Over the past decade, many enterprises have focused on moving their applications to cloud infrastructure. Most enterprises have considered a mix of public cloud and private cloud environments for their workloads. Various workloads have been successfully migrated to a cloud environment including data analytics and customer engagement applications. In the recent few years, enterprises have also begun experimenting with running artificial intelligence/machine learning, Internet of Things (IOT) and Blockchain solutions in public cloud environments. However, a challenge that enterprises running workloads in public cloud environments continue to face deals with latency introduced due to the distance between the point of contact of an end user and the public cloud data center.
Typically referred to as the “Edge”, the point of user contact has evolved from being simply a web/mobile browser to more sophisticated contact points such as “Smart Vehicles” or “Smart Things”. Such requests are often highly latency intolerant and also tend to have very sensitive security requirements. This has led to the evolution of the concept of “Edge Computing” which refers to processing an end-user/thing request at a point closet to the location where the request originated. A similar model has been in existence since the late 90s where content delivery networks such as Akamai technologies provided hundreds of thousands of “Edge” servers distributed worldwide. This model is now entering a “2.0” phase where the requirements around real-time responses & what processing is possible at the edge is getting more complex. In addition, the data being generated at the “Edge” is now orders of magnitude greater than that generated in the “Web” era.
Edge computing model will need the support of Telco giants such as AT & T who are busy rolling out 5G networks. Edge computing will need to rely on high speed cellular networks like 5G to ensure data connectivity even in remote locations. Delivering immersive experiences such as Augmented reality will need to rely on edge computing to ensure the vast amount of data being generated is processed in real-time to deliver an enjoyable experience. According to a Data Age 2025 study, almost a quarter of all data will be generated at the edge. Major hardware and cloud providers have jumped into the edge computing market, given the expectations around rapid YOY growth (35 %) and a forecast of ~ $7B USD. Legacy content delivery networks (CDNs) have had a taste of what it’s like to deal with the edge having delivered content to internet devices for the past two decades. However, the requirements around data storage and compute at the edge are likely to challenge even leading providers such as Akamai. Cloud leaders such as Amazon Web Services (AWS) have expanded their centralized cloud data center model to support an “Edge” infrastructure via their service offering [email protected]. This service enables an application to delegate content processing for eg. to the edge and when combined with it’s traditional content-delivery network service AWS CloudFront, one can expect to apply “business rules” that execute on the edge via serverless functions. This can lead to a great customer experience by delivering relevant and personalized content to end-users. AWS also has a leading solution “AWS Greengrass” that let’s you run local compute, messaging and Machine Learning inference on connected devices. Microsoft is not far behind with Azure IoT Edge offering processing for connected things and newly announced Azure Data Box Edge that enables data processing at the edge. Other providers such as startup “Packet” are expanding rapidly to deploy a globally distributed set of edge locations. No single provider appears to have a comprehensive solution today as edge computing calls for network, compute, data and hardware innovations.
Edge computing will be a key trend that must be followed by organizations looking to transition into a Digital business. Edge computing will reshape both business operations as well as IT environments in the coming years. Will cloud computing be replaced by Edge? Not likely. Each will continue to serve distinct use cases. Centralized cloud infrastructure will continue to serve as the backbone for data and compute intensive workloads including Machine Learning model training while “delegating” lighter processing to the edge. For application owners that deal with “Intelligent” applications that need to process real-time information to deliver immersive experiences or predictive analytics, the future may very well lie at the edge.
Love your trips to the grocery store? You may soon enjoy a “Joy Ride” next time you need to pick up your milk from the local grocery store. With the launch of Instacart, the online grocery ordering app, we experienced a whole new level of convenience. Instacart enabled a quick and easy way to stock your fridge with groceries without stepping out of your house. Instacart members can enjoy their favorite TV Shows while a personal shopper runs through your grocery list and delivers them to you within a very short time interval. The Instacart service however is not free and users have to either pay a delivery fee or sign up for an annual membership package.
