Hewlett Packard Enterprise (HPE) held its annual Discover conference in Las Vegas last week. It has made a sizable commitment to Internet of Things (IoT) and the Edge—areas central to my writing for the past few years. I am floating a number of ideas looking for feedback as I travel, and I’ll bounce some of those here later.
There is so much I learned last week beyond even what I wrote Monday about the new Edgeline computer. Perhaps the best place to start is with my latest discussion with Lin Nease, Chief Technologist IoT at HPE. This was a continuation of a discussion we began in Madrid last November and resumed at Industry of Things World in San Diego in February.
HPE’s power of compute at the Edge fascinates me. Even though my being in Las Vegas precluded being in Boston for LiveWorx, ThingWorx came up in many conversations at Discover. Nease said that ThingWorx (product and division of PTC) has been a good partner. Back to compute power at the edge Nease mentioned this power combined with TSN—Time Sensitive Networking, a new extension of Ethernet promulgated by IEEE.
Indeed, there is sufficient power in Edgeline that an enterprising developer could, for instance, accomplish the software defined DCS that seems to be the dream of some of the engineers at ExxonMobil and the Open Process Automation folks. Anyone out there have time and money?
Speaking of Edge, evidently the enterprise IT bloggers I hung out with during the event try to avoid the term. CEO Antonio Neri had said, “Edge is everything outside the data center.” In the blogger round table that I posted Monday, blogger Alastair Cooke noted, “Gary, we consider everything you do as edge.” Back to Neri who stated 94% of data is wasted; 75% of data comes from the edge.
Following are some points I gleaned from a session called “Harness the Power of Digital Platforms”:
HPE is a huge fan of open source & open platforms
Digital natives build platforms-e.g. Uber, Google, Amazon, etc.
An internal team built an open API platform to solve a problem in supply chain
Biggest problem was selling the system internally so that people would actually use the system (never seen that before—said no one anywhere)
Traditional—>Digital; everything is a frictionless stream of data
Platform always on, always looking for exceptions — sense/respond
HPE has an OEM Solutions group. Following are some points from a session discussing them:
OEM Solutions can be Embedded, Integrated, Private Label
Everything as a Service — Green Lake is the service offering that OEMs can resell the service
Shift to software defined
From storage to flash
Example—Konica Minolta embedded an Edgeline computing device in a printer called workplace hub that makes it easier to set up and install a new remote office
HPE has momentum in IoT and edge devices—and an organization supporting manufacturing.
I attended the Hewlett Packard Enterprise (HPE) Discover conference as the IoT blogger. It is a different program from that of the press. More blog posts coming when I get a chance to catch up. Actually this week I’m in Florida at yet another conference. And I have things from two weeks ago. Jeffrey Powers with Geekazine live streamed and recorded the blogger / influencer sessions. This video shows the blogger roundtable that I participated in. It begins at 3:50 into the video.
Antonio Neri, CEO and President of Hewlett Packard Enterprise (HPE), used the phrase “Data is the new currency, memory the new gold” in his keynote to the company’s annual US customer conference Discover in Las Vegas in June. Just one of the many places I’ve been lately.
If you haven’t planned for data in your machine and process control designs, you had best begin.The race for improved operations performance is on now.
We talk often of “edge” in the world of Internet of Things or Industrial Internet of Things. The edge has many definitions, but it can be defined as any place outside a data center. PLCs, for example, not only perform logic control, but they also aggregate data from perhaps thousands of sensors. SCADA devices and industrial computers also collect and channel data from a few to many sensors and data sources.
Business operations managers are hungry for this data to feed their information systems that in turn fuel their business decisions. Data in context is information. Information correctly presented to decision makers leads to better, faster decisions—and a competitive edge.
This search for competitive edge has moved me from an emphasis on control and automation (something we still need to do well) to Industrial Internet of Things. The IIot is taken by many as a similar strategy to Industrie 4.0 or Smart Manufacturing or whatever different countries call their strategies. This means I’m looking at a new generation of edge computing, enhance networking standards, human-centered design for mobile visualization of data, and even Augmented Reality (AR) and Artificial Intelligence (AI). These are not far-out technologies any longer. They are here and applications are growing.
Neri talked about the future as edge-centric, cloud-enabled, data-driven. He said the edge is where the action is, where the data is created. HPE is going to invest $4 billion in the intelligent edge over the next 4 years.
