A provocative title for sure when everyone thinks we just started the era of cloud computing. I recently listened to a talk by Peter Levine, general partner at Andreessen Horowitz on this topic which makes a ton of sense. The proliferation of intelligent devices and the rise of IoT (Internet of Things) lead us to a new world beyond what we see today in cloud computing (in terms of scale).
I have said many times that the onset of cloud computing was like back to the future of centralized computing. We had IBM mainframes, dominating the centralized computing era during the 1960s and 1970s. The introduction of PCs created the world of client-server computing (remember the wintel duopoly?) from 1980s till 2000. Then the popularity of the mobile devices started the cloud era in 2005, thus taking us back to centralized computing again. The text message I send you does not go from my device to your device directly, but gets to a server somewhere in the cloud first and then to your phone. The trillions of smart devices forecasted to appear as sensors in automobiles, home appliances, airplanes, drones, engines, and almost any thing you can imagine (like in your shoe) will drastically change the computing paradigm again. Each of these “edge intelligent devices” can not go back and forth to the cloud for every interaction. Rather they would want to process data at the edge to cut down latency. This brings us back to a new form of “distributed computing” model – kind of back to a vastly expanded version of the “PC era”.
Peter emphasized that the cloud will continue to exist, but its role will change from being the central hub to a “learning center” where curated data from the edge (only relevant data) resides in the cloud. The learning gets pushed back to the edge for getting better at its job. The edge of the cloud does three things – sense, infer, and act. The sense level handles massive amount of data like in a self-driving car (10GB per mile), thus making it like a “data center on wheels”. The sheer volume of data is too much to push back to the cloud. The infer piece is all machine learning and deep learning to detect patterns, improve accuracy and automation. Finally, the act phase is all about taking actions in real-time. Once again, the cloud plays the central role as a “learning center” and the custodian of important data for the enterprise.
Given the sheer volume of data created, peer-to-peer networks will be utilized to lessen load on core network and share data locally. The challenge is huge in terms of network management and security. Programming becomes more data-centric, meaning less code and more math. As the processing power of the edge devices increases, the cost will come down drastically. I like his last statement that the entire world becomes the domain of IT meaning we will have consumer-oriented applications with enterprise-scale manageability.
This is exciting and scary. But whoever could have imagined the internet in the 1980s or the smartphone during the 1990s, let alone self-driving cars?
I was invited to participate in a panel called “IoT Analytics” last Thursday, March 23rd. This was organized for the IoT Global Council by Erick Schonfeld of Traction Technology Partner (New York). Besides me there were two other speakers: Brandon Cannaday, cofounder and chief product officer of Losant and Patrick Stuart, head of products at SkyCatch. For those of you not familiar with IoT, it stands for Internet of Things. There is another term called IIoT for Industrial Internet of Things. IoT has been in the lexicon for last few years signifying the era of “pervasive computing” where devices with an IP address can be everywhere – the freeze, microwave, thermostats, door knobs, cars, airplanes, electric motors, various sensors,…..constantly sending data. The phrases “connected home” or “connected car” are an upshot of the IoT phenomenon. However Gartner group showed IoT to be at the peak of the “hype cycle” couple of years back.
I emphasized on the “pieces of the puzzle” or the components of IoT Analytics – data ingestion at scale, handling streaming data pipeline, data curation and unification, and storing the results in a highly scalable NoSQL data store, as the steps before analytics can happen. Just dumping everything into a Hadoop data lake only addresses 5% of the problem (data ingestion). Transforming the data and curating it to make sense is a non-trivial step. Then I spoke about analytics which has several components – descriptive (what happened and why?), predictive (what is probably going to happen?), and prescriptive (what should I do about it?). Streaming analytics must filter, aggregate, enrich, and analyze high throughput of data from disparate sources to identify patterns, detect urgent situations (like a temperature spike in an engine), and automate immediate action in real time.
Patrick of SkyCatch showed how they are serving the construction industry in taking images (via drones) and accurately creating “earth maps” for self-driving bulldozers, thus saving human labor cost. Another example was taking images of actual progress in large construction sites and contrasting it against plan, to show offsets, thus detecting delays and taking corrective actions in time.
Brandon of Losant showed example of a large utility company in Australia that supplies high powered (expensive) pumps with sensors. By collecting data from the sensors and monitoring it centrally, they can identify problems and notify the maintenance teams for taking corrective actions. Previously they had to fly people around for maintenance and this new IoT Analytics has saved the company lots of cost. Both are startup companies in the IoT Analytics space and are tackling immediate issues in real time.
It was a good panel and I learnt a lot from my co-panelists.
