SpaceCurve has been pretty silent since its inception, presumably because it’s busy building out a product that has to convince businesses to build applications or run analytics in ways they might not have even seriously considered before. By digesting myriad streams of data from mobile devices, sensors, social media and anything else spitting out data about time or places, the company claims on its website it can ”tie people or entities to a precise point in time and space, immediately discover the social and semantic relationships between them, and deliver this  real-time intelligence instantly to identify new opportunities, and support better decisions and more profitable actions.”

Digging through the marketing lingo, one can spot the opportunities SpaceCurve could help solve if it works as advertised. Rather than just knowing where someone or something is at any given time, you could know how they’re related to the other things around them and perhaps figure out who’s who among a sea of anonymous devices. Marketers trying to master geo-targeting might like these capabilities, as might intelligence agencies trying to, I don’t know, comb through metadata from millions of call records.

SpaceCurve closed a $3.5. million Series A round in August 2012 and has raised $15.2 $17.3 million overall since it was founded in 2009.

Feature image courtesy of Shutterstock user twobee.

Disclosure: Reed Elsevier, the parent company of science publisher Elsevier, is an investor in Giga Omni Media, the company that publishes GigaOM.

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Every tech vendor on the planet is now officially targeting the Chief Marketing Officer with IT products and otherwise doing everything in its power to make it easy for marketing departments to buy its stuff. That must be kind of hard for the person who was the traditional gatekeeper for the IT strategy and budget.

Now IBM is getting in on the act, offering a new marketplace of 100 SaaS applications divvied up into categories for different cadres of IT buyers. And (IBM being IBM) that list is extensive, leading off with the CMO but also including sales and eCommerce leaders; customer care and support executives; Chief Procurement Officers; Chief Supply Chain Officers; General Counsel; Chief Financial Officers; Chief Human Resource Officers. Oh yes, and then Chief Information Officers.

This list speaks to a certain amount of title inflation: I was surprised not to see Chief Innovation Officer, one of the newer C-level buzzword bingo titles on that list, but give it time.

Target: Chief Marketing Officer

IBM’s move to make its SaaS apps more easily found and purchased by CMOs comes a few weeks after Salesforce.com dropped a cool $2.5 billion on ExactTarget, an email marketing company that also focuses on marketing execs. Just this morning, SendGrid, which traditionally sells to developers of web applications, launched an email tool for marketing pros that will compete with MailChimp. Marketo  last week launched its first product since its IPO, which uses machine learning to tailor email pitches according to customer activity.

And don’t forget that Oracle bought Eloqua, a marketing automation company, for nearly $900 million in December. NetSuite got into marketing automation early, having purchased a couple professional services companies, Retail Anywhere, Order Motion, and Element Fusion over the past few years and is now touting a big customer win with Williams Sonoma. Clearly there’s a trend here.

Is the CMO really in charge of IT? Should he or she be?

But all this “buying-power-goes-to-the-CMO” talk, which we covered back in September, still smacks of a fad to me. Someone at the customer organization needs to have a holistic picture of what’s being bought and deployed if only to make sure that the company gets the best volume discount for any SaaS service used.  That person may not be the CIO but it better be someone with a firm grasp not only of technology per se, but a working knowledge of service level agreements and compliance issues. I doubt that most CMOs want to take that on, but I could be wrong and I’m sure you’ll let me know.

At the MIT CIO Symposium last month, Michael Relich, EVP and CIO of Guess Inc., said that in a perfect universe “CMOs and CIOs should be best friends,” because CMOs need data and to get it they need point-of-sale and e-commerce systems that are all about IT. But when asked if CMOs will get more IT budget than CIOs, Relich said: “Over my dead body.”

And that brings me to Structure this week where GigaOM will host a panel by CIOs on their role in the modern IT organization. I’ll be sure to ask them what they think of this marketing automation extravaganza and the purported rise of the CMO.

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Here’s Olson’s explanation from his post:

We’re building a company that we expect to stay independent and to lead the market for many years to come. That will demand relentless focus on operational excellence and on the technology and solutions that our customers need. The combination is, at our present scale, two jobs, not one.

