HDDs for cloud storage, a trend that seems to be picking up speed, and we believe the cloud HDD market will be very healthy and will see the emergence of new, cloud-specific HDDs that are radically different and specifically designed for cool and cold storage.
There is also an explosion of SSD and PCIe flash cards in cloud computing for databases, caches, low-latency access and virtual machine (VM) enablement. Many applications that we take for granted would not be possible without these extreme low-latency, high-capacity flash products. But very few companies can make a viable storage system from flash at an acceptable cost, opening up an opportunity for many startups to experiment with different solutions.
Summary: So I believe the biggest hyperscale innovations are autonomous behavior and orchestration, HA at the datacenter level vs. machine level, and big data. These are radically changing the whole industry. And what are those changes for our industry and ecosystem? You name it: timing, end customers, new players, open initiatives, new architectures and algorithms, innovation, and consumption patterns. All that’s staying the same are legacy products and solutions.
These were great questions. Sometimes you need the press or someone outside the industry to ask a question that makes you step back and think about what’s going on. Great questions.
Tags: Alibaba, Apple Siri, Arista, ARM 64, Baidu, big data, Casandra, CEO & CIO Magazine, China, cloud storage, Cloudera, cold storage, cool storage, datacenter, datacenter ecosystem, Dell, flash, Foxconn, Google File System, Google MapReduce, Hadoop, hard disk drive, HDD, high availability, HP, hyperscale datacenter, Intel, Internet, latency, Microsoft, Mirantis, Nebula, OEM, Open Compute, OpenPower P8, OpenStack, original equipment manufacturer, Quanta, rack scale, RAID, Redhat Linux, SAS, SDDC, SDN, SDS, Serial Attached SCSI, software-defined datacenter, software-defined networks, software-defined storage, solid state drive, SSD, Tencent, TYAN, United Stack, virtual machine, VM, Wistron
Open Compute and OpenStack are changing the datacenter world that we know and love. I thought they were having impact. Changing our OEMs and ODM products, changing what we expect from our vendors, changing the interoperability of managing infrastructure from different vendors. Changing our ability to deploy and manage grid and scale-out infrastructure. And changing how quickly and at what high level we can be innovating. I was wrong. It’s happening much more quickly than I thought.
On November 20-21 we hosted LSI AIS 2013. As I mentioned in a previous post, I was lucky enough to moderate a panel about Open Compute and OpenStack – “the perfect storm.” Truthfully? It felt more like sitting with two friends talking about our industry over beer. I hope to pick up that conversation again someday.
The panelists were awesome: Cole Crawford of Open Compute and Chris Kemp of OpenStack. These guys are not only influential. They have been involved from the very start of these two initiatives, and are in many ways key drivers of both movements. These are impressive, passionate guys who really are changing the world. There aren’t too many of us who can claim that. It was an engaging hour that I learned quite a bit from, and I think the audience did too. I wanted to share from my notes what I took away from that panel. I think you’ll be interested.
Goals and Vision: two “open source” initiatives
There were a few motivations behind Open Compute, and the goal was to improve these things.
The goal then, for the first time, is to work backwards from workload and create open source hardware and infrastructure that is openly available and designed from the start for large scale-out deployments. The idea is to drive high efficiency in cost, materials use and energy consumption. More work/$.
One surprising thing that came up – LSI is in every current contribution in Open Compute.
OpenStack layers services that describe abstractions of computer networking and storage. LSI products tend to sit at that lowest level of abstraction, where there is now a wave of innovation. OpenStack had similar fragmentation issues to deal with and its goals are something like:
There is a certain amount of compatibility with Amazon’s cloud services. Chris’s point was that Amazon is incredibly innovative and a lot of enterprises should use it, but OpenStack enables both service providers and private clouds to compete with Amazon, and it allows unique innovation to evolve on top of it.
OpenStack and Open Compute are not products. They are “standards” or platform architectures, with companies using those standards to innovate on top of them. The idea is for one company to innovate on another’s improvements – everybody building on each other’s work. A huge brain trust. The goal is to create a competitive ecosystem and enable a rapid pace of innovation, and enable large-scale, inexpensive infrastructure that can be managed by a small team of people, and can be managed like a single server to solve massive scale problems.