The company announced a new edge computing device with enterprise grade computing power (far beyond a PC) plus up to 48TB (yes that’s Tera not Giga) of memory. Oh, and it also comes in an environmentally hardened package. The CTO of Murphy Oil talked of using these on off-shore oil rigs.
Texmark Chemicals is a Houston, Texas based petrochemical refiner. I had several opportunities to talk with them about their IoT projects. They orchestrated an ecosystem of 12 suppliers initially to instrument critical pumps in their process in order to achieve predictive maintenance. This potentially saves the company millions of dollars by avoiding catastrophic failure. (Note: I previously wrote about the Texmark use case here–and expect more to come.)
Back to the announcement from HPE about the new edge product—a family of edge-to-cloud solutions enabled by HPE Edgeline Converged Edge Systems to help organizations simplify their hybrid IT environment. By running the same enterprise applications at the edge, in data centers and in the cloud, the solutions allow organizations to more efficiently capitalize on the vast amounts of data created in remote and distributed locations like factories, oil rigs or energy grids.
(Dr. Tom Bradicich wrote a blog post you can find here.)
HPE’s new edge-to-cloud solutions operate unmodified enterprise software from partners Citrix, GE Digital, Microsoft, PTC, SAP and SparkCognition, both on HPE Edgeline Converged Edge Systems – rugged, compact systems delivering immediate insight from data at the edge – and on data center and cloud platforms. This capability enables customers to harness the value of the data generated at the edge to increase operational efficiency, create new customer experiences and introduce new revenue streams. At the same time, edge-to-cloud solutions enabled by HPE Edgeline simplify the management of the hybrid IT environment, as the same application and management software can be used from edge to cloud.
“The edge is increasingly becoming a centerpiece of the digital enterprise where things and people generate and act on massive amounts of data,” said Dr. Tom Bradicich, Vice President and General Manager, IoT and Converged Edge Systems, HPE. “Our edge-to-cloud solutions help bring enterprise-class IT capabilities from the data center to the edge. This reduces software and IT administration costs, while accelerating insight and control across the organization and supply chain.”
HPE also announced the HPE Edgeline Extended Storage Adapter option kit, adding up to 48 terabytes of software-defined storage to HPE Edgeline Converged Edge Systems. This enhancement enables storage-intensive use cases like artificial intelligence (AI), video analytics or databases at the edge, while leveraging industry-standard storage management tools such as Microsoft Storage Spaces, HPE StoreVirtual VSA, and VMware vSAN.
I went from Germany to Las Vegas and the time change screwed with my posting schedule. So…I am finally finishing up my Hannover Messe reporting before I begin with my recent trip.
My last post detailed the first round of briefings with Hewlett Packard Enterprise. Today I’ll finish up.
But first, a digression.
Misinformation about what exactly OPC UA is continues to circulate within the industry. I had at least three conversations where people referred to OPC as proprietary. Plus OPC and MQTT are mistakenly considered competitive rather than complementary. OPC Foundation still has some evangelizing to accomplish.
A few years ago it appeared that major automation vendors were ignoring OPC and its interoperability tending toward self-encased solutions. In fact, I got dissed by some dude on YouTube for a report I did on that subject.
Time has passed. More and more people and companies recognize the value of interoperability and OPC UA. No doubt the PubSub helps in some cases. And without a doubt the combination of OPC UA and TSN is enticing to many.
HPE has devised an application dubbed “Remote Visual Guidance.” It began with an eLearning application HPE MyRoom. Integrated with a hard hat, a camera, and glasses that project an image to the user, the system enables remote support from an expert who may not be able to fly to the site. Imagine working in a remote location such as an offshore oil rig where flying in an expert is both dangerous and expensive, for example. The system comes in three versions—wearable say integrated with a hard hat, smart phone app, or tablet app. Therefore, the three versions are No hands, 1 hand, and 2 hands). Try this for a potential use case for a value add from an OEM. The OEM bundles the app with its machine. This gives the customer direct contact with remote expert for the cost of perhaps a service contract.
I had a good conversation with HPE’s Christian Reichenbach on Blockchain technology. I believe this technology is quickly moving past hype into something we can use. The concepts of trusted transaction and ledger have immediate appeal for industries such as pharma manufacturing. We can think of many more.
Reichenbach identifies three waves of blockchain.
Wave One is personal exemplified by crypto currency—the Bitcoin that garners most of the press
Wave Two came with Enterprise to Enterprise transactions. For example, he pointed to the vision system QA demo at the HPE stand. It uses blockchain to send QA report as a secure, trusted transaction that includes a record.