Tom led Arcsight through its IPO to industry leadership in mission-critical, bet-the-business security. He knows the enterprise. He’s a been-there, done-that executive. He’s run very successful enterprise software companies at global scale.

Tom’s appointment as CEO allows me to concentrate my time with key constituents: Our product and engineering teams, our partners, our sales force, our customer-facing technical teams and – most importantly – our customers themselves. He and I have spent considerable time together over the last several months, building trust in both directions and planning for a smooth transition. Cloudera is a better company, today and for the long term, with the two of us working together.

It’s kind of ironic that Olson is stepping down, considering he was always considered the seasoned enterprise executive of a founding team custom-built to grow into the company that has Cloudera now become. It was the first company to make a living selling a commercial version of the Apache Hadoop big data platform, and it’s still the biggest. Cloudera has raised $141 million in venture capital since launching in 2009, is doing about $100 million in annual revenue and has well more than 300 employees.

Before founding Cloudera along with Amr Awadallah, Jeff Hammerbacher and Christophe Bisciglia, Olson was CEO of Sleepycat Software. Sleepycat was the creator and primary developer of the BerkeleyDB database technology, and Oracle bought the company in 2006. However, Olson told me during an interview on Tuesday afternoon, Cloudera is “vastly larger” than Sleepycat on every metric — including headcount and revenue.

That scale of operations, Olson, said, has necessarily forced him to put more energy into company management and short-term oversight rather than working with customers and on long-term product strategy. With Reilly on board, Cloudera has someone who’s managed companies at this scale and has the operational aspects down pat.

If he has any hard feelings about the change in leadership, Olson isn’t letting on publicly. ”We believe we’re building one for the ages here,” he said. “… [Tom and I] got to know each other very well, obviously, otherwise I’d never be able to hand my baby over.”

Update: This post was updated at 3:05 p.m. to reflect comments from Mike Olson.

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All of this is key to its industrial intent vision, where connected sensors on machines talk to the cloud and companies harness the power of industrial data in real time to automate industrial processes. GE has estimated that connecting devices to the “industrial internet” could boost global GDP to the tune of $10 trillion to $15 trillion by 2030.

GE’s new data and cloud products

GE is building big data software called the Historian that uses Hadoop to manage time-series data to help industrial customers track their rising industrial data. GE’s Bill Ruh, VP of the Global Software Center, pointed out that industrial data is growing at twice the rate of other types of data. For example, GE generates about 5 terabytes of data a day in its labs.

The Hadoop part of the software allows the data to scale across multiple nodes, while the time-series component helps manage the influx of tiny pieces of data that comes in almost constantly. Time-series data isn’t huge, but it’s always coming in, adding up to millions and billions of records over a relatively short amount of time depending on how often it is collected.

The partnership with Amazon (Amazon CTO Werner Vogels attended the event, and he’ll also speak at our Structure event tomorrow in San Francisco) means the cloud giant will be the first cloud provider on which GE will deploy its industrial internet platform. It’s not clear yet, if Amazon will use GE’s Hadoop software in its cloud or if there are just some API links being built.

Update: Vogels and Ruh say that the relationship means that customers can ship and store their data designed for the GE Predictivy software and the Historian platform to Amazon’s cloud. So customers can do it on-premise and/or in the cloud. Pivotal will help build some of the software connectors that will make it possible for customers to use this data where they want without concerning themselves about where it is headed.

In some ways the demonstrations that GE showed off, are taking direct design strategies from consumer applications such as Facebook, and its software options, called Predictivity are designed to connect the data coming in from machines to people in user-friendly ways.

The goal behind all of these products is to bring the internet of things back to the enterprise realm. It’s nice to connect your home, but when you can connect power plants you can drive a lot more results in terms of energy efficiency and even cost savings. And because the money is there, we’ll see a lot of interesting software to solve the problems associated with managing, analyzing and running predictions against data.

“Now for the first time I think we’re going to see innovation coming out of the industrial space and not just the IT space, “said Paul Maritz, the CEO of Pivotal, a company that GE recently invested $105 million in.

I’ll update the story with more information after the event.

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Netflix just posted the tool, which provides a birds-eye view of its own cloud landscape (cloudscape?), onto its Github page, the last of a series of open-sourced Netflix goodies to go up.