Here’s their thought. Hardware is a supply chain management game + services. Open Compute is an opportunity for anyone to supply that infrastructure. And today, OEMs are killer at that. But maybe ODMs can be too. Open Compute allows innovation on top of the basic interoperable platforms. OpenStack enables a framework for innovation on top as well: security, reliability, storage, network, performance. It becomes the enabler for innovation, and it provides an “easy” way for startups to plug into a large, vibrant ecosystem. And for customers – someone said its “exa data without exadollar”…
As a result, the argument is this should be good for OEMs and ISVs, and help create a more innovative ecosystem and should also enable more infrastructure capacity to create new and better services. I’m not convinced that will happen yet, but it’s a laudable goal, and frankly that promise is part of what is appealing to LSI.
Open Compute and OpenStack are “peanut butter and jelly”
Ok – if you’re outside of the US, that may not mean much to you. But if you’ve lived in the US, you know that means they fit perfectly, and make something much greater together than their humble selves.
Graham Weston, Chairman of the Rackspace Board, was the one who called these two “peanut butter and jelly.”
Cole and Chris both felt the initiatives are co-enabling, and probably co-travelers too. Sure they can and will deploy independently, but OpenStack enables the management of large scale clusters, which really is not easy. Open Compute enables lower cost large-scale manageable clusters to be deployed. Together? Large-scale clusters that can be installed and deployed more affordably, and easily without hiring a cadre of rare experts.
Personally? I still think they are both a bit short of being ready for “prime time” – or broad deployment, but Cole and Chris gave me really valid arguments to show me I’m wrong. I guess we’ll see.
US or global vision?
I asked if these are US-centric or global visions. There were no qualms – these are global visions. This is just the 3rd anniversary of OpenStack, but even so, there are OpenStack organizations in more than 100 countries, 750 active contributors, and large-scale deployments in datacenters that you probably use every day – especially in China and the US. Companies like PayPal and Yahoo, Rackspace, Baidu, Sina Weibo, Alibaba, JD, and government agencies and HPC clusters like CERN, NASA, and China Defense.
Open Compute is even younger – about 2 years old. (I remember – I was invited to the launch). Even so, most of Facebook’s infrastructure runs on Open Compute. Two Wall Street banks have deployed large clusters, with more coming, and Riot Games, which uses Open Compute infrastructure, drives 3% of the global network traffic with League of Legends. (A complete aside – one of my favorite bands to workout with did a lot of that game’s music, and the live music at the League of Legends competition a few months ago: http://www.youtube.com/watch?v=mWU4QvC09uM – not for everyone, but I like it.)
Both Cole and Chris emailed me more data after the fact on who is using these initiatives. I have to say – they are right. It really has taken off globally, especially OpenStack in the fast-paced Chinese market this year.
Book: 4th Paradigm – A tribute to computer science researcher Jim Grey
Cole and Chris mentioned a book during the panel discussion. A book I had frankly never heard of. It’s called the 4th Paradigm. It was a series of papers dedicated to researcher Jim Grey, who was a quiet but towering figure that I believe I met once at Microsoft Research. The book was put together by Gordon Bell, someone who I have met, and have profound respect for. And there are mentions of people, places, and things that have been woven through my (long) career. I think I would sum up its thesis in a quote from Jim Grey near the start of the book:
“We have to do better producing tools to support the whole research cycle – from data capture and data curation to data analysis and data visualization.”
This is stunningly similar to the very useful big data framework we have been using recently at LSI: ”capture, hold, analyze”… I guess we should have added visualize, but that doesn’t have too much to do with LSI’s business.
As an aside, I would recommend this book for the background and inspiration in why we as an industry are trying to solve many of these computer science problems, and how transformational the impact might be. I mean really transformational in the world around us, what we know, what we can do, and how quickly we can do it – which is tightly related to our CEO’s keynote and the vision video at AIS.
Demos at AIS: “peanut butter and jelly” - and bread?
