Communication services providers (CSPs) are experiencing a period of disruption. Overall revenue growth is decelerating and is projected to remain below 1 percent per year, following a trend that started even before the pandemic.¹ At the same time, driven by the pandemic, data consumption in 2020 increased by 30 percent relative to 2019, with some operators even reporting increases of 60 percent.² 

The combination of pressure on revenues with rising data traffic costs is forcing operators to innovate in three fundamental ways. First, operators are looking to establish new sources of revenue. Second, increased network utilization must be met with a reduction in network cost. And third, there is an opportunity to gain new customers by improving the customer experience.

Fortunately, 5G offers a path forward across each of these three areas. Concepts such as network slicing and private networks allow CSPs to offer differentiated network services to public sector and enterprise customers. The disaggregation of hardware and software allows new vendors with unique strengths to enter the market and to enable CSPs to build, deploy, and operate networks in fundamentally new ways. And the ability to place workloads at the edge permits CSPs to offer compelling experiences to consumers and businesses alike. In this blog, we will discuss how CSPs can create a solid foundation for their cloud networks. 

Understanding telecommunications networks

First, it is useful to consider the way telecommunications networks were traditionally built. Initially, networks were built using physical network functions (PNFs) — appliances that used a tight combination of hardware and software to perform a specific function. PNFs offered the benefit of being purpose-built for a specific application, but they were inflexible and difficult to upgrade. As an example, deploying new features frequently required replacing the entire PNF, i.e., deploying a new hardware appliance.

The first step in improving deployment agility came with the concept of virtualized network functions (VNFs), software workloads designed to operate on commercial off-the-shelf (COTS) hardware. Rather than utilizing an integrated hardware and software appliance, VNFs disaggregated the hardware from the software. As such, it became possible to procure the hardware from one vendor and the software from another. It also became possible to separate the hardware and software upgrade cycles. 

However, while VNFs offered advantages over PNFs, VNFs were still an intermediate step. First, they typically needed to be run within a virtual machine (VM), and as such required a hypervisor to interface between the host operating system (OS) and the guest OS inside the VM. The hypervisor consumed CPU cycles and added inefficiency. Second, the VNF itself was frequently designed as a monolithic function. This meant that while it was possible to upgrade the VNF separately from the hardware, such an upgrade, even for a feature that affected only a portion of the VNF, required deployment of the entire large VNF. This created risk and operational complexity, which in turn meant that upgrades were delayed just as they were with PNFs.

Creating the foundation for cloud networks

The trick to establishing your cloud based network resides in the challenge of moving from VNFs to containerized network functions (CNFs) — network functions organized as containers as a collection of small programs, each of which can be independently operated. 

The concept of containers is not new. In fact, Google has been using containerized workloads for over 15 years. Kubernetes, which Google developed and open-sourced, is the world’s most popular container orchestration system, and is based on Borg, Google’s internal container management system.³ There are lots of benefits to using containers, but fundamentally, it frees developers from worrying about resource scheduling, interprocess communication, security, self-healing, load balancing, and many other tedious (but important!) tasks. 

Consider just a couple examples of benefits that containerization brings to network functions. First, when upgrading the network function to implement new features, you no longer need to re-deploy the entire network function. Instead, you only need to re-deploy the containers that are affected by the upgrade. This improves developer velocity and reduces the risk of the upgrade because, rather than infrequent upgrades that each introduce substantial changes, you can now have frequent upgrades that each deploy small changes. Small changes are less risky because they are easier to understand and to roll back in case of anomaly. Incidentally, this also improves your security posture because it reduces the time between when a security vulnerability is discovered and when a patch is deployed.

Speaking of security, another example of the benefits that containerization brings to network functions is an automatic zero-trust security posture. In Kubernetes, the communication among microservices can be handled by a service mesh, which manages mundane aspects of inter-services communication such as retries in case of failure and providing observability into communication. It can also manage other essential aspects such as security. For example, Anthos Service Mesh, which is a fully-managed implementation of the open-source Istio service mesh (also co-developed by Google), includes the ability to authenticate and encrypt all communications using mutual TLS (mTLS) and to deploy fine-grained access control for each individual microservice.

Automation and orchestration for cloud networks

CNFs bring tremendous benefits, but they also bring challenges. In place of a relatively small number of network appliances, we now have a large number of containers, each of which requires configuration, management, and maintenance. In the past, many of these processes were accomplished using manual techniques, but this is impossible to accomplish economically and reliably at the scale required by CNFs.