Asked why Netflix went its own way with an AWS monitoring tool, Ariel Tseitlin, director of cloud solutions for Netflix responded by email to say:

“We built Ice to to give us deep insight into our cloud usage that we couldn’t find with any of Amazon’s or 3rd party offerings.  It gives us the visibility and operational support to manage our mature complex environment and we hope that the rest of the cloud community can benefit from it.”

Like the other AWS checkers, Netflix Ice relies on data supplied by Amazon’s own APIs. With those stats in hand, it tracks usage by accounts; regions; type of service (EC2, S3, EBS); and usage types by instance size. It also tracks whether you use on-demand, reserved or other instance types, the pricing of which varies. Given the sheer number of services and options AWS offers, it’s clear that tracking all of that is a handful, especially for a large organization.

Ice is a Grails project consisting of a processor, a reader and a UI. The processor takes in the Amazon billing file and makes it available to the reader, which renders it to the UI. The UI queries the reader and renders interactive graphs and tables for the browser.

Netflix has years of institutional knowledge on this topic, relying as it does on Amazon infrastructure.  As the blog post states:

Netflix is a highly decentralized environment where each service team decides how many resources their services need.  The elastic nature of the cloud make capacity planning less crucial and teams can simply add resources as needed.  Viewing the broad picture of cloud resource usage becomes more difficult in such an environment.  To address both needs, Netflix created Ice.

So, if you’re a big AWS shop and would really like to get a handle on just what all your developers have running (or deployed and not running) on AWS cloud, you might want to check Ice out.

Los Gatos, Calif.-based Netflix is really trying to propagate a range of the tools and utilities it uses to make sure its streaming media empire runs well on AWS. Most recently, it posted Isthmus, which vows to manage elastic load balancing across AWS regions. Isthmus, in turn, builds on Zuul, another tool that acts as a gatekeeper between Netflix’ own API and other Netflix services and AWS Elastic Load Balancer that routes video to users. The goal is to prevent meltdowns like the one that hit Netflix last Christmas Eve. 

Netflix, as its cloud guru Adrian Cockroft said at an open source open house it hosted a few months ago, really wants outside companies to deploy its components and, it’s very interested in getting other, non AWS cloud vendors, to deploy these tools as well. One can only imagine why. Cockcroft will be joining us this week at Structure in San Francisco so come by to see what he has to say.

Update: Now that Amazon and Netflix have joined a half dozen or more third-party AWS monitoring tools in the pool, I’d  love to hear from some of the competitors in this space — folks, what does Netflix’ move mean to you and your AWS monitoring tools? Use comments to respond.

This story was updated at 4 p.m. PDT with additional competitors in this space and a request for comments.

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The study, entitled “Mapping the global Twitter heartbeat,” was published in the university’s peer-reviewed journal First Monday in May, and used what is known as the Twitter “Decahose” — which is made up of one-tenth of all the messages sent across the network. Access to the data was provided by Gnip, one of the companies that is licensed to sell Twitter’s full firehose, as part of a demonstration project with computer maker Silicon Graphics called “Twitter Heartbeat.”

For that demonstration, the researchers used the Decahose — which streamed more than 1.5 billion tweets from 71 million unique users during the period from October 23 to November 30 of 2012, an average of 38 million tweets a day — to show a real-time map of global discussion about topics such as Hurricane Sandy and the U.S. federal election. As part of that project, the team created one of the largest databases of global tweets with geographic data included, based both on GPS data and user profiles.

In addition to some interesting data about where most geo-located tweets come from (Jakarta in Indonesia and New York City were two of the top locations), the study looked at what the Twitter data shows about the way that social networks have changed the way we communicate. In many ways, the researchers said, networks like Twitter have “created a world in which a person may speak to another on the other side of the planet with just a few millisecond delay, effectively removing the geographic barrier.”

“Users on Twitter communicate with others both near them and half a world away, illustrating that the role of physical proximity in communication seems to be reduced in the era of social media.”

These maps of real-time connections produced for the Illinois study reminded me of similar maps created with Facebook data, such as the one that Facebook intern Paul Butler produced in 2010 (which appears below) — or the one that data researcher Pete Warden created by scraping Facebook user profiles, a fascinating map of connections that he later had to delete after the social network threatened to sue him for breaching its terms of service.