Ok – I’m struggling for analogy. We had an awesome demo at AIS that Chris and Cole pointed out during the panel. It was originally built using Nebula’s TOR appliance, Open Compute hardware, and LSI’s storage magic to make it complete. The three pieces coming together. Tasty. The Open Compute hardware was swapped out last minute (for safety, those boxes were meant for the datacenter – not the showcase in a hotel with tipsy techies) and were generously supplied by Supermicro.
I don’t think the proto was close to any one of our visions, but even as it stood, it inspired a lot of people, and would make a great product. A short rack of servers, with pooled storage in the rack, OpenStack orchestrating the point and click spawning and tear down of dynamically sized LUNs of different characteristics under the Cinder presentation layer, and deployment of tasks or VMs on them.
We’re working on completing our joint vision. I think the industry will be very impressed when they see it. Chris thinks people will be stunned, and the industry will be changed.
Catalyzing the market… The future may be closer than we think…
Ultimately, this is all about economics. We’re in the middle of an unprecedented bifurcation in IT use. On one hand we’re running existing apps on new, dense enterprise hardware using VMs to layer many applications on few servers. On the other, we’re investing in applications to run at scale across inexpensive clusters of commodity hardware. This has spawned a split in IT vendor business units, product lines and offerings, and sometimes even IT infrastructure management in the datacenter.
New applications and services are needing more infrastructure, and are getting more expensive to power, cool, purchase, run. And there is pressure to transform the datacenter from a cost center into a profit center. As these innovations start, more companies will need scale infrastructure, arguably Open Compute, and then will need an Openstack framework to deploy it quickly.
Whats this mean? With a combination of big data and mobile device services driving economic value, we may be at the point where these clusters start to become mainstream. As an industry we’re already seeing a slight decline in traditional IT equipment sales and a rapid growth in scale-out infrastructure sales. If that continues, then OpenStack and Open Compute are a natural fit. The deployment rate uptick in life sciences, oil and gas, financials this year – really anywhere there is large-scale Hadoop, big data or analytics – may be the start of that growth curve. But both Chris and Cole felt it would probably take 5 years to truly take off.
Time to Wrap Up
I asked Chris and Cole for audience takeaways. Theirs were pretty simple, though possibly controversial in an industry like ours.
Hardware vendors should think about products and how they interface and what abstractions they present and how they fit into the ecosystem. These new ecosystems should allow them to easily plug in. For example, storage under Cinder can be quickly and easily morphed – that’s what we did with our demo.
We should be designing new software to run on distributed scale-out systems in clouds. Chris went on to say their code name was “Maestro” because it orchestrates like in a symphony, bringing things together in a beautiful way. He said “make instruments for the artists out there.” The brain trust. Look for their brushstrokes.
Innovate in the open, and leverage the open initiatives that are available to accelerate innovation and efficiency.
On your next IT purchase, try an RFP with an Open Compute vendor. Cole said you might be surprised. Worst case, you may get a better deal from your existing vendor.
So, Open Compute and Openstack are changing the datacenter world that we know and love. I thought these were having a quick impact, changing our OEMs and ODM products, changing what we expect from our vendors, changing the interoperability of managing infrastructure from different vendors, changing our ability to deploy and manage grid and scale-out infrastructure, and changing how quickly and at what high level we can be innovating. I was wrong. It’s happening much more quickly than even I thought.
Tags: AIS, Alibaba, Amazon, Baidu, big data, CERN, China, China Defense, Chris Kemp, Cole Crawford, datacenter, Facebook, Hadoop, HPC, IT infrastructure, JD, Jim Grey, NASA, Nebula, Networking, Open Compute, OpenStack, PayPal, Rackspace, Riot Games, scale-out cluster, Sina Weibo, Storage, Supermicro, Yahoo
You might be surprised to find out how big the infrastructure for cloud and Web 2.0 is. It is mind-blowing. Microsoft has acknowledged packing more than 1 million servers into its datacenters, and by some accounts that is fewer than Google’s massive server count but a bit more than Amazon.
Facebook’s server count is said to have skyrocketed from 30,000 in 2012 to 180,000 just this past August, serving 900 million plus users. And the social media giant is even putting its considerable weight behind the Open Compute effort to make servers fit better in a rack and draw less power. The list of mega infrastructures also includes Tencent, Baidu and Alibaba and the roster goes on and on.
