Do you want to fire up a bunch of techies? Talk about multicloud! There is no shortage of opinions. I figured we should tackle this hot topic head-on, so I recently talked to four smart folks—Corey Quinn of Duckbill Group, Armon Dadgar of Hashicorp, Tammy Bryant Butow of Gremlin, and James Watters of VMware—about what multicloud is all about, key considerations, and why you should (or shouldn’t!) do it.

Five important insights came out of these discussions. If you’re on a multicloud journey or considering one, keep reading.

Do: Choose to do multicloud for the right reasons

Don’t do multicloud because Gartner says so, implores Corey Quinn. Before embarking on a multicloud, define a “why” focused on business value journey, says Armon Dadger. For example, you might want to use services from each public cloud because of their differentiated services, according to Tammy Bryant Butow. Armon also calls out regulatory reasons, existing business relationships, and accommodating mergers and acquisitions. On the topic of M&A, Corey points out that if you acquire a company that uses another cloud, it’s usually expensive and difficult to consolidate. It can be smarter to stay put.

Don’t: Over-engineer for workload or data portability

Thinking that you’ll build a system that moves seamlessly among the various cloud providers? Hold up, says our group of experts. Armon points out that aspects of your toolchain or architecture may be multicloud—think of some of your workflows or global network routing—but that shifting workloads or data is far from simple. Corey says that trying to engineer for “write once, run anywhere” can slow you down, and ignores the inherent uniqueness that’s part of each platform. Specifically, Corey calls out the per-cloud stickiness of identity management, security features, and even network functionality. And data gravity is still a thing, says James, that causes some to dismiss multicloud outright.

If you’re using multiple public clouds, you take advantage of the distinct value each offers, Armon says. Use native cloud services where possible so that you see the benefits from useful innovations, built-in resilience, and baked-in best practices. The value from that cloud-infused workload may outweigh the benefits of seamless portability.

Do: Recognize different stakeholder interests and needs

James smartly points out that many multicloud debates happen because people are arguing from different perspectives. Context matters. If you’re an infrastructure engineer who invests heavily in a given cloud’s identity and access management model, multicloud looks tricky. Or if you’re a data engineer with petabytes of data homed in a particular cloud, multicloud may look unrealistic. James highlights that many developers default to multicloud because their local tools—where all the work happens—are multicloud. A developer’s IDE and preferred code framework(s) aren’t tied to any given cloud. Be aware that groups within your organization will come at multicloud from distinct directions. And this may impact your approach!

Don’t: Go it alone

Corey talks about the importance of asking others what worked, and what didn’t. Tammy offers her best practices around sharing results from experiments. It’s about sharing knowledge and tapping into it for community benefit. Others have probably tried what you’re trying, and can help you avoid common pitfalls. If you’ve just made an architectural choice that didn’t work out, share it, and help others avoid the pain. 

Read research from analysts, go to conferences or watch videos to observe case studies, and join online communities that offer a safe place to share mistakes and learn from others.

Do: Experiment first using techniques like multi-region deployments

If you think you can operate systems across clouds, how about you first try doing it across regions in a specific cloud, suggests Corey. Getting a system to properly work across cloud regions isn’t trivial, he says, and that experience can help you uncover where you have architectural or operational constraints that will be even worse across cloud providers.

This is great guidance if your multicloud aspirations involve using multiple clouds to power one application—versus the more standard definition of multicloud where you use different clouds for different applications—but can also surface issues in your support process or toolchain that fail when faced with distributed systems. Start with muti-region deployments and chaos engineering experiments before aggressively jumping into multicloud architectures.

The Google Cloud take

Do the things above. It’s great advice. I’ll add three more things that we’ve learned from our customers.