Although Twitter CEO Dick Costolo likes to talk about the service as the “pulse of the planet,” it’s worth noting that most of the world’s population still doesn’t tweet — and even most of those who do aren’t using it all the time: Twitter has about 550 million users, or about eight percent of the world’s population, but the top five percent account for almost half of all tweets sent. Of the sample the U of Illinois researchers looked at, one quarter tweeted only once.

In addition, the study notes that only 8 percent of all users had location data available. About one percent of all users surveyed accounted for more than two-thirds of all geo-referenced tweets, showing that geo-located are created by what the researchers called “an even more extreme subset of users” than overall tweets. They noted that studies relying on these tweets alone would have a “skewed view of the Twitterverse, especially over short periods of time.”

That said, however, it’s fascinating to see tangible evidence of how social networks like Twitter can help to erase geographical barriers and connect users around the globe in real time.

Post and thumbnail photos courtesy of Flickr user Dunechaser

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Researchers at the University of Illinois at Urbana-Champaign ended up deploying Pica8′s P-3290 switches because they support OpenFlow and because they boast 1-gigabit Ethernet. They could have gone with, say, Hewlett-Packard or NoviFlow, but they heard others saying positive things about Pica8, said Brighten Godfrey, an assistant professor at the university.

Godfrey and his colleagues at the university’s Ocean Cluster for Experimental Architectures in Networks have been running an application they call VeriFlow in their network to spot how a configuration change might affect the security of the rest of the network or violate existing policies, so an administrator can centrally keep an eye on these things down to the millisecond.

They have also been testing out a novel network architecture called Jellyfish, which lets administrators add switches into their networks quickly and basically at random. It might sound like that behavior could bring on capacity issues, but Godfrey said the method turns out to be 25 percent to 40 percent more efficient with the same hardware than with a legacy design such as a spanning tree.

“That kind of thing would have been pretty difficult in traditional hardware and is quite feasible with OpenFlow,” Godfrey said.

Finally, the switches are in place for experiments with migrating whole virtual networks to different physical gear without causing service disruptions.

When scalability calls, network admins shouldn’t be faulted for wanting to throw hardware at the problem, and these sorts of applications could help the cause. As OpenFlow makes these applications possible, it’s worth asking why it’s not yet ubiquitous in network gear. Cisco and Juniper have been less taking gradual steps at providing customers with small steps in the direction software-defined networking (SDN).

The subject is hot, and it’s one that could well come up during a conversation on SDN with Juniper’s Bob Mulgia at our Structure conference in San Francisco on Wednesday.

It’s unclear if existing Cisco or Juniper customers will defect and jump at switches that can be programmable with a common protocol and controlled on commodity servers by way of SDN controllers from a number of emerging vendors. But with more of these cases emerging, the shift looks increasingly palpable.

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They were app developers; the transformation into systems engineers was just a necessity of growing the business. A website that looked pretty and worked smoothly was little more than veneer if the real product — the AWS virtual servers running Heroku’s customers’ applications under the covers of the hip samurai-themed web service — didn’t work. At one point, Lindenbaum joked during a recent call, Heroku had to do a UX refresh “and we literally didn’t have anyone in the company who could build web apps anymore.”

After leaving Heroku and ultimately its parent company Salesforce.com , Lindenbaum is back in the public eye with a new effort called Heavybit Industries that aims to save other startups from Heroku’s early growing pains. The idea came after so many fledgling companies came to Heroku looking for help, and after Lindenbaum got personally involved with some as an adviser or investor. He eventually realized that there’s a lot of institutional knowledge out there about how to build business that serve developers, but there’s also a lot of duplicated effort because the people starting these businesses often don’t know their peers exist, much less what they’re up to.

How Heavybit works

Heavybit is like a co-working-space-meets-incubator-meets fraternity, and Lindenbaum has recruited some of the biggest names in venture capital, application development and developer-focused startups to make sure Heavybit delivers on its promise. It works like this: Companies that have raised some money, gained some traction among developers, and now have to deal with the difficult problems of scaling their code or monetizing their business come to Heavybit. Once accepted, they’re in the “active period” for nine months, which includes a curriculum of weekly talks on technology or entrepreneurship; office hours with experts and investors; and meeting/work space in a building in San Francisco’s SOMA neighborhood.