Even more jaw-dropping is that almost 99.9% of these hyperscale infrastructures are built with servers featuring direct-attached storage. That’s right – they do the computing and store the data. In other words, no special, dedicated storage gear. Yes, your Facebook photos, your Skydrive personal cloud and all the content you use for entertainment, on-demand video and gaming data are stored inside the server.
Direct-attached storage reigns supreme
Everything in these infrastructures – compute and storage – is built out of x-86 based servers with storage inside. What’s more, growth of direct-attached storage is many folds bigger than any other storage deployments in IT. Rising deployments of cloud, or cloud-like, architectures are behind much of this expansion.
The prevalence of direct-attached storage is not unique to hyperscale deployments. Large IT organizations are looking to reap the rewards of creating similar on-premise infrastructures. The benefits are impressive: Build one kind of infrastructure (server racks), host anything you want (any of your properties), and scale if you need to very easily. TCO is much less than infrastructures relying on network storage or SANs.
With direct-attached you no longer need dedicated appliances for your database tier, your email tier, your analytics tier, your EDA tier. All of that can be hosted on scalable, share-nothing infrastructure. And just as with hyperscale, the storage is all in the server. No SAN storage required.
Open Compute, OpenStack and software-defined storage drive DAS growth
Open Compute is part of the picture. A recent Open Compute show I attended was mostly sponsored by hyperscale customers/suppliers. Many big-bank IT folks attended. Open Compute isn’t the only initiative driving growing deployments of direct-attached storage. So is software-defined storage and OpenStack. Big application vendors such as Oracle, Microsoft, VMware and SAP are also on board, providing solutions that support server-based storage/compute platforms that are easy and cost-effective to deploy, maintain and scale and need no external storage (or SAN including all-flash arrays).
So if you are a network-storage or SAN manufacturer, you have to be doing some serious thinking (many have already) about how you’re going to catch and ride this huge wave of growth.
Tags: Alibaba, Amazon, Baidu, cloud computing, DAS, direct attached storage, enterprise, enterprise IT, Google, hyperscale, Microsoft, Open Compute, OpenStack, Oracle, SAP, Tencent, VMware
I am sitting in the terminal waiting for my flight home from – yes, you guessed it – China. I am definitely racking up frequent flier miles this year.
This trip ended up centering on resource pooling in the datacenter. Sure, you might hear a lot about disaggregation, but the consensus seems to be: that’s the wrong name (unless you happen to make standalone servers). For anyone else, it’s about a much more flexible infrastructure, simplified platforms, better lifecycle management, and higher efficiency. I call it “resource pooling,” which is descriptive, but others simply call it rack scale architecture.
It’s been a long week, but very interesting. I was asked to keynote at the SACC conference (Systems Architect Conference China) in Beijing. It was also a great chance to meet 1-on-1 with the CTOs and chief architects from the big datacenters, and visit for a few hours with other acquaintances. I even had the chance to have dinner with the CEO /CIO China Magazine editor in chief, and CIO’s from around Beijing. As always in life, if you’re willing to listen, you can learn a lot. And I did.
Thinking on disaggregation aligns
With CTOs, there was a lot of discussion about disaggregation in the datacenter. There is a lot of aligned thinking on the topic, and it’s one of those occasions where you had to laugh because I think anyone of the CTOs keynoting could have given anyone else’s presentation. So what’s the big deal? Resource pooling and rack scale architecture.
I’ll use this trip as an excuse to dig a little deeper into my view on what this means.
First – you need to understand where these large datacenters are in their evolution. They usually have 4 to 6 platforms and2 or 3 generations of each in the datacenter. That can be 18 different platforms to manage, maintain, and tune. Worse – they have to plan 6 to 9 months in advance to deploy equipment. If you guess wrong, you’ve got a bunch of useless equipment, and you spent a bunch of money – the size of mistake that will get you fired… And even if you get it right, you’re left with the problem – Do I upgrade servers when the CPU is new? Or at, say, 18 months? Or do I wait until the biggest cost item – the drives – need to be replaced in 4 or 5 years? That’s difficult math. So resource pooling is about lifecycle management of different types of components and sub-systems. You can optimally replace each resource on its own schedule.