Fortunately, there are cloud-native approaches to solving these challenges. First, consider the problem of autonomously deploying and maintaining CNFs. The ideal way is to use the concept of Configuration as Data. Unlike imperative techniques such as Infrastructure as Code, which provide a detailed description of a sequence of steps that need to be executed to achieve an objective, Configuration as Data is a declarative method whereby the user specifies the desired end state (i.e., the actual desired configuration) and relies on automated controllers to continuously drive the infrastructure to achieve that state. Kubernetes includes such automated controllers, and the great news is that this method can be used not just for infrastructure but also for the applications residing on top of it, including CNFs. This cloud-native technique frees you from the toil and associated risk of writing detailed configuration procedures, so you can focus on the business logic of your applications.

As another example, consider the problem of understanding your network performance, including anomaly detection, root cause analysis, and resolution. The cloud-native approach starts with creating a data platform where both infrastructure and CNF monitoring data can be ingested, regularized, processed, and stored. You can then correlate data sets against each other to detect anomalies, and with AI/ML techniques, you can even anticipate anomalies before they happen. AI/ML is likewise indispensable in gaining an understanding of why the anomaly is happening, i.e. performing root cause analysis, and automated closed-loop controllers can be developed to correct the problem, ideally before it even happens.

Architecting for the edge

The transition from VNFs to CNFs is a critical piece in addressing the challenge that CSPs face today, but it alone is not enough. CNFs need infrastructure to run on, and not all infrastructure is created equal. 

Consider a typical 5G network. There are some functions, such as those associated with an access network, that need to be deployed at the edge. These functions require low latency, high throughput, or even a combination of the two. In 5G networks, examples of such functions include the radio unit (RU), distributed unit (DU), centralized unit (CU), and the user plane function (UPF). The first three are components of the radio access network (RAN), while the last is a component of the 5G core. At the same time, there are some other control plane functions such as the session management function (SMF) or the authentication and mobility management function (AMF) that do not have such tight latency and high throughput requirements and can thus be placed in a more centralized data center. Furthermore, consider an AI/ML use case where a particular model (perhaps for radio traffic steering) needs to run at the network edge because of its latency requirements. While the model itself needs to run at the edge, model training (i.e., generating the model coefficients) is frequently a compute-intensive exercise that is latency-insensitive and is thus more optimal to run in a public cloud region.

All of these use cases have one thing in common: they call for a hybrid deployment environment. Some applications must be deployed at the edge as close to the user as possible. Others can be deployed in a more centralized environment. Still others can be deployed in a public cloud region to take advantage of the large amount of compute and economies of scale available therein. Wouldn’t it be convenient — if not transformational — if you could use a single environment for deploying at the edge, in a private datacenter, and in public cloud, with a consistent set of security, lifecycle management, policy, and orchestration resources across all such locations? This is indeed what Google Distributed Cloud, enabled by Anthos, brings to the table.

With Google Distributed Cloud, you can architect a 5G network deployment such as the one shown below.

Business benefits of cloud networks

Beyond the technical benefits, consider the business benefits of such an architecture. First, by following the best practices of hardware and software disaggregation, it permits the CSP to procure the infrastructure and the network functions from different vendors, spurring competition among vendors. Second, each workload is placed in precisely the right location, enabling efficient utilization of hardware resources and offering compelling low-latency, high-throughput services to users. Third, because the architecture utilizes a common hybrid platform (Anthos), it makes it easy to move workloads across infrastructure locations. Fourth, the separation of workloads into microservices accelerates time-to-market when developing new features or applications, such as those enabling enterprise use cases. And finally, the container management platform supports the simultaneous deployment of both network functions and edge applications on the same infrastructure, allowing the operator to deploy new experiences such as AR/VR directly on bare metal as close to the user as possible.

The next generation cloud network is now

There is a lot more we could say, but perhaps the most important takeaway is that this architecture is not a future dream. It exists today, and Google is working with leading CSPs and network vendor partners to deploy it, helping them realize the promise of 5G to deliver new revenues, reduce operating costs, and enable new customer experiences.

To learn more, watch the video series on the cloudification of CSP networks.

Discover what’s happening at the edge: How CSPs Can Innovate at the Edge.