James Lindenbaum at Structure 2009. (c) Pinar Ozger

Membership in Heavybit is in exchange for equity, and the community has space for between 10 to 15 companies at a time, Lindenbaum said (although it’s really a “membership for life” situation). The first batch of startups includes some more-established ones — Zencoder, Stripe, PagerDuty and Meteor — that will serve as mentors as well as receive mentorship. Other inaugural Heavybit members include Treasure Data, Kodowa, Iron.io, CircleCi, CloudConnect, Keen IO, Codenvy and Backlift.

Early Heavybit expert advisers include Derek Collison (Apcera/VMware/Google), Adam Gross (CloudConnect/Salesforce.com), Jesse Robbins (Opscode/Amazon), Javier Soltero (Acompli/VMware/Hyperic), and Lindenbaum’s Heroku co-founders Adam Wiggins and Orion Henry. Among  Heavybit’s early investor partners are Ping Li (Accel Partners), Chris Sacca (Lowercase Capital), John Connors (Ignition Partners) and Matt Ocko (Data Collective).

Bringing “bad-ass” engineers back from mobile apps

One of Lindenbaum’s goals when putting together the advisers — and one of his continuing goals with Heavybit — is to to put member companies in touch with people who really understand the business and architectural complexities of distributed, multitenant applications. “The reason [these developer-focused] products are so great is because they’re built … by app developers for app developers,” Lindenbaum said. But, like the Heroku team early on, the founders aren’t always skilled in building systems designed to scale.

“The scale curve is much steeper for these companies,” he explained, because the way it usually works is these businesses attract customers who also have their own customers to serve. So rather than handling data for one company, they might be handling data for 20 of that company’s clients, as well.

In order to put his companies in touch with the best of the best of distributed systems engineers, though, Lindenbaum first has to walk those guys back from the Instagram edge. Once you prove yourself at a place like Google or Facebook, Lindenbaum said, “[E]veryone thinks you’re a bad ass. As soon as you say you’re going to build a thing, VCs line up to give you money.”

Unfortunately, he added, many of these people are chasing the past rather than future, trying to cash in their lottery tickets on building the next photo-sharing app rather than on the hairy enterprise-grade systems problems where their skills would really be valuable.

But he has a plan to bring them back to the enterprise side. He intends to push the message of how hard these problems are and how much the cloud services and developer-focused products industries are becoming analogous to traditional heavy industries in terms of the complex but mature supply chains involved.

Essentially, he wants to do the “Got Milk?” ads for the cloud services industry, educating the market so the individual companies don’t have to. It’ll be like a trade association, he joked, “only the non-evil version of that.” Once you shine a light on the difficulty of the problems, Lindenbaum said, the really good engineers come running back to solve them.

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The new SendGrid Marketing Email service, launching Tuesday, will rely on the same infrastructure SendGrid already uses for the 8 billion transactional messages it sends monthly. But, unlike its transactional email service, this new offering targets non-techie marketing people, not developers.

A company’s marketing staff can opt for one of several newsletter templates, “build” the content using a drag-and-drop interface, and create mailing lists. According to a statement about the new service, once the newsletter is ready to roll:

… marketers can distribute to their entire list in seconds and view campaign performance in real-time via SendGrid’s newsletter analytics dashboard, which provides insight into delivery rates, opens, clicks, click-through rates, unsubscribe requests and more.  Similar to SendGrid’s transactional email service, technical users can leverage an API for the marketing email service and forgo the online interface.

SendGrid’s pitch is that it will all do this for less than competitors like MailChimp or Constant Contact because it will charge based on how much mail is sent and not on the size of the subscriber list.

Given that tech vendors see Chief Marketing Officers and their minions controlling more of the IT budget, it makes sense to build tools tailored for that constituency. That trend is also driving quite a bit of M&A activity as evidenced by Salesforce.com’s recent $2.5 billion buyout of ExactTarget early this month.

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