Increasing resource utilization and efficiency
But it’s also about resource utilization and efficiency. Datacenters have multiple platforms because each platform needs a different configuration of resources. I use the term configuration on purpose. If you have storage in your server, it’s in some standard configuration – say, 6 3 TByte drives or 18 raw TBytes. Do you use all that capacity? Or do you leave some space so databases can grow? Of course you leave empty space. You might not even have any use for that much storage in that particular server – maybe you just use half the capacity. After all, it’s a standard configuration. What about disk bandwidth? Can your Hadoop node saturate 6 drives? Probably. It could probably use 12 or maybe even 24. But sorry – it’s a standard configuration. What about latency-sensitive databases? Sure, I can plug a PCIe card in, but I only have 1.6 TByte PCIe cards as my standard configuration. My database is 1.8 TBytes and growing. Sorry – you have to refactor and put on 2 servers. Or my database is only 1 TByte. I’m wasting 600 GBytes of really expensive resource.
For network resources – the standard configuration gets maybe exactly 1 10GE port. You need more? Can’t have it. You don’t need that much? Sorry – wasted bandwidth capacity. What about standard memory? You either waste DRAM you don’t use, or you starve for more DRAM you can’t get.
But if I have pools of rack scale resources that I can allocate to a standard compute platform – well – that’s a different story. I can configure exactly the amount of network bandwidth, memory, flash high- performance storage, and disk bulk storage. I can even add more configured storage if a database grows, instead of being forced to refactor a database into shards across multiple standard configurations.
Pooling resources = simplified operations
So the desire to pool resources is really as much about simplified operations as anything else. I can have standardized modules that are all “the same” to manage, but can be resource configured into a well-tailored platform that can even change over time.
But pooling is also about accommodating how the application architectures have changed, and how much more important dataflow is than compute for so much of the datacenter. As a result there is a lot of uncertainty about how parts of these rack scale architectures and interconnect will evolve, even as there is a lot of certainty that they will evolve, and they will include pooled resource “modules.” Whatever the overall case, we’re pretty sure we understand how the storage will evolve. And at a high level, that’s what I presented in my keynote. (Hey – I’m not going to publicly share all our magic!)
One storage architecture of pooled resources at the rack scale level. One storage architecture that combines boot management, flash storage for performance, and disk storage for efficient bandwidth and capacity. And those resources can be allocated however and whenever the datacenter manager needs them. And the existing software model doesn’t need to change. Existing apps, OS’s, file systems, and drivers are all supported, meaning a change to pooled resource rack scale deployments is de-risked dramatically. Overall, this one architecture simplifies the number of platforms, simplifies the management of platforms, utilizes the resources very efficiently, and simplifies image and boot management. I’m pretty sure it even reduces datacenter-level CapEx. I know it dramatically reduces OpEx.
Yea – I know what you’re thinking – it’s awesome ! (That’s what you thought – right?)
Oh – what about those CIO meetings? Well, there is tremendous pressure to not buy American IT equipment in China because of all the news from the Snowden NSA leaks. As most of the CIO’s pointed out, though, in today’s global sourcing market, it’s pretty hard to not buy US IT equipment. So they’re feeling a bit trapped. In a no-risk profession, I suspect that means they just won’t buy anything for a year or so and hope it blows over.
But in general, yep, I think this trip was centered on resource pooling in the datacenter. Sure, you might hear about disaggregation, but there’s a lot of agreement that’s the wrong name. It’s much more about resource pooling for flexible infrastructure, simplified platforms, better lifecycle management, and higher efficiency. And we aim to be right in the middle. Literally.
I’ve just been to China. Again. It’s only been a few months since I was last there.
I was lucky enough to attend the 5th China Cloud Computing Conference at the China National Convention Center in Beijing. You probably have not heard of it, but it’s an impressive conference. It’s “the one” for the cloud computing industry. It was a unique view for me – more of an inside-out view of the industry. Everyone who’s anyone in China’s cloud industry was there.