1. Don’t fear multicloud. You’re already doing it. You don’t single-source everything. As Corey mentioned, you probably already have one cloud for productivity tools, another for source code, another for cloud infrastructure. You’ll use software and application services from a mix of providers for a single app. You have that experience in your team and have been doing that for decades. What people do rightly worry about is using more than one infrastructure service beneath an application, as that can introduce latency, security, and logistical hurdles. Make sure you know which model your team is considering.
2. Embrace the right foundational components, including Kubernetes. Will everything run on Kubernetes? Of course not. Don’t try to do that. But it also represents the closest thing we have to a multicloud API. Companies are using Kubernetes to stripe a consistent experience across clouds. And this isn’t just to orchestrate containers, but also to manage infrastructure and cloud-native services. Also, consider where you need other fundamental consistency across clouds, including areas like provisioning and identity federation.
3. Use Google Cloud as your anchor. Here’s a fundamental question you have to decide for yourself: Are you going to bring your on-premises technology and practices to the cloud, or bring cloud technology and practices on-prem? We sincerely believe in the latter. Anchor to where you’re trying to get to. We offer Anthos as a way to build and run distributed Kubernetes fleets in Google Cloud and across clouds. By using a cloud-based backplane instead of an on-prem one, you’re offloading toil, leveraging managed services for scale and security, and introducing modern practices to the rest of your team.

We learned a lot about multicloud through these discussions, and it seems like others did too. That’s why we’re going to do a second round of interviews with a new crop of experts so that we can keep digging deeper into this topic. Stay tuned!

For a look ahead at the trends that will animate the retail industry this year, let’s take a look back at the 2022 National Retail Federation (NRF) “Big Show” in NYC.

Attendees at January’s event were treated to tangible examples of how retail challenges are being solved today, including new solutions to help them parse customer expectations and buying patterns, adapt stores into omni-channel experience hubs, and improve data visibility and actionability.

NRF 2022 also took the “omni-channel everything” theme of last year’s show to the logical next level: Enabling the best hybrid experiences. The message came through loud and clear of the importance of integration and interoperability in this new hybrid world – making everything work well together.

The need for modern digital infrastructure to enable this blending of physical and digital retail smoothly is paramount. To that end, technology vendors demonstrated how digital transformation initiatives, such as contactless and real time IoT and mobile applications, need to be built on cloud, edge, and secure connectivity to allow retailers to achieve the modern seamless hybrid retail that today’s consumer wants.

Other prominent themes and technologies highlighted at NRF included: extending engagement in the metaverse, sustainability, physical and digital security, and the agility and adaptability imperative.

The Metaverse and Hybrid (Omni-channel) Experiences

Today, the metaverse is an extension of our lives, enhanced by technology, which exists as a series of virtual worlds. In the future, the metaverse will be an interconnected, endless world where digital and physical lives fully converge. Imagine waiting for an appointment at a real booth on the NRF show floor while your avatar roams a fully fleshed-out digital NRF, meeting other virtual attendees, stopping for coffee at the digital Starbucks, and paying for a coffee that an in-the-flesh Starbucks employee brings to them. Digital and physical selves merge seamlessly in the metaverse, as the worlds draw closer together.

In the metaverse, brands have a digital presence, too. Nike filed seven trademarks late last year, including those for “Nike,” “Just Do It,” and its swoosh logo, and posted openings for virtual designer roles, indicating its intent to make and sell virtual branded sneakers and apparel. It subsequently purchased RTFKT Studios, a company that already makes and sells NFTs and digital sneakers. (In one collaboration with teenage artist FEWOCiOUS, the company sold 600 pair/NFTs of sneakers in just six minutes to the tune of more than $3.1 million.)

The metaverse also opens possibilities for gathering data about consumers and product demand. Imagine a sneaker drop in the virtual world. Certain styles of new kicks sell like gangbusters, giving the brand insight into what might sell IRL, intelligence that leads to trend-right production and less inventory headed for markdown or landfills. The metaverse can be a vehicle for more sustainable operations.

