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IBM Power Systems now available on Google Cloud

Enterprises looking to the cloud to modernize their existing infrastructure and streamline their business processes have many options. At one end of the spectrum, some organizations are replatforming entire legacy systems to adopt the cloud. Many others, however, want to continue leveraging their existing infrastructure while still benefiting from the cloud’s flexible consumption model, scalability, and new advancements in areas like artificial intelligence, machine learning, and analytics.To help you meet your cloud goals, whatever they may be, Google Cloud now offers IBM Power Systems as part of our cloud solutions. Today, customers can run IBM Power Systems as a service on Google Cloud—whether you’re using AIX, IBM i, or Linux on IBM Power. For organizations using a hybrid cloud strategy, especially, IBM Power Systems are an important tool. Because of their performance and ability to support mission critical workloads—such as SAP applications and Oracle databases—enterprise customers have been consistently looking for options to run IBM Power Systems in the cloud. IBM Power Systems for Google Cloud offers a path to do just that, providing the best of both the cloud and on-premise worlds. You can run enterprise workloads like SAP and Oracle on the IBM Power servers that you’ve come to trust, while starting to take advantage of all the technical capabilities and favorable economics that Google Cloud offers. IBM Power Systems on Google Cloud offers many other benefits, as well, including:Integrated billing: You can deploy the solution through the Google Cloud Marketplace and take advantage of integrated Google Cloud billing. This means you can take advantage of this offering just like any other Google Cloud service and get a unified bill from Google Cloud. Private API access: Google Cloud’s Private API Access technology lets you access Google Cloud resources privately, while enabling all IBM Power Systems resources (LPARs) to use private IP spaces that you choose. It’s secure by design and enables ultra low latency between the IBM Power servers and Google Compute Engine virtual machines.Integrated customer support: Google Cloud manages customer support, giving you one point of contact for any issues.Rapid deployment: An intuitive new management console enables quick ramp and rapid deployment of the solution.Many enterprise customers, including leaders in energy and retail, have already begun modernizing their infrastructure with this new offering. To learn more about how you can use IBM Power Systems on Google Cloud contact your Google Cloud sales representative, or email us at IBMPowerForGoogleCloud@google.com.
Quelle: Google Cloud Platform

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Retailers embrace Azure IoT Central

For many retailers around the world, the busiest quarter of the year just finished with holiday shopping through Black Friday and Cyber Monday to Boxing Day. From supply chain optimization, to digital distribution, and in-store analytics, the retail industry has wholeheartedly embraced IoT technology to support those spikes in demand; particularly in scenarios where brands need to build flexibility, hire strong talent, and optimize the customer experience in order to build brand loyalty. In our latest IoT Signals for Retail research, commissioned by Microsoft and released January 2020, we explore the top insights from leaders who are using IoT today. We discuss growth areas such as improving the customer experience, the use of artificial intelligence to achieve break-through success, and nuances between global markets around security concerns and compliance.

Building retail IoT solutions with Azure IoT Central

As Microsoft and its global partners continue to turn retail insights into solutions that empower retailers around the world, a key question continues to face decision makers about IoT investments; whether to build a solution from scratch, or buy a solution that fits their needs. For many solution builders, Azure IoT Central is the perfect fit, a fully managed IoT platform with predictable pricing and unique features like retail specific application templates that can accelerate solution development thanks to the inclusion of over 30 underlying Azure services. Let us manage the services so you can focus on what’s more important, applying your deep industry knowledge to help your customers.

New tools to accelerate building a retail IoT Solution

Today we are excited to announce the addition of our sixth IoT Central retail application template for solution builders. The Micro-fulfilment center template showcases how connectivity and automation can reduce cost by eliminating downtime, increasing security, and improving efficiency. App templates can help solution builders get started quickly and includes sample operator dashboards, sample device templates, simulated devices producing real-time data, access to Plug and Play devices, and security features that give you peace of mind. Fulfillment optimization is a cornerstone of operations for many retailers and optimizing early may offer significant returns in the future. Application templates are helping solution builders overcome challenges like getting past the proof-of-concept phase, or building rapid business cases for new IoT scenarios.