I moderated a panel of 3 CIOs last Sunday at the Solix Empower conference on the subject of data-driven enterprise. The three CIO’s came from different industries. Marc Parmet of the TechPar group spent many years at Avery Dennison after stints at Apple and IBM. Sachin Mathur leads the IT innovations at Terex Corp., a large company supplying cranes and other heavy equipments. PK Agarwal, currently dean at Northeastern University, used to be the CIO for the Government of California. Here are some of the points covered:
I reminded the audience that we are at the fourth paradigm in science (as per the late Jim Gray). A thousand year ago, science was experimental, then few hundred years back science became theoretical (Newton’s law, Maxwell’s law..), fifty years ago, science became computational (simulation via a computer). Now the fourth paradigm is data-driven science where experiment, theory, and computation must be combined to one holistic discipline. Actually science hit the “big data” problem long before the commercial world.
Top level management is starting to understand that data is the oxygen, but they are yet to fully make their organizations data-driven. Just having a data warehouse with analytics and reporting does not make it data-driven, but they do see the value of predictive analytics and deep learning for competitive advantage.
While business-critical applications continue to run on-premise, newer, less critical apps such as collaboration and email (e.g. Lotus Notes) are moving to the public cloud. One said that they are evaluating migrating current Oracle ERP to a cloud version. Data security and reliability are critical needs. One panelist talked about not just private, public or hybrid cloud, but “scattered” cloud which will be highly distributed.
Out of the 3V’s of big data (volume, variety, and velocity), variety seems to be of higher need – images, pictures, videos combined with sensors deployed in manufacturing and factory automation. For industries such as retail and telcos, volume dominates. The velocity part will become more and more critical as streaming of these data in real-time will need fast ingestion and analysis-on-the-fly for timely decision making. This is the emerging world of IoT where devices with an IP address will be everywhere – individuals, connected homes, autonomous cars, connected factories. They will produce huge amounts of data volume. Cluster computing with Hadoop/Spark will be the most economical technology to deal with this load. Much work lies ahead.
There will be serious shortage of “big data” or “data science” skills, of the order of 4-5 million in next few years. Hence universities such as Northeastern is setting up new curriculum on data science. Today’s data scientist must have knowledge of the business, algorithms, comp. science, statistical modeling plus he/she must be good story teller. Unlike the past, it’s not just answering questions, but figuring out what questions to ask. Such skills will be at a premium as enterprises become more data-driven.
We discussed many other points. It was a fun panel.
I watched Larry Ellison’s keynotes at this week’s Oracle Open world conference in San Francisco. They are definitely serious in pushing their cloud offerings, even though they came in late. But Oracle claimed that they have been working on it for almost ten years. The big push is at all 3 levels – SaaS, PaaS, and IaaS. The infrastructure as a service claims faster and cheaper resources (computing, storage, and networking) to beat Amazon’s AWS. They make a good point on better security for the enterprises, given the risk of security breaches happening at greater frequency lately. One comment I have is that AWS is beyond just IaaS, they are into PaaS as well (e.g. Docker services, etc. for devops). Oracle’s big advantage is in offering SaaS for all their application suits – ERP, HCM and CRM (they call it CX as customer experience). This is not something AWS offers for the enterprise market, although apps like SalesForce and Workday are available. Microsoft has Dynamics as an ERP on their cloud.
I do agree that Oracle has an upper hand when it comes to database as a service. Larry showed performance numbers for AWS Redshift, Aurora, and DynamoDB compared to Oracle’s database (much faster). They do have a chance to beat AWS when it comes to serious enterprise-scale implementations, given their strong hold in that market. Most of these enterprises still run much of their systems on-premise. Oracle offers them an alternative to switch to the cloud version within their firewall. They also suggest the co-existence of both on-prem and cloud solutions. The total switch-over to cloud will take ten years or more, as the confidence and comfort level grows over time.
AWS has a ten year lead here and they have grown in scale and size. The current run rate for AWS is over $10B in revenue with hefty profit (over 50%). However, many clients complain about the high cost as you use more services of AWS. Microsoft Azure and Google’s cloud services are marching fast to catch up. Most of the new-age web-companies use AWS. Oracle is better off focusing on the enterprise market, their strong hold. Not to discount IBM here, who is pushing their Soft Layer cloud solutions to the enterprise customers. Mark Hurd of Oracle showed several examples of cloud deployment at large to medium size companies as well. One interesting presence at the Open World yesterday was the chief minister (like a state Governor) of the Indian state, Maharashtra (Mumbai being the big city there). He signed a deal with Oracle to help implement cloud solutions to make many cities into “smart” cities and also connecting 29000 villages digitally. This is a big win for Oracle and will set the stage for many other government outfits to follow suit.
I think more competition to AWS is welcome, as no one wants a single-vendor lock-in. Mark Hurd said that by 2020, cloud solutions will dominate the enterprise landscape. The analysts are skeptical on Oracle’s claim over AWS, but a focused Oracle on cloud is not to be taken lightly.
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While reading the latest issue of the Economist, I was reminded that August 25th. marks an important anniversary for two key events: 25 years back, on August 25, 1991, Linus Torvalds launched a new operating system called Linux and on the same day in 2006, Amazon under the leadership of Andy Jesse launched the beta version of Elastic Computing Cloud (EC2), the central piece of Amazon Web Services (AWS).