The metaverse further bridges the narrowing gap between digital worlds and physical worlds. Most consumers aren’t outfitting an avatar, but they are moving between online and offline and expect retailers to accommodate those hybrid omni-channel journeys seamlessly. Those demands have accelerated around last-mile delivery and experiences such as buying online and picking up in store (BOPIS) or at curbside, shopping in store and returning merchandise online, adding items to a BOPIS purchase when at the store, or communicating a substitution to the third-party grocery delivery service

Hybrid experiences open opportunities to please the consumer in new ways, but they also add expense and complexity. The need to meet this demand while enabling profitability was a major theme behind many of the technologies discussed at NRF. These included artificial intelligence (AI) for recommending the right product, return logistics software for defining and guiding product-specific reverse logistics workflows, order orchestration and fulfillment applications for omni-channel shopping, and last-mile delivery visibility for optimizing customer experience, to name a few. Also on display were task management applications help to improve and optimize in-store employee engagement, as well as touch-free applications to allow for faster payments and customer self-service checkout. RFID continues to improve inventory accuracy and inventory locating on the shelf, throughout the store, and the supply chain.

Sustainability

NRF 2022 saw a strong focus on sustainability. An NRF/IBV study released at the show highlighted the significant embrace of sustainable shopping by consumers. According to the survey, 62% of shoppers are “willing to change their purchasing habits to reduce environmental impacts.” About half indicated a willingness to pay a premium – on average a 70% premium – for sustainable products and brands.

Retailers are working to improve sustainability and reduce carbon footprint across operations by using sustainable sourcing through the supply chain, the store, and even returns. Tech vendors unveiled a variety of solutions enabled by cloud/edge, AI, computer vision, and IoT/RFID to allow retailers to effectively measure and record their environmental efforts, with the goal of reducing their impact.

Several cloud and digital infrastructure providers showcased sustainability clouds and other technology aimed at asset management with the goal of reducing energy consumption, water usage, waste. Examples included using IoT sensors to reduce water usage, optimizing re-use of store assets, and dashboards that allow retailers to accurately monitor and measure carbon output. However, such sustainability solutions can be most successful when running on the next-generation digital infrastructure that helps retailers better compete and differentiate in today’s omni-channel world.

Physical and Digital Security

According to a 2021 NRF survey, 57% of U.S. retailers reported the pandemic led to an increase in organized retail crime, while 50% reported an increase in shoplifting. When IDC’s Future Enterprise Resiliency & Spending Survey, Wave 10 (November 2021) asked retailers which digital infrastructure investments would provide the greatest strategic advantage in 2022, their #1 response was “cybersecurity and recovery investments.”

A wide range of technology vendors acknowledged retailer concerns with regards to security, fraud, and loss prevention:

• Networking, connectivity, and edge vendors highlighted multilayer security solutions that promise to protect data from a range of IoT applications that utilize customer and associate data. Many offer security consulting services to address varied threats including ransomware, retail crime, and loss prevention.
• Security and e-commerce security vendors showcased solutions to prevent fraud and abuse in e-commerce applications as well as omni-channel applications such as BOPIS and curbside pickup, using AI-based analysis for identifying “bad”/risky customers and mitigating risk.
• Cloud vendors highlighted how retail clouds provide consistent, reliable identity management and data security.
• POS/payments/store technology vendors emphasized their ability to handle payments securely from any platform with multifactor tokenization, improved identity techniques such as biometrics and voice authentication, as well as AI-enabled and computer vision solutions for loss prevention at checkout and at the door.

The Agility and Adaptability Imperative

On display at the show were multiple flavors of the digital infrastructure technology that retailers need to achieve agile, personalized, data-driven, integrated seamless operations across the many channels of today’s retail landscape. The emphasis was apt. More than half of retailers plan to boost investment in business agility and operational agility over the next 12 months, according to IDC’s Future Enterprise Resiliency & Spending Survey, Wave 10 (November 2021).

Technology vendors highlighted their connectivity investments to enable business and operational agility and their technology investments for better ease of integration, scalability, and the ability to more easily swap out or mix and match applications with integrated platforms, open systems, hybrid cloud, and retail industry clouds.