First, the air was really hazy, but I don’t think the locals considered it that bad. The US consulate iPhone app said the particulates were in the very unhealthy range. Imagine looking across the street. Sure, you can see the building there, but the next one? Not so much. Look up. Can you see past the 10th floor? No, not really. The building disappears into the smog. That’s what it was like at the China National Convention Center, which is part of the same Olympics complex as the famous Birdcage stadium: http://www.cnccchina.com/en/Venues/Traffic.aspx
I had a fantastic chance to catch up with a university friend, who has been living in Beijing since the 90’s, and is now a venture capitalist. It’s amazing how almost 30 years can disappear and you pick up where you left off. He sure knows how to live. I was picked up in his private limo, whisked off to a very well-known restaurant across the city, where we had a private room and private waitress. We even had some exotic, special dishes that needed to be ordered at least a day in advance. Wow. But we broke Chinese tradition and had imported beer in honor of our Canadian education.
Sizing up China’s cloud infrastructure
The most unusual meeting I attended was an invitation-only session – the Sino-American roundtable on cloud computing. There were just about 40 people in a room – half from the US, half from China. Mostly what I learned is that the cloud infrastructure in China is fragmented, and probably sub-scale. And it’s like that for a reason. It was difficult to understand at first, but I think I’ve made sense of it.
I started asking why to friends and consultants and got some interesting answers. Essentially different regional governments are trying to capture the cloud “industry” in their locality, so they promote activity, and they promote creation of new tools and infrastructure for that. Why reuse something that’s open source and works if you don’t have to and you can create high-tech jobs? (That’s sarcasm, by the way.) Many technologists I spoke with felt this will hold them back, and that they are probably 3-5 years behind the US. As well, each government-run industry specifies the datacenter and infrastructure needed to be a supplier or ecosystem partner with them, and each is different. The national train system has a different cloud infrastructure from the agriculture department, and from the shipping authority, etc… and if you do business with them – that is you are part of their ecosystem of vendors, then you use their infrastructure. It all spells fragmentation and sub-scale. In contrast, the Web 2.0 / social media companies seem to be doing just fine.
Baidu was also showing off its open rack. It’s an embodiment of the Scorpio V1 standard, which was jointly developed with Tencent, Alibaba and China Telecom. It views this as a first experiment, and is looking forward to V2, which will be a much more mature system.
I was also lucky to have personal meetings with general managers,chief architects and effective CTOs of the biggest cloud companies in China. What did I learn? They are all at an inflexion point. Many of the key technologists have experience at American Web 2.0 companies, so they’re able to evolve quickly, leveraging their industry knowledge. They’re all working to build or grow their own datacenters, their own infrastructure. And they’re aggressively expanding products, not just users, so they’re getting a compound growth rate.
Here’s a little of what I learned. In general, there is a trend to try and simplify infrastructure, harmonize divergent platforms, and deploy more infrastructure by spending less on each unit. (In general, they don’t make as much per user as American companies, but they have more users). As a result they are more cost-focused than US companies. And they are starting to put more emphasis on operational simplicity in general. As one GM described it to me – “Yes, techs are inexpensive in China for maintainence, but more often than not they make mistakes that impact operations.” So we (LSI) will be focussing more on simplifying management and maintainence for them.
Baidu’s biggest Hadoop cluster is 20k nodes. I believe that’s as big as Yahoo’s – and it is the originator of Hadoop. Baidu has a unique use profile for flash – it’s not like the hyperscale datacenters in the US. But Baidu is starting to consume a lot. Like most other hyperscale datacenters, it is working on storage erasure coding across servers, racks and datacenters, and it is trying to make a unified namespace across everything. One of its main interests is architecture at datacenter level, harmonizing the various platforms and looking for the optimum at the datacenter level. In general, Baidu is very proud of the advances it has made, and it has real confidence in its vision and route forward, and from what I heard, its architectural ambitions are big.