IoT Central Retail Application Templates for solution builders.

Innovative Retailers share their IoT stories

In addition to rich industry insights like those found in IoT Signals for Retail, we are proudly releasing three case stories detailing decisions, trade-offs, processes, and results from top global brands investing in IoT solutions, and the retail solution builders supporting them. Read more about how these companies are implementing and winning with their IoT investments and uncover details that might offer you an edge as you navigate your own investments and opportunities.

South Africa Breweries and CIRT team up to solve a cooler tracking conundrum

South Africa Breweries, a subsidiary of AB InBev, is the worlds’ largest brewing company and is committed to keeping its product fresh and cold for customers, a challenge that most consumers take for granted. From tracking missing coolers to reducing costs, and achieving sustainability goals, Sameer Jooma, Director of Innovation and Analytics for AB InBev turned to IoT innovation led by Consumption Information Real Time (CIRT), a South African solution builder. CIRT was tasked to pilot Fridgeloc Connected Cooler, a cooler monitoring system, providing real time insight into temperature (both internal cooler and condenser), connected state and location of hundreds of coolers through urban and rural South Africa. Revamping an existing cooler audit process that involved auditors visiting dealer locations to verify that a cooler was in the right place, and tracking the time between delivery and installation to an outlet are just two of the process optimization benefits found by Jooma.

“The management team wanted to have a view of the coolers, and to be able to manage them centerally at a national level. IoT Central enabled us to gain that live view.” – Sameer Jooma, Director: Innovation and Analytics, AB InBev.

Learn more about the universal cooler challenges that face merchants and consumer packaged goods companies worldwide in the case story.

On the “road” to a connected cooler in rural South Africa, a field technician gets stuck in the sand on his way to the tavern.

Fridgeloc Connected Cooler at a tavern in Soweto, South Africa.

Mars Incorporated Halloween display campaign unveils new insights thanks to Footmarks Inc.

For most consumer packaged goods companies, sales spike during holiday times thanks to investments across the marketing and sales mix, from online display advertising to in-store physical displays. This past Halloween, Jason Wood, Global Display Development Head, Mars Inc., a global manufacturer of confectionery and other food products, decided it was time to gain deeper insights into an age-old problem of tracking where their product displays went after they left the warehouse. Previously, Mars was only able to track the number of displays it produced, and how many left its warehouses for retailer destinations. They found the right partner with Footmarks Inc. who has designed their beacon and gateway-based display tracking solution with Azure IoT Central to deliver secure, simple and scalable insights into what happens once displays begin transit. Several interesting insights emerged throughout the campaign and afterward.

"Information on when displays came off the floor were surprising—major insights that we wouldn't have been able to get to without the solution." – Jason Wood, Global Display Development Head, Mars Inc.

Learn more about challenges Mars and Footmarks faced scaling, pricing, and managing devices for display tracking in the case story.

Foormarks Inc., Smart Connect Cloud dashboard for Mars Wrigley showing display tracking solution using IoT sensors for the 2019 Halloween campaign.

Microsoft turns to C.H. Robinson and Intel for Xbox and Surface supply chain visibility

In advance of the busy 2019 holiday season and the introduction of many new Surface SKU’s, the Microsoft supply chain team was interested in testing the benefits of a single platform connecting IoT devices on shipments globally, streamlining analytics and device management. This Microsoft team was also thinking ahead, preparing for the launch of the latest Xbox console, Xbox Series X, and for a series of new Surface product launches. With Surface and Xbox demand projected to grow around the world, the need for insights and appropriate actions along the supply chain was only going to increase. The Microsoft team partnered with TMC (a division of C.H. Robinson), a global technology and logistics management provider who partnered with Intel, to design a transformative solution based on their existing Navisphere Vision software that could be deployed globally using Azure IoT Central. The goal was to track and monitor shipments’ ambient condition for shock, light, and temperature to identify any damage in real time, anywhere in the world—at a scale covering millions of products.