^{1.Statista, Forecast growth worldwide telecom services spending from 2019 to 2024
2 PricewaterhouseCoopers, Global entertainment and media outlook 2021-2025
3. Borg: The Predecessor to Kubernetes}

A subsidiary of United States-headquartered corporation Yum! Brands, Pizza Hut prides itself on serving more pizzas than any other pizza business. Founded in 1958, Pizza Hut operates 18,000 restaurants in over 100 countries. In the Indian subcontinent, Pizza Hut and franchise partners Devyani International and Sapphire Foods India operate more than 500 pizza restaurants, including 430 in India itself.

Yum! Brands aims to increase the number of Pizza Hut restaurants in India to 700 by 2022 and has nominated the country as one of the keys to its future growth. The business also operates the KFC and Taco Bell brands in India.

“Globally we are the number one pizza chain in the world based on store count and we aim to be the single biggest pizza brand in India,” says Prashant Gaur, Chief Brand and Customer Officer, Pizza Hut India Subcontinent.

Google Cloud Results

• Maximizes customer coverage and helps ensure riders deliver pizzas to customers within required timeframes
• Onboards new stores to delivery in half a day, rather than the one month required previously
• Meets tech-savvy customer demands to interact across new social media messaging channels
• Launch of live tracking delivers superior customer experience, driving positive word of mouth and repeat business

Pizza Hut launched initially in the country in the late 1990s as a dine-in restaurant brand. However, with changing customer needs, Pizza Hut soon included delivery and takeaway to provide customers with the best tasting pizzas whenever and wherever they wanted them. “Pizza is always at the center of the experience, whether through delivery, dine-in, or takeaway,” says Gaur. “Convenience is key in allowing people to access our products.”

Manual processes

While the business had long shifted into a model that featured delivery and takeaway options, it still used some manual processes. For example, some restaurants used manual listings of customer addresses to manage delivery, which ended up excluding some customers and compromising the brand. In other cases it could take the business up to a week to create a trade zone – a delivery zone assigned to a restaurant – for each new outlet, delaying the commencement of delivery services and costing the business money.

In addition, Pizza Hut India identified an opportunity to more closely track whether pizzas were being delivered within targeted timeframes.

“In some cases, we were using a manual, self-reporting mechanism that provided information about the number of orders that reached consumers less than 30 minutes after an order was placed,” explains Ashish Agarwal, Director, Technology and eCommerce, Pizza Hut India Subcontinent. “We wanted to objectively track and verify delivery times.”

Manual order tracking and execution also limited the number of orders that could be processed effectively during demand peaks. Further, customers could not monitor the status of their pizza orders, including estimated time of arrival.

“Millennial consumers expect products and services to be available when and where they want them. Our focus is to retain the heritage of the brand, which is the dine-in environment, legendary service, and great assets in terms of our stores, while responding to this demand,” adds Gaur.

Pizza Hut India also needed improved analytics in order to identify where the best returns could be achieved by opening new restaurants; how to improve the customer experience; and operate more efficiently.

The business decided to implement a transformation program underpinned by two imperatives: the need to deliver operational efficiencies and scale faster by accelerating the opening of new stores, and the need to give consumers the option of connecting with the brand using the most convenient channel.

A ground-breaking initiative

Pizza Hut India evaluated potential technology partners that could help deliver the program and decided to partner with digital consulting services company MediaAgility, and use Google Maps Platform and Google Cloud Platform services.

“Our journey with MediaAgility and Google incorporated two key initiatives that had a specific impact on our brand and consumers,” says Gaur. “The first of these initiatives was the launch of a feature that enabled consumers and our business to track delivery riders in real time.”

This initiative was ground-breaking for a business that had, until recent years, focused on establishing itself as a restaurant brand. However, with delivery an increasingly important part of its revenue mix, Pizza Hut India decided to build customer engagement through the channel. “By allowing customers to track delivery riders in real time, we could improve engagement – but more importantly give them control,” says Gaur.

During the evaluation, MediaAgility demonstrated Google Maps Platform to Pizza Hut India. “We loved Google Maps Platform as its accuracy and value was proven by consumers using Google Maps for their day-to-day needs,” says Agarwal.

Pizza Hut India conducted brainstorming sessions with MediaAgility and its franchise partners to develop its strategy and complete the implementation. The business then completed several proofs of concept to determine how best to deploy and adapt the technology to some operational processes. “We submitted some data points to our franchise partners and our Pizza Hut brand operations team, and they determined which option to adopt,” says Agarwal.

Google Maps Platform powers delivery

MediaAgility, Pizza Hut India, and the franchise partners then completed a three-month implementation that included onboarding all existing restaurants and new restaurants to the delivery platform based on Google Maps Platform and on Google Cloud Platform.