Seeing Instacart’s success, most major grocery chains including Kroger, Meijer and Target have launched their own “Groceries App”. These chains intend to serve their customers better by offering in-store pricing and other coupons that are not available to Instacart users. Grocery delivery services have exploded in the recent past with several other Instacart competitors such as Postmates and Shipt (Acquired by Target). Postmates recently tied up with Instacart in addition to being a preferred partner for Walmart’s grocery delivery service. Shipt has tied up with major grocery chains such as Safeway and Vons to enable grocery delivery. The delivery model for the online grocery services has relied on “Runners” or individuals who “Run” through stores to pick up groceries on your behalf.
Instacart may have pioneered online grocery ordering and delivery. However, the grocery delivery market is about to witness another transformational shift that should immensely benefit shoppers. Grocery stores are looking to self-driving cars to literally roll-out the “Red Carpet” to have you come into the store. Waymo, Google’s former self-driving car business, recently announced a partnership with Walmart to offer customers a “Self-Driving” car that will not just pick up your groceries for you but also pick YOU up at home and bring you safely back home. Grocery giant Kroger partnered with Silicon-Valley startup Nuro that provides an autonomous vehicle that picks up your groceries and delivers them home to you. Users can unlock the “Nuro” vehicle using a pre-defined code. Initially, Kroger will leverage Nuro to deliver in areas where it doesn’t offer delivery services. However, I believe Kroger will look to replace it’s Delivery service powered by Instacart with it’s own fleet of Nuro vehicles.
The value proposition for grocery delivery powered by autonomous vehicles is high for both the grocers and the users. Grocers stand to gain by owing the “last mile of delivery” giving themselves more control over the customer experience while also owning the data regarding the delivery time/preferences etc. Users may benefit from either “no fees” or “lower delivery fees”. Walmart’s approach is intriguing as they are focused on “bringing customers into the store” in a self-driving vehicle where as Kroger is trying the opposite- sending groceries home. Walmart’s strategy may drive further “impulse” purchase in non-grocery areas and lead to an overall increase in sales across multiple categories. Kroger’s approach may not lead to more ‘in-store’ sales but it will be interesting to see if the “Nuro” vehicle may carry a few “convenience” items that one may have forgotten to order with their milk- e.g. eggs eventually leading to a larger average order value.
Autonomous vehicles will unleash a plethora of disruption well beyond grocery delivery. While initial self-driving use cases are surfacing in the food and grocery delivery domain, they hold immense potential to transform our everyday lives. From delivering medicines from your local pharmacy to picking up your dry cleaning, autonomous delivery is all set to revolutionize local commerce.
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The rise of online shopping has caused many retailers to shut down their brick-and-mortar presence in shopping malls. “Anchor” stores such as “Macy’s”, “Sears”, “JC Penney” have shut down many prime locations due to poor profitability rising from the net effect of better deals and convenience from online shopping. This has forced many mall managers to rethink their strategy to lure shoppers into the mall. Some of the vacancies are being redeveloped as “Fitness Centers”, “Clinics” and even “Event Spaces” for concerts etc. Other ideas being proposed include “Destination malls” that may include experiences such as Casinos, rock climbing walls and even roller coasters.
Amidst this, a new category of stores are emerging that hold promise for the revival of “brick-and-mortar”. “Pop-up-Stores” are popping up at malls and enabling physical retailers and online retailers alike an opportunity to offer a unique experience to shoppers that entices them to leverage lucrative offers and make an instant purchase. Pop-up-Stores are available in the form of a “store within a store” or “independent kiosks”. “Pop-up-Stores” also enable merchants to go “where the demand” is instead of sign on a 99 year lease like in the past. This is proving to be extremely disruptive & it’s no longer just the local small business owner who is working on setting up a popup store to boost sales. Big brands including online subscription service “Birchbox” have used pop-up stores to promote their products through “Pop-up” events and other brands such as Best Buy, JCrew and Nordstorm have set up pop-up stores across the country. The beauty of a pop-up store is it’s low commitment offer along with low-cost. It strikes a strong resemblance to a “pay for usage only”, “cloud computing” model we are now familiar with. What’s more, each pop-up store can be customized for the local market more easily and brands can unleash their creativity to draw crowds in. Popup stores have grown into a $10 billion industry according to Popup republic.