“The real power comes in the combination of C.H. Robinson’s Navisphere Vision, technology that is built by and for supply chain experts, and the speed, security, and connectivity of Azure IOT Central.” – Chris Cutshaw, Director of Commercial and Product Strategy at TMC

Learn more about the results from the recent holiday season and what Navisphere Vision can do for global supply chain visibility in the case story.

Navisphere Vision dashboard showing IoT Sensors activity, managed through Azure IoT Central.

Getting started

NRF 2020: Retail's Big Show is happening in Manhattan from January 12 to 14. Azure IoT and other experts including retail solution builders Attabotics, C.H. Robinson, and CIRT will be in attendance.

Read more about IoT Signals for Retail report.

Get started with Azure IoT Central today.

Learn more about the solutions being used by these customers today.

Footmarks Inc. Smart Tracking asset tracking for consumer packaged goods companies.
CIRT Fridgeloc solution.
C.H. Robinson Navisphere Vision solution.

Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries.

Quelle: Azure

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Performance art: Making cloud network performance benchmarking faster and easier

Before you migrate workloads to the cloud, you need to benchmark network performance in order to understand how that performance affects your business applications. Unfortunately, the cloud hasn’t offered the standards, tools, and methods to do the benchmark testing you need. As a result, you’re forced to make deployment decisions without comprehensively understanding the implications of network performance for your use case.Today, we’re excited to make a few announcements that will help you understand cloud network performance more quickly and easily:We are investing in performance benchmarking tools. To begin with, we merged new contributions to PerfKit Benchmarker, an open-source tool created inside Google that makes network performance benchmarking faster and easier by automating network setup, provisioning of VMs, and test runs. With the updates, PerfKit Benchmarker now supports a broader range of network performance tests for VM-to-VM latency, throughput, packets-per-second for multiple clouds (inter-region, inter-zone, intra-zone, and on-prem to cloud), and lets you view the results in Google Data Studio (free to use). With this information, you can more accurately predict the performance impact of moving workloads to/across different clouds.The publication of a new benchmarking methodology for using PerfKit Benchmarker continuously and consistently. This methodology, co-developed with performance engineering researchers at Southern Methodist University’s AT&T Center for Virtualization, is based on Google’s own internal best practices. “Continuous performance measurement and benchmarking are essential for understanding trends and patterns in large-scale cloud deployments,” said Suku Nair, director of SMU AT&T Center for Virtualization. “PerfKit Benchmarker, which wraps over 100 industry standard benchmark testing tools in an easy-to-use and extensible manner, is a key enabler in automating this process.”Read on for an overview of how to use PerfKit Benchmarker to take advantage of its new features, such as support for additional performance metrics (e.g., packets per second) and deployment use cases  (e.g., VPN). Using PerfKit BenchmarkerPerfKit Benchmarker automates the setup and teardown of all the resources you need to run tests on (or between) most major public cloud providers, as well as on-premises deployments like Docker and OpenStack. Specifically, it automates the setup and provisioning of networks, subnets, firewalls and firewall rules, virtual machines, and drives required to run a large variety of benchmarks, as well as running