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VMware expands European Cloud

VMware has unveiled an expanded portfolio of cloud services and made VMware Cloud on Amazon Web Services (AWS) available in Europe, bringing the service closer to South African companies.

The announcements are key to the VMware strategy of enabling customers to work seamlessly with, and better manage, hybrid clouds. This will in turn provide local VMware users with the opportunity to marry multiple clouds, manage them from a single interface, develop for them, derive quantifiable analytics on use and behaviour, and leverage more effective cost analysis.

VMware and AWS will also enable system integrator and system outsourcer (SISO) partners, managed service providers, and solutions providers to grow their cloud business and help their customers realise the full benefits of hybrid cloud.

AWS does not yet have datacentres or local cloud infrastructure in South Africa. However, according to Ian Jansen van Rensburg, senior systems engineering manager at VMware Sub-Saharan Africa, the VMware Cloud Provider Programme partners have many customers that make use of AWS together with VMware. As long as they are not forced by legislation to keep the data inside the boundaries of South Africa, they are able to use AWS points pf presence in South Africa.

“Customers are focused on digital transformation and that is a business decision on how they leverage cloud,” states Jansen van Rensburg. “The needs of applications are driving these cloud decisions, as customers need to support both new and existing applications, which is conversely also driving massive cloud adoption, even locally.

“VMware Cloud is unique in the sense that you can develop any type of application and deliver these applications to any cloud and deliver to any device. All of this can be done while having a consistent infrastructure across cloud environments. This provides the customers the flexibility they need when using multiple cloud environments, as well as a way in which they can better mitigate the security risks involved in doing this.”

He believes that, when VMware transformed the data centre 20 years ago, it inadvertently laid the foundation for how we build cloud environments today. VMware Cloud Services are designed to give customers the flexibility to leverage any cloud environment while providing consistent operations for how clouds are managed and secured. VMware’s growing portfolio of Cloud Services therefore provides visibility, operations, automation, security, and governance across any cloud.

“VMware’s focus is to break down obstacles and barriers for customers and deliver the ultimate Hybrid cloud,” he says.

The full announcement, as provided by VMware, includes:

  • New VMware Hybrid Cloud Extension Service for Private Cloud: A SaaS offering that provides application mobility and infrastructure hybridity across different vSphere versions, on-premises and in the cloud. Previously announced Hybrid Cloud Extension services for both IBM Cloud and VMware Cloud on AWS are now available, and VMware has now added a new service for self-managed private enterprise datacenters. Hybrid Cloud Extension provides the operational support that enables enterprises to complete large-scale workload movement in environments spanning multiple private datacentre locations. Hybrid Cloud Extension enables enterprises to manage secure application migration without modification, with little or no application downtime, and across heterogeneous VMware vSphere environments. Cloud migration is simplified by eliminating the need to replatform, retest, or change cloud tooling, all while maintaining business continuity, application uptime, network architectures, and performance. With the general availability of Hybrid Cloud Extension for both IBM Cloud and VMware Cloud on AWS, customers can also extend their VMware-based environments to the public cloud for on-demand capacity and geographical expansion.
  • Expanded Wavefront by VMware Service: This SaaS-based, high-scale, metrics monitoring and analytics platform supports cloud-native and enterprise applications, and both public and private cloud infrastructure, including AWS, Google Cloud Platform, workloads running on Azure, and now VMware Cloud on AWS. VMware has added 45 new Wavefront integrations, including GCP, Chef, GitHub, Spark, Nginx+, and Mesos, in addition to already supported integrations , such as AWS Lambda, Kafka, and Docker, expanding the set of information that can be unified, visualised, and monitored by Wavefront, helping customers better optimise applications and deliver more compelling reporting and dashboards for dynamic applications. Wavefront now supports Kubernetes in Pivotal Container Service (PKS), application platform services such as Pivotal Cloud Foundry (PCF), and enterprise applications running on VMware-based private clouds. Wavefront also now integrates with VMware vRealize Operations, empowering IT to partner with lines of business and application owners by providing rapid onboarding of Wavefront, agent lifecycle management and control, and shared visibility not only of the infrastructure, but also for the applications that run on top. Wavefront is free to try at www.wavefront.com/sign-up.
  • New VMware Log Intelligence Service: The newest offering for VMware Cloud Services, Log Intelligence will deliver deep operational insights into VMware-based datacentres and VMware Cloud on AWS. Log Intelligence provides rapid IT troubleshooting and centralised log management across multiple clouds including VMware Cloud on AWS. Log Intelligence uses machine learning algorithms and real-time log analytics to continuously scan for anomalies in datacentre and cloud environments. The service delivers high-performance log search and rich dashboards to give IT unified visibility into application behavior and the health of underlying infrastructure.
  • Expanded VMware Cost Insight Service: Adding to the existing support for AWS, Microsoft Azure, and VMware private cloud datacentres, Cost Insight now delivers detailed assessments for migrating workloads to VMware Cloud on AWS, calculating the capacity and the cost of running apps in private or public clouds. Cost Insight offers a deep understanding into the true cost of migration through integration with VMware Network Insight, giving IT a more accurate view of the total cost of an app, including the estimates on network egress and storage IOPS costs post migration. Cost Insight offers an array of savings recommendations, alerts, and reporting capabilities including the ability to set cost thresholds to manage costs and maintain budget.

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Now IBM’s Watson joins IoT revolution in agriculture

Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production

IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.

By 2050, the world will need to feed two billion more people without an increase in arable land [1]. IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.

Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”

New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.

Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.” 

The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 [2]. Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.

The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.

Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.

IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.

The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.

[1] The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”

[2] Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10


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What if Amazon used AI to take on factories?

By ANTONY BOURNE, IFS Global Industry Director for Manufacturing

Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.

At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.

If Amazon did factories

If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.

Manufacturing with knowledge

Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.

In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.

As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.

Knowledge for manufacturing

For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.

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