Vendors also showed off infrastructure to better harness data while enabling its visibility, maximizing its value, and providing the data-driven personalization essential for competitive advantage and differentiation. Highlights included fast, secure connectivity, 5G and Wifi-6, and edge- and cloud-enabled data and AI platforms to generate real-time insights – all designed to enable today’s omni-channel retail.

Advice for the technology buyer

Retailers should consider these key themes from NRF 2022 when making technology investment decisions for 2022 and beyond. To avoid lagging behind those retailers already moving toward thriving into the future, take action to:

• Enable the seamless, contactless omni-channel approach that today’s consumers want and expect.
• Replace legacy infrastructure that was not built to handle the modern retail environment that requires the agility and adaptability to seamlessly connect rapidly increasing volumes of data securely and more quickly than ever.

Whether sustainability, adaptability, the metaverse, or security are top concerns, addressing business needs holistically and strategically should be job #1.

Continue the conversation by downloading our Transforming retail and CPG markets whitepaper today.

At 340 square miles, the City of Memphis is among the largest in the United States in terms of land area. Memphis has over 6,800 lane-miles of city streets, enough to drive back and forth to Los Angeles four times. Keeping these streets well maintained and safe for citizens and visitors is a major priority for the city.

Lots of traffic, lots of roads, and a four-season climate prone to wintertime freeze-thaw-refreeze cycles means the opportunity for potholes. Although the city aims to fill potholes within five business days of notification, it can take longer, especially during winter and early spring. Last year, the city’s Public Works crews repaired some 63,000 potholes, only 20% of which were reported by residents. Approximately 32,000-man-hours each year are spent repairing potholes, with seasonal fluctuations requiring ten to twelve Street Maintenance crews working steadily during the winter months. Still, many went unreported, leading the city to flag pothole request resolution under “needs improvement” on its open data portal website.

Like many large cities, Memphis also struggles with vacant and blighted properties. Nearly 15,000 properties in Memphis are likely vacant, and city officials contend that many are owned by out-of-town investors who live elsewhere and do not take necessary restoration or maintenance steps. These properties can decrease the value of surrounding real estate and discourage new businesses and other residents from moving to an area. Citizen frustration and concerns over the number of blighted properties has made blight eradication a major focus of the City of Memphis.

Historically, residents reported potholes and blighted properties by calling 311, or more recently by using the Memphis 311 app. However, these reports only covered about 20 percent of the problems — often the worst cases. And by the time residents took the initiative to submit a 311 report, they usually weren’t feeling good about the situation.

Recognizing that potholes and vacant properties are often the most visible indicators of whether a city government is doing its job efficiently, Memphis Mayor Jim Strickland and CIO Mike Rodriguez began looking for ways they could apply technology to fix the problems. Mike approached Google for ideas, and Google recommended conducting a machine learning proof-of-concept (POC) with SpringML, a Google Cloud Partner.

“Memphis is focused on easy living, and we want to do everything we can to keep our citizens happy,” says Mike Rodriguez. “Working with Google and SpringML to reduce potholes and urban blight using machine learning and artificial intelligence was an easy decision.”

Bringing machine learning to city operations and budgets

The city’s goal is to detect potholes and abandoned properties by analyzing video footage of roads and residential properties. It wanted to classify potholes by width and depth, and share the information with workers who can repair them. For abandoned properties, it wanted to enable more strategic deployment of resources for homeowners citywide and take action to hold neglectful property owners accountable.

The POC began by training TensorFlow models for ML object detection using preconfigured AI Platform Deep Learning VM Images on Compute Engine. SpringML helped set up cameras and developed a user interface to collect pothole data and automate the 311 ticketing process.

Together, the teams analyzed 30 days of video from a moving city bus and high-resolution video from 360-degree cameras mounted to a code enforcement vehicle, overlaid with data from 311 reports. As the models were refined, accuracy quickly climbed from 50 percent to over 90 percent as models were taught to differentiate a pothole from a manhole cover or other object.