the benchmarks themselves and tearing down the infrastructure afterwards. Along with installing and running the actual benchmark tests, PerfKit Benchmarker packages the test results in an easy-to-consume JSON format and offers hooks into backend storage providers like Google BigQuery, Elasticsearch, and InfluxDB to automate publishing results, making reporting and analytics a breeze.When performing network tests, the critical metrics you need to understand include throughput, latency, jitter, and packets per second. To find the values of these metrics across various configurations, you can use PerfKit Benchmarker to draw upon a number of testing tools, including iperf2, iperf3, ping, netperf, nuttcp, nttcp and NTttcp, just to name a few.Once PerfKit Benchmarker has been installed, running a single benchmark is simple: Specify the test you want to run and where you want to run it. As a basic example, here is a ping benchmark between two VMs that are located in zone us-east1-b of Google’s cloud:./pkb.py –benchmarks=ping –zones=us-east1-b –cloud=GCPThis command creates a new Virtual Private Cloud (VPC) and two new VMs in zone us-east1-b of Google Cloud, configures them for a ping test (including setting the appropriate firewall rules), runs the test, and then deletes the VMs and the VPC. Finally, it outputs the results to the console and stores them in a file in the /tmp directory. You can also store results in BigQuery or Elasticsearch when appropriate flags have been set. Measuring Google Cloud inter-region latency with PerfKit BenchmarkerWhen designing your environment, it’s important to understand the latency between components in different Google Cloud regions. As an example, here are the results of our own all-region to all-region round trip latency tests using n1-standard-2 machine types and internal IP addresses. The daily benchmark tests ran over the course of the last month. The statistics were all collected using PerfKit Benchmarker to run ping benchmarks between VMs in each pair of regions.To reproduce this chart, you can run the following command with the following config file. To run a smaller subset of regions, just remove the regions you don’t want included from the zones and extra_zones lists.You can also add the –run_processes=<# of processes> flag to tell it to run multiple benchmarks in parallel. Furthermore, you can add the –gce_network_name=<network name> flag to have each benchmark use a Cloud VPC you have already created so each benchmark doesn’t make its own VPC../pkb.py –benchmarks=ping  –benchmark_config_file=/pat /to/all_region_latency.yamlMore benchmarks using PerfKit BenchmarkerOther examples of network performance benchmark tests you can run using PerfKit Benchmarker include:Inter-region, inter-zone, and intra-zone network performance testsOn-premises to cloud and cross-cloud performance benchmarks between a VM in one cloud, and a VM on-premises or in another cloudPerformance benchmarks using various network tiersBenchmarking across various guest OSes (e.g., Linux vs Windows) and machine types (e.g., general purpose, compute-optimized)For complete details about the methodology for running more of these benchmarks, read the “Measuring cloud network performance with PerfKit Benchmarker” methodology white paper.More good stuff on the wayBy using PerfKit Benchmarker, you can make better decisions about where to put workloads, and improve the experience of your end-users. As time goes on, we’ll continue to add coverage for new performance benchmarking use cases, publish additional guidelines for cloud performance benchmarking, and report on the experiences of cloud adopters. In the meantime, we welcome and encourage new contributions to the PerfKit Benchmarker codebase, and look forward to seeing the community grow!
Quelle: Google Cloud Platform