JD.com (which used to be 360buy.com) is the largest direct ecommerce company in China and (only) had about $10 billion (US) in revenue last year, with 100% CAGR growth. As the GM there said, its growth has to slow sometime, or in 5 years it’ll be the biggest company in the world. I think it is the closest equivalent to Amazon there is out there, and they have similar ambitions. They are in the process of transforming to a self-built, self-managed datacenter infrastructure. It is a company I am going to keep my eyes on.
Tencent is expanding into some interesting new businesses. Sure, people know about the Tencent cloud services that the Chinese government will be using, but Tencent also has some interesting and unique cloud services coming. Let’s just say even I am interested in using them. And of course, while Tencent is already the largest Web 2.0 company in China, its new services promise to push it to new scale and new markets.
Extra! Extra! Read all about it …
And then there was press. I had a very enjoyable conversation with Yuan Shaolong, editor at WatchStor, that I think ran way over. Amazingly – we discovered we have the same favorite band, even half a world away from each other. The results are here, though I’m not sure if Google translate messed a few things up, or if there was some miscommunication, but in general, I think most of the basics are right: http://translate.google.com/translate?hl=en&sl=zh-CN&u=http://tech.watchstor.com/storage-module-144394.htm&prev=/search%3Fq%3Drobert%2Bober%2BLSI%26client%3Dfirefox-a%26rls%3Dorg.mozilla:en-US:official%26biw%3D1346%26bih%3D619
I just keep learning new things every time I go to China. I suspect it has as much to do with how quickly things are changing as new stuff to learn. So I expect it won’t be too long until I go to China, again…
I’ve been travelling to China quite a bit over the last year or so. I’m sitting in Shenzhen right now (If you know Chinese internet companies, you’ll know who I’m visiting). The growth is staggering. I’ve had a bit of a trains, planes, automobiles experience this trip, and that’s exposed me to parts of China I never would have seen otherwise. Just to accommodate sheer population growth and the modest increase in wealth, there is construction everywhere – a press of people and energy, constant traffic jams, unending urban centers, and most everything is new. Very new. It must be exciting to be part of that explosive growth. What a market. I mean – come on – there are 1.3 billion potential users in China.
The amazing thing for me is the rapid growth of hyperscale datacenters in China, which is truly exponential. Their infrastructure growth has been 200%-300% CAGR for the past few years. It’s also fantastic walking into a building in China, say Baidu, and feeling very much at home – just like you walked into Facebook or Google. It’s the same young vibe, energy, and ambition to change how the world does things. And it’s also the same pleasure – talking to architects who are super-sharp, have few technical prejudices, and have very little vanity – just a will to get to business and solve problems. Polite, but blunt. We’re lucky that they recognize LSI as a leader, and are willing to spend time to listen to our ideas, and to give us theirs.
Even their infrastructure has a similar feel to the US hyperscale datacenters. The same only different. ;-)
A lot of these guys are growing revenue at 50% per year, several getting 50% gross margin. Those are nice numbers in any country. One has $100’s of billions in revenue. And they’re starting to push out of China. So far their pushes into Japan have not gone well, but other countries should be better. They all have unique business models. “We” in the US like to say things like “Alibaba is the Chinese eBay” or “Sina Weibo is the Chinese Twitter”…. But that’s not true – they all have more hybrid business models, unique, and so their datacenter goals, revenue and growth have a slightly different profile. And there are some very cool services that simply are not available elsewhere. (You listening Apple®, Google®, Twitter®, Facebook®?) But they are all expanding their services, products and user base. Interestingly, there is very little public cloud in China. So there are no real equivalents to Amazon’s services or Microsoft’s Azure. I have heard about current development of that kind of model with the government as initial customer. We’ll see how that goes.
100’s of thousands of servers. They’re not the scale of Google, but they sure are the scale of Facebook, Amazon, Microsoft…. It’s a serious market for an outfit like LSI. Really it’s a very similar scale now to the US market. Close to 1 million servers installed among the main 4 players, and exabytes of data (we’ve blown past mere petabytes). Interestingly, they still use many co-location facilities, but that will change. More important – they’re all planning to probably double their infrastructure in the next 1-2 years – they have to – their growth rates are crazy.