The city also imported routes, potholes, and paving data along with geolocation data from ArcGIS and Google Maps into BigQuery to better understand street conditions and the proximity of potholes to one another. BigQuery also analyzes city property records, tax records, 311 reports, and third-party survey data on-demand to predict where homes are starting to become run down and where neighborhood decay is most likely to occur. The SpringML team created a pilot analysis to begin vacant property protections and developed a user interface tool to interact with the model’s results.

“Google Cloud Platform made it possible for us to experiment with machine learning and artificial intelligence to help solve our city’s problems while working within the budget constraints of a municipal IT organization,” says Mike. “Google turned a ‘nice to have’ into a ‘let’s do this!'”

Identifying 75 percent more potholes

Memphis expects to substantially reduce the number of potholes on its streets, creating a better driving experience for residents and visitors alike. Because drivers won’t be as likely to swerve to miss a pothole, streets will be safer and friendlier to bicycles and scooters. Fewer potholes will also save the city between $10,000 and $20,000 annually in city claims that it pays out in cases where vehicle damage results from a pothole that was not addressed in a timely manner.

“Historically, Public Works has relied primarily upon Street Maintenance crews to proactively locate and fill potholes. As Memphis has over 6,800 lane-miles of public streets, it is a daunting task to reliably survey the entire system in an efficient and systematic way,” says Robert Knecht, Public Works Director for the City of Memphis. “The outcome of the data collected will be invaluable to Public Works so that it can ensure it is managing the city’s street system in a more proactive manner.”

Memphis will be able to better prioritize road maintenance based on condition and impact, increasing the efficiency of its Public Works road crews. Analyzing video of streets also gave the city visibility into issues it wasn’t previously aware of, such as curbs, gutters, and manhole covers that had been mistakenly paved over and need to be excavated. The ML process is easily transferrable to other concerns as well, helping the city identify illegal signs or spools of cable hanging on light posts that could be potentially unsafe.

Helping communities recover and thrive

Memphis is also having success in analyzing predictive trends to combat high rates of abandoned and blighted properties, surpassing 97.5 percent accuracy. “In the past, Public Works experimented with comprehensive, city-wide blight identification by using approximately 200 volunteers to survey and photograph over 237,000 city parcels. This effort was costly, took a long time to complete, and resulted in inconsistent data collection,” says Robert. “Blighted property conditions can change quickly in a city the size of Memphis. Now, with this new technology, Memphis will be able to make a significant difference in the efforts to proactively and comprehensively identify and manage blighted and substandard properties.”

Code Enforcement with better data-driven detection mechanisms enables the city to also identify cases where homeowners are not physically or financially able to keep up with the challenges of homeownership and make them aware of resources that are available to assist them. Memphis Code Enforcement can do a better job of finding people living in derelict properties that pose hazards to inhabitants’ health and safety, and help them fix those problems or find a new place to live.

“Using SpringML and Google Cloud Platform to detect indicators of vacant or blighted properties will help Memphis create safer neighborhoods that will be more attractive to businesses and home buyers,” says Mike. “Property values and employment will go up, crime will go down, and social services can be more focused and effective.”

Revolutionizing service delivery for citizens

Memphis is proving the viability of a cost-effective, cloud-based machine learning model that other cities can follow. The city is already looking into new applications of AI and ML that will further improve city services and help it build a better future for its 652,000 residents.

As part of his commitment to a transparent government, Memphis Mayor Jim Strickland created an open data policy that commits to releasing raw data and sharing it with citizens in a variety of downloadable formats. Going forward, this transparency will help citizens understand how their needs are being served and uncover new, innovative use cases for AI and ML.

“Our goal is to become a smart city, and technologies such as Google Cloud Platform and SpringML put us ahead of the game,” says Mayor Strickland. “Google understands data, and there isn’t a better company to help us analyze our data resources for actionable insights.”