Pizza Hut India now uses Distance Matrix API through Google Maps Platform to provide travel time and distance based on recommended routes between origins and destinations. This service helps provide delivery riders’ estimated time of arrival to customers.

Directions Service calculates directions by communicating with the Google Maps API Directions Service, which receives direction requests and returns efficient paths based on travel time and factors such as distance and number of turns. This service provides a view of the delivery rider’s position relative to the customer’s location.

Through the Nearest Roads service included in Roads API, Pizza Hut India obtains individual road segments for given GPS coordinates, while Snap to Roads provides the best-fit road geometry for given GPS coordinates.

The business employs Maps Javascript API to customize maps with dedicated content and imagery for websites and mobile devices – showing a map view to store managers and customers – and uses Maps SDK for Android to add maps based on Google Maps to its applications.

Google Cloud Platform runs the delivery platform

Pizza Hut India is running its delivery platform on a Google Cloud Platform architecture that comprises App Engine to run its web applications; virtual machine instances provided through Compute Engine; Cloud Datastore to run a NoSQL document database; Firebase to develop and run its mobile applications; Cloud Storage to store data; and a BigQuery analytics data warehouse.

Realizing goals

With Google Maps Platform and Google Cloud Platform, Pizza Hut India and its franchise partners are realizing the goals of the transformation program.

Rather than take up to seven days to manually map trade zones for stores, Pizza Hut India uses Google Maps Platform to create and update them as required. “After we started working with MediaAgility and Google, we digitized those maps and created trade zones – zones within which Pizza Hut India restaurants will deliver – based on estimated travel times during the busiest time of the week,” says Gaur. “This minimizes the risk of late deliveries.

“The other benefit was reduced time to activate new stores,” he adds. “If you are launching 100 stores per year, this becomes a big, big task. Now we can bring new stores into the market much more quickly.”

With MediaAgility and Google Maps Platform, the business can also help ensure newly built establishments – such as blocks of flats – are captured within trade zones, allowing stores to deliver to residents.

Delivery accounts for increased transactions

Pizza Hut India now automatically allocate orders to delivery riders using a rider tracking application on their mobile phones. When a rider starts his or her journey, Google Maps Platform enables point-by-point tracking by consumers and store managers. The Pizza Hut India delivery operations team monitors delivery performance through a real-time dashboard.

Pizza Hut India is meeting customer expectations of live, map-based streaming of delivery status on their devices – enhancing customer experience and loyalty, and adding accountability to the process. The business is reaping the rewards of its investment, with delivery now a large slice of its overall offering. “We have taken significant strides in the past three to four years to change our customers’ online ordering experience, and the last-mile delivery experience to the customers’ homes,” says Gaur.

Launching delivery tracking has also had a dramatic impact on Pizza Hut India’s internal key performance indicators. “The proportion of calls to our call center that are following up on an order, as opposed to placing an order, has fallen dramatically,” says Gaur.

Advanced analytics

Further, Pizza Hut India is running advanced analysis of data in the BigQuery data warehouse, enabling the business to determine which restaurants are doing well, which deliveries may be delayed, and what locations are most promising to open a new store. These insights enable the business to boost productivity, expand effectively, and operate more efficiently.

The business can now onboard new stores to delivery in half a day, rather than the month required previously. “The process enabled by Google Cloud and MediaAgility is also delivering significant operational cost savings as well as helping us open and grow new stores quickly,” says Agarwal.

“MediaAgility acted as our development partner across the project, helping us deploy everything from zones to rider tracking,” he says. “It’s been with us from the strategy discussion through the implementation and stabilization phases.”

Chatbot in development

MediaAgility has also helped Pizza Hut India create a chatbot using the Dialogflow development suite for creating conversational interfaces. “This project is about giving millennials and other customers one more channel to reach out and connect to the brand,” explains Agarwal.

Pizza Hut India is now ideally placed to continue growing and position itself as a brand of choice for tech-savvy consumers. “We’re extremely pleased with the contribution of all the parties involved in this project and look forward to continue transforming our business to meet the demands of the digital age,” says Agarwal.

While Gaur acknowledges it is difficult to predict change over the next two to five years, he believes delivery is likely to become more prominent in Pizza Hut India’s combination of offerings. “When we began our online journey in 2016, we predicted delivery would be about 25 percent of the mix by 2020,” he says. “With Google and MediaAgility, I think it will keep growing.”