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Google Cloud Helps Retailers Win the Digital Race

As I attend NRF 2020, retail’s biggest annual event today and speak with a number of leading retailers, one thing is clear: digital transformation is more than just a requirement. It’s a race. Retailers that transform the fastest are the most successful. We see this with retail leaders like Kohl’s and Lowe’s, who continue to innovate and reinvent themselves, and also with digital natives like Zulily and Stitch Fix, who have come up with entirely new ways to deliver great customer experiences.Technology is the fulcrum for this transformation, and Google Cloud is working with retailers in three important ways: We’re helping retailers accelerate digital and omnichannel revenue growth;We’re helping them become more customer-centric and data-driven; andWe’re providing solutions that help drive operational improvement. Capturing digital and omnichannel growth—and eliminating interruptions In a recentsurvey, one in 10 retail executives said their company’s website experienced an outage during Black Friday and Cyber Monday last year, and 72 percent said they experienced an outage within the past five years. We all know even a second in lag time can mean the difference between a sale and an abandoned cart, so uptime and speed are critical when shoppers are spending billions of dollars in a single day. That’s why we’re excited to expand our Retail Acceleration Program (RAP) to a broader set of customers in 2020. RAP is a services offering that helps retailers optimize their websites, build a unified view of customer data, and drive increased foot traffic. Today, we’re also expanding the availability of Customer Reliability Engineering, a white-glove service that helps retailers plan and execute flawlessly during their peak shopping seasons. Customers such as Kohl’s, Wayfair, and Shopify have already turned to Google Cloud to help them stay worry-free during Black Friday and Cyber Monday. Capturing omnichannel growth ultimately means creating better online experiences. Google Cloud offers several tools for retailers interested in providing more intuitive product discovery for consumers. We’re currently piloting one of these new tools—Google Cloud Search for Retail—and will bring it to the broader retail market in 2020. Powered by Google Search algorithms and leveraging state-of-the-art cloud AI technologies, Google Cloud Search for Retail provides retailers with high-quality product search results for their websites and mobile applications—giving them the ability to surface the right products, to the right customers, at just the right time.  Retailers today are increasingly centralizing their user data in Google’s BigQuery data analytics platform, and then building personalization and recommendation models on top of this data. Today, we’re announcing Google Cloud 1:1 Engagement for Retail, a blueprint and best-practice guide on how to build these types of data-driven solutions effectively and with less up-front cost. Delivered by Google Cloud and our ecosystem of partners, 1:1 Engagement for Retail helps retailers create hyper-personalization at scale.Helping retailers become more customer-centric and data-driven Google is the first place that shoppers go to discover new brands and products. Hundreds of millions of people shop each day across Google properties including Search, YouTube, Shopping, Google Assistant and Maps. We help retailers expand their reach with Google Ads, as well as empower them to better understand their shoppers with advanced analytics, so that they can optimize their spend across channels.As digital influence on sales continues to increase—and newer fulfillment options such as “buy online, pick up in store” or “ship from store” continue to become popular—there’s even more pressure on retailers’ supply chains. Being accurate with inventory planning and operating a more streamlined supply chain can be the difference between success and failure. Google Cloud’s new Buy Optimization and Demand Forecasting service offering allows retailers to plan inventory and manage their supply chains to deliver the right products to the right channels.One retailer using these solutions is Carrefour, one of the largest grocery retailers in France. Carrefour needed to ensure it had the right products, in front of the right shoppers, at the right store location. With Google Cloud, Carrefour developed an assortment recommendation tool that helped the chain support a more personalized selection at the store level, giving store directors the autonomy to influence inventory needs. The tool also gives Carrefour headquarters visibility into the merchandising decisions by each of their franchise stores. Driving operational improvement by merging online and offlineRetail customers are becoming more and more “channel-less” in their shopping. It’s imperative, then, to provide a consistent experience for customers as they move between channels in their shopping journeys. Our Google Cloud API Management for Retail solution, powered by Apigee, allows retailers to easily integrate the systems that power different sales channels, providing a more unified shopping experience for customers.Retailers struggle with the real estate that bulky computer servers take up in their stock rooms, and also face challenges in centrally managing all of their server applications. Today, we’re piloting Google Cloud Anthos for Retail, which helps retailers streamline and modernize their store operations. Rolling out more broadly in 2020, Anthos for Retail enables retailers to consistently deploy, configure, and manage applications across their fleet of stores at scale—without sacrificing performance or reliability. Speaking of stores, nothing is more critical for retailers than ensuring their frontline workforce is able to collaborate efficiently and effectively. The demographics of frontline retail workers are changing rapidly. Even as a more tech-savvy workforce comes online, many retailers still lag in putting cutting-edge tools in the hands of their employees—and this translates to delivering poor customer experiences. In fact, according to one Google study, more than 50 percent of frontline workers say that technology at their workplace has not changed in the last five years. With G Suite, Chrome Enterprise, and Android, we can help drive this transformation. G Suite enables retailers to improve productivity with easy-to-use tools that foster collaboration across the organization. Chrome Enterprise allows retailers to deploy shared, cloud-native devices that are secure, mobile and allow any employee to sign in and pick up where they left off. And Android devices can power dynamic store associate apps that digitize processes like stock checking and reordering to both collect signals from your store and make information available in real time to your store associates allowing them to proactively service your customers better.One example of this is Lowe’s. Using Android-based mobile devices and Google Cloud technology, the home improvement store, is giving its store associates the ability to view and update pricing and inventory on-the-fly. In fact, the company has recently rolled out 88,000 SMART Mobile devices to allow its associates to efficiently access real-time data without leaving the sales floor or losing engagement with a customer. Staying viable in the retail market today means using technology to solve big problems. Google continues to innovate and provide industry-specific tools that help retailers not just keep up with the competition, but also to win the ever-changing race.Here’s where you can learn more on Google Cloud for retail.
Quelle: Google Cloud Platform

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How predictive maintenance improves efficiencies across five industries