Often 5 or 6 distinct platforms, just like the US hyperscale datacenters. Database platforms, storage platforms, analytics platforms, archival platforms, web server platforms…. But they tend to be a little more like a rack of traditional servers that enterprise buys with integrated disk bays, still a lot of 1G Ethernet, and they are still mostly from established OEMs. In fact I just ran into one OEM’s American GM, who I happen to know, in Tencent’s offices today. The typical servers have 12 HDDs in drive bays, though they are starting to look at SSDs as part of the storage platform. They do use PCIe® flash cards in some platforms, but the performance requirements are not as extreme as you might imagine. Reasonably low latency and consistent latency are the premium they are looking for from these flash cards – not maximum IOPs or bandwidth – very similar to their American counterparts. I think hyperscale datacenters are sophisticated in understanding what they need from flash, and not requiring more than that. Enterprise could learn a thing or two.
Some server platforms have RAIDed HDDs, but most are direct map drives using a high availability (HA) layer across the server center – Hadoop® HDFS or self-developed Hadoop like platforms. Some have also started to deploy microserver archival “bit buckets.” A small ARM® SoC with 4 HDDs totaling 12 TBytes of storage, giving densities like 72 TBytes of file storage in 2U of rack. While I can only find about 5,000 of those in China that are the first generation experiments, it’s the first of a growing wave of archival solutions based on lower performance ARM servers. The feedback is clear – they’re not perfect yet, but the writing is on the wall. (If you’re wondering about the math, that’s 5,000 x 12 TBytes = 60 Petabytes….)
Yes, it’s important, but maybe more than we’re used to. It’s harder to get licenses for power in China. So it’s really important to stay within the envelope of power your datacenter has. You simply can’t get more. That means they have to deploy solutions that do more in the same power profile, especially as they move out of co-located datacenters into private ones. Annually, 50% more users supported, more storage capacity, more performance, more services, all in the same power. That’s not so easy. I would expect solar power in their future, just as Apple has done.
Here’s where it gets interesting. They are developing a cousin to OpenCompute that’s called Scorpio. It’s Tencent, Alibaba, Baidu, and China Telecom so far driving the standard. The goals are similar to OpenCompute, but more aligned to standardized sub-systems that can be co-mingled from multiple vendors. There is some harmonization and coordination between OpenCompute and Scorpio, and in fact the Scorpio companies are members of OpenCompute. But where OpenCompute is trying to change the complete architecture of scale-out clusters, Scorpio is much more pragmatic – some would say less ambitious. They’ve finished version 1 and rolled out about 200 racks as a “test case” to learn from. Baidu was the guinea pig. That’s around 6,000 servers. They weren’t expecting more from version 1. They’re trying to learn. They’ve made mistakes, learned a lot, and are working on version 2.
Even if it’s not exciting, it will have an impact because of the sheer size of deployments these guys are getting ready to roll out in the next few years. They see the progression as 1) they were using standard equipment, 2) they’re experimenting and learning from trial runs of Scorpio versions 1 and 2, and then they’ll work on 3) new architectures that are efficient and powerful, and different.
Information is pretty sketchy if you are not one of the member companies or one of their direct vendors. We were just invited to join Scorpio by one of the founders, and would be the first group outside of China to do so. If that all works out, I’ll have a much better idea of the details, and hopefully can influence the standards to be better for these hyperscale datacenter applications. Between OpenCompute and Scorpio we’ll be seeing a major shift in the industry – a shift that will undoubtedly be disturbing to a lot of current players. It makes me nervous, even though I’m excited about it. One thing is sure – just as the server market volume is migrating from traditional enterprise to hyperscale datacenter (25-30% of the server market and growing quickly), we’re starting to see a migration to Chinese hyperscale datacenters from US-based ones. They have to grow just to stay still. I mean – come on – there are 1.3 billion potential users in China….
Tags: Alibaba, Amazon, Apple, ARM, Baidu, China, China Telecom, datacenter, Facebook, Google, Hadoop, hard disk drive, HDD, hyperscale, Microsoft, OpenCompute, Scorpio, Shenzhen, Sina Weibo, solid state drive, SSD, Tencent, Twitter