So will the pop-up stores be the savior for Brands looking to compete against online commerce giants such as Amazon? The answer may depend on the creative genius in the marketing and experience of the pop-up stores. Immersive personalized experiences including game arcades, virtual reality and digital walls can be delivered seamlessly through the use of digital technology such as Cloud computing, Big Data, Machine Learning and Internet of Things (IOT). Digital signage solutions such as those enabled through tablets or mirror displays such as Samsung’s ML55E Digital Mirror Display can provide engaging content and experiences for apparel shoppers. Digital Kiosks let shoppers explore and learn more about the products and even complete purchases right at the pop-up store. Sensor data through “beacons” and Facial recognition systems deployed in the pop-up store could make them “autonomous” stores where no retail associate is present. Such pop-up stores can further enhance the customer experience by enabling personalization and targeted marketing, and convenient access in non-traditional locations such as airports, hotel lobbies etc.
It’s clear that pop-up shops have a compelling value proposition to both retailers and shoppers. Shoppers will continue to flock to pop-up stores and seek out “unique” experiences(and offers) that they can’t get online and are ready to “pop” open their wallets for the right product delivered through this exciting new channel.
Cloud wars are hot right now. Amazon, Microsoft and Google cloud are currently in the lead. Many large enterprises are choosing multi-cloud strategies and deploying workloads across cloud providers. While AWS continues to be the market leader, Microsoft’s Azure has had the fastest growth rate. Amongst these cloud providers, one other major provider has been quietly innovating to catch up with it’s rivals. Oracle, the leader in database technology launched it’s public cloud offering a few years ago and has been attempting to convert it’s existing install base of customers into cloud consumers. However, Oracle cloud has found itself in the midst of intense competition. Oracle’s strategy for cloud adoption includes a full-stack cloud offering including Software-As-A-Service (SaaS), Platform-As-A-Service (PaaS) and Infrastructure-As-A-Service (IaaS). This is a truly unique value proposition as no other cloud provider has such a comprehensive suite.
Oracle’s core strength, database technology is likely to influence decision makers into deploying their applications on Oracle cloud. Given it’s depth of understanding in the database technology domain, Oracle launched “Autonomous databases” at the 2017 Oracle Open world. Oracle’s autonomous database practically eliminates the need for any human intervention in managing the database and automatically performs tasks such as performance tuning, upgrades and patches. This leads to a massive reduction in downtime. Moreover, advanced machine learning and compression lead to a lower operating cost. Oracle also announced the Autonomous datawarehouse cloud earlier this year, which offers similar machine learning and self-recovery features. This week, Oracle announced Oracle Autonomous Transaction Processing Service , a fully-managed online transaction processing system designed for transaction processing for finance, retail, manufacturing applications. This is a major differentiator for Oracle cloud, as an existing Oracle user can simply migrate their on-premise databases to Oracle cloud and experience instant scalability and reduced costs.
So can we rely on autonomous databases for mission critical workloads? Enterprises have always relied on the expertise of DBA’s to constantly monitor their mission critical databases and apply required performance changes including updating indexes or redefining partitions etc. Oracle’s autonomous database is now relying on “Machine Learning” to take control of several traditional DBA tasks. The figure below shows how Oracle is applying Machine Learning to manage the databases:
Many enterprises and DBAs are likely to be paranoid about giving up control. However, such a model may have some distinct advantages and even free up DBA time to focus on higher value activities. For example, Oracle claims that its autonomous databases, leverage the Oracle RAC technology to scale the database across a cluster more effectively than competing clouds by allowing not just seamless horizontal scaling but also vertical scaling by increasing the number of cores on a node as required. Another big advantage stems from the auto-patch management especially as it pertains to security patches being applied automatically. In addition, data encryption and data masking is handled automatically as well. The one thing Oracle knows really well, is database performance and it has embedded tuning algorithms into the autonomous database to automatically improve performance as needed. Backups are typically scheduled to run every night and all encrypted data is transferred to the Oracle database backup cloud service.
Given Oracle’s service guarantees of 99.995 % uptime, the Oracle Autonomous database solution should be worthwhile for enterprises currently running large scale database workloads on Oracle.