Wave Three includes Things to Things. This means systems around products leading to systems of systems thinking. Things become autonomous actors. They contract with each other with no middle man. It includes ledger systems. Let’s take the example of an HPE Edge Gateway plus Etherium (an HPE partner). Perhaps it’s the same concept as loyalty card scanning and giving you value for using it. Let’s look at a car. Currently there are lots of sensors but no marketplace to exploit all that data. Say we take Edgeline device connected to CANbus of the car. Then, say, connect to the rain sensor or a sensor in the shock absorber. Previously the end user gave data away for free, but now maybe the car makes a smart contract with weather channel or Waze and sells the data.
One last item I gleaned from the Microsoft booth. HPE has a starter kit to help users easily connect devices to the cloud using HPE Edgeline, Softing (OPC UA kit), and Microsoft Azure.
Overall analysis from HPE visit at Hannover was that IoT has matured in a sense from a department with a product to infusing into the entire manufacturing product and service portfolio.
Much of the interesting activity in the Industrial Internet of Things (IIoT) space lately happens at the edge of the network. IT companies such as Dell Technologies and Hewlett Packard Enterprise have built upon their core technologies to develop powerful edge computing devices. Recently Bedrock Automation and Opto 22 on the OT side have also built interesting edge devices.
I’ve long maintained that all this technology—from intelligent sensing to cloud databases—means little without ways to make sense of the data. One company I rarely hear from is FogHorn Systems. This developer of edge intelligence software has recently been quite active on the partnership front. One announcement regards Wind River and the other Google.
FogHorn and Wind River (an Intel company) have teamed to integrate FogHorn’s Lightning edge analytics and machine learning platform with Wind River’s software, including Wind River Helix Device Cloud, Wind River Titanium Control, and Wind River Linux. This offering is said to accelerate harnessing the power of IIoT data. Specifically, FogHorn enables organizations to place data analytics and machine learning as close to the data source as possible; Wind River provides the technology to support manageability of edge devices across their lifecycle, virtualization for workload consolidation, and software portability via containerization.
“Wind River’s collaboration with FogHorn will solve two big challenges in Industrial IoT today, getting analytics and machine learning close to the devices generating the data, and managing thousands to hundreds of thousands of endpoints across their product lifecycle,” said Michael Krutz, Chief Product Officer at Wind River. “We’re very excited about this integrated solution, and the significant value it will deliver to our joint customers globally.”
FogHorn’s Lightning product portfolio embeds edge intelligence directly into small-footprint IoT devices. By enabling data processing at or near the source of sensor data, FogHorn eliminates the need to send terabytes of data to the cloud for processing.
“Large organizations with complex, multi-site IoT deployments are faced with the challenge of not only pushing advanced analytics and machine learning close to the source of the data, but also the provisioning and maintenance of a high volume and variety of edge devices,” said Kevin Duffy, VP of Business Development at FogHorn. “FogHorn and Wind River together deliver the industry’s most comprehensive solution to addressing both sides of this complex IoT device equation.”
Meanwhile, FogHorn Systems also announced a collaboration with Google Cloud IoT Core to simplify the deployment and maximize the business impact of Industrial IoT (IIoT) applications.
The companies have teamed up to integrate Lightning edge analytics and machine learning platform with Cloud IoT Core.
“Cloud IoT Core simply and securely brings the power of Google Cloud’s world-class data infrastructure capabilities to the IIoT market,” said Antony Passemard, Head of IoT Product Management at Google Cloud. “By combining industry-leading edge intelligence from FogHorn, we’ve created a fully-integrated edge and cloud solution that maximizes the insights gained from every IoT device. We think it’s a very powerful combination at exactly the right time.”
Device data captured by Cloud IoT Core gets published to Cloud Pub/Sub for downstream analytics. Businesses can conduct ad hoc analysis using Google BigQuery, run advanced analytics, and apply machine learning with Cloud Machine Learning Engine, or visualize IoT data results with rich reports and dashboards in Google Data Studio.
“Our integration with Google Cloud harmonizes the workload and creates new efficiencies from the edge to the cloud across a range of dimensions,” said David King, CEO at FogHorn. “This approach simplifies the rollout of innovative, outcome-based IIoT initiatives to improve organizations’ competitive edge globally, and we are thrilled to bring this collaboration to market with Google Cloud.”