New technologies—including the rise of the Internet of Things (IoT)—and market pressures to reduce costs are pushing companies to move from reactive, condition-based maintenance and analytics to predictive maintenance. MarketsandMarkets forecasts the global predictive maintenance market size to grow from USD $3.0 billion in 2019 to USD $10.7 billion by 2024.
Predictive maintenance is generally thought to be most applicable to the manufacturing industry. While manufacturing certainly benefits from proactive maintenance, which encompasses predictive and preventative efforts, predictive maintenance can be applied to and benefit a wide range of industry sectors.
Predictive maintenance: Five client case studies from five industries
IBM is helping companies across industries apply predictive maintenance to improve business performance. Below are five IBM client examples demonstrating how predictive maintenance in the cloud is helping businesses from five different industries excel.
Waste management
Government of Jersey cleans waste management. The Government of Jersey is moving from reactive to proactive maintenance to better serve the approximately 100,000 residents of Jersey, the largest of the Channel Islands located off the coast of France. Maintenance had previously been done largely reactively and documentation sometimes took hours to find. Now, the Government of Jersey solid waste department is deploying solutions from IBM Business Partners Ennovia and Crazylog on the IBM Cloud to address these challenges. The CrazyLog Quickbrain solution provides modules for maintenance management, including preventative maintenance scheduling, inventory management and a record of reactive maintenance. The government-run waste department now has greater visibility into its equipment and can more easily access and find relevant information from its 5,000 pieces of documentation.
Read the case study for additional details.
Manufacturing
EcoPlant helps Israeli food companies improve efficiencies. Air compression systems are used by the food and beverage sector to package food, cut and shape food products and clean machinery. However, they’re also quite expensive to run, using as much as 30 percent of plant electricity, according to the US Department of Energy (DOE). Israeli startup EcoPlant is changing the landscape by helping the food and agricultural manufacturing plants cut energy use, reduce costs and improve maintenance and visibility, all with predictive maintenance on IBM Cloud.
Learn more about the EcoPlant predictive maintenance solution by reading the blog post and case study.
Building services
KONE keeps elevators running smoothly. KONE is in the business of keeping people in motion. Traditionally, elevators and escalators have been maintained on a calendar basis or when a problem occurred, but KONE recently launched its 24/7 Connected Services offering on IBM Cloud to provide predictive maintenance for its elevators. The Connected Services offering uses IBM Watson IoT and analytics to help reduce equipment downtime, minimize faults and provide more detailed information about equipment performance and usage.
See how KONE is better serving their customers by reading the case study and watching the video.
Renewable energy
Performance for Assets increases windfarm efficiencies and output. Wind energy is on the rise globally, according to data from Wind Energy International, but windfarm owners have typically had limited or no insight into the condition of their machines. To address this gap, Performance for Assets (P4A) teamed with the IBM Garage to develop an advanced monitoring system for wind turbines in the IBM Cloud. Their solution is designed to help windfarm owners gain insights that’ll help them maintain wind turbines, thereby increasing energy output and profits.
Read more about how Performance for Assets created a predictive maintenance solution with IBM by checking out the blog post and case study.
Mining
Sandvik Mining and Rock Technology improves mining output and safety. Sandvik Mining and Rock Technology is bringing advanced predictive analytics the mining industry. A common industry challenge is maintaining equipment; without properly functioning machinery, mining operations will slow drastically or cease altogether. Sandvik worked with IBM to enhance Optimine, its information and process management solution. Running on IBM Cloud, the solution uses IBM Watson IoT and IBM Maximo Asset Management to analyze vast amounts of data and predict maintenance needs. Now, mining operators can better act on insights to improve production efficiency.
Read the blog post to learn more about the solution that’s helping mining companies reduce mine production downtime by as much as 30 percent.
Learn more about predictive maintenance
See the following resources for more information about predictive maintenance services:

Blog post: A predictive maintenance breakdown
Solution page: Enterprise asset management and preventative maintenance
Guide: A business guide to modern predictive analytics
Interview: Electronic Design Editor Bill Wong talks with Greg Knowles, Program Director for the Watson IoT Portfolio Strategy, about predictive maintenance and artificial intelligence.

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Quelle: Thoughts on Cloud