The two are very interlinked. Linux became the world’s most used piece of software of its type. Of course Linux usage soared due to backers like HP, Oracle, and IBM to combat the Windows force. Without open-source programs like Linux, cloud computing would not have happened. Currently 1500 developers contribute to each new version of Linux. AWS servers deploy Linux heavily. Being first to succeed on a large scale allowed both Linux and AWS to take advantage of the network effect, which makes popular products even more entrenched.
Here are some facts about AWS. It’s launch back in 2006 was extremely timely, just one year before the smartphones came about. Apple launched its iPhone in 2007 which ushered the app economy. AWS became the haven for start-ups making up nearly two-third of its customer base (estimated at 1 million). According to Gartner Group, the cloud computing market is at $205B in 2016, which is 6% of the world’s IT budget of $3.4 trillion. This number will grow to $240B next year. No wonder, Amazon is reaping the benefits – over past 12 months, AWS revenue reached $11B with a margin of over 50%. During the last quarter, AWS sales were 3 times more than the nearest competitor, Microsoft Azure. AWS has ten times more computing capacity than the next 14 cloud providers combined. We also saw the fate of Rackspace last week (acquired by a private equity firm). Other cloud computing providers like Microsoft Azure, Google Cloud, and IBM (acquired SoftLayer in 2013) are struggling to keep up with AWS.
The latest battleground in cloud computing is data. AWS offers Aurora and Redshift in that space. It also started a new services called Snowball, a suitcase-sized box of digital memory which can store mountains of data in the AWS cloud (interesting challenge to Box and Dropbox). IBM bought Truven Health Analytics which keeps data on 215m patients in the healthcare industry.
The Economist article said, “AWS could end up dominating the IT industry just as IBM’s System/360, a family of mainframe computers did until the 1980s.” I hope it’s not so and we need serious competition to AWS for customer’s benefits. Who wants a single-vendor “lock-in”? Microsoft’s Azure seems to be moving fast. Let us hope IBM, Google, and Oracle move very aggressively offering equivalent or better alternatives to Amazon cloud services.
On this first day of August 2016, I saw that the top most-valued companies are tech. companies, and the fifth one is almost there. Here is the list.
Apple ($appl): $566 billion
Alphabet ($goog): $562B
Microsoft ($msft): $433B
Amazon ($amzn): $365B
Exxon Mobile ($xom): $356B
Facebook ($fb): $353B
The big move is Amazon’s beating Exxon Mobile (used to be number 1 for many years) to the fourth spot. The switch came after Amazon posted its fifth straight quarter of profits last week as the oil giant’s profits tumbled 59 percent during the same rough period. If Exxon continues its drop, then Facebook will beat it in days.
This is quite remarkable! Other than Microsoft and Apple, the other 3 companies are much younger, Facebook being the youngest one. Their rapid rise is due to the growth of the Internet with its associated areas of search, e-commerce, and social networking. Interestingly Amazon survived the dot-com bust of the early 2000-2001 time unlike Yahoo, AOL, etc. Contrast this to the $4.8B valuation of Yahoo’s core business acquired by Verizon last week! Also, the fastest growing and most profitable of Amazon’s 3 businesses (Books, any commercial items, and AWS) is the cloud infrastructure piece called AWS (Amazon Web Services) with a run-rate of $10B this year. This is way ahead of Microsoft’s Azure cloud or Google’s cloud solutions.
The importance of cloud is obvious as Oracle just paid $9.3B last week to acquire Netsuite, a company that was funded by Larry Ellison. With a 40% ownership of Netsuite, he gets a hefty $3.5B from this deal. Paradoxically, Amazon lead the way to cloud computing – not IBM, not HP, not EMC/VMWare, and not Microsoft or Google. So no wonder, Amazon is reaping the benefits!
This is big news this morning – Microsoft buying LinkedIn at $26.2B cash. LinkedIn’s stock is soaring by 47% as we write while Microsoft stock is falling! This is one of the biggest acquisitions since Dell’s acquiring EMC few months back. So how does this work?
Well, Satya Nadella explains the importance of a professional network in their scheme of cloud offerings, from Office360 to Dynamics. Imagine walking to a meeting and viewing all the attendees info from their LinkedIn profiles. He said, “It helps us differentiate our CRM product with social selling. It helps us take Dynamics [Microsoft’s suite of business management software] into new spaces like human capital management with recruiting, and learning, and talent management.”
LinkedIn had a bad quarter and the stock was going south by as much as 40%. So there was some anxiety on where the company was heading in future. They saw this opportunity to be part of a larger company and the board quickly jumped into this offer, as it seems. As far as the synergy is concerned, time will tell how they integrate and make it look like a seamless cloud offering. Reid Hoffman, chairman of LinkedIn will stay as an advisor, but his new role is yet to be defined. Jeff Weiner will continue to stay as CEO reporting to Nadella.
This certainly strengthens Microsoft’s cloud presence and adds value to the Dynamics business more than the Office360 side. But use of Office360 suite in creating and managing documents/profiles may add to the growth of that business. If they can make it a success, Satya Nedella’s leadership will have a new feather in his cap.