Retail organizations constantly face financial pressure to increase sales while maintaining profit margins. Digital commerce creates new opportunities and a more competitive landscape for retailers by allowing them to reach a global customer base online, but it also exposes them to competition from larger online retailers. To be successful in this environment, retailers must not only have a strong online presence to keep up with their competition and gain market share, but also uplift the transactional customer experience to a more experiential one.

In today’s data-driven artificial intelligence-inspired business environment, organizations require complex IT infrastructure to support various functions such as prospecting, product development, marketing, and data analytics. Managing and scaling this infrastructure can be challenging, especially as needs evolve. As a result, many organizations are turning to Google Cloud as a solution for meeting their business goals, rather than simply expanding their in-house IT resources with more equipment and personnel. Specifically, retailers across the globe are betting on Kubernetes on Google Cloud to take advantage of secure, reliable, and scalable infrastructure.

Here are a few examples of worldwide retailers adapting to changing customer expectations using intelligent infrastructure solutions including Google Kubernetes Engine (GKE), the most scalable and automated fully managed Kubernetes from Google Cloud.

Haravan is a Vietnamese ecommerce platform that aims to improve the process of buying and selling products, allowing businesses to focus on creating and selling their products.

By using Google Cloud, Haravan helped small and medium-sized enterprises in Vietnam achieve double-digit growth, consistently met its 99.97% uptime commitment to clients, efficiently managed 5 times the normal amount of ecommerce activity, and facilitated the implementation of artificial intelligence-powered expansion plans.

“We have a guaranteed commitment to enable any volume of sales for clients over all channels, be it social networks, marketplaces, livestream, or website. Only Google Cloud, with the flexible autoscaling of GKE, gives us certainty to meet our guarantees even in the most massive Black Friday surges.” —Hung Le, VP of Software Engineering, Haravan

Loblaw is Canada’s food and pharmacy leader and the nation’s largest retailer. The company operates over 2,500 locations, including corporate, franchised, and associate-owned stores, and employs nearly 200,000 full- and part-time employees.

By using Google Cloud, boosted the performance of the online grocery platform, resulting in higher conversion rates and increased revenue, recovered up to 50% of Site Reliability Engineers’ time for innovation, introduced new, real-time personalization features and shopping conveniences for customers, and enhanced resiliency to protect customers and revenue.

“Moving our online grocery site to Google Cloud gave us a 4x performance increase and the capacity to handle up to three times the traffic; and we can scale up at any time.” —Hesham Fahmy, VP Technology, Loblaw

L.L.Bean is a North American retail company known for its boots and mail-order catalog, which dates back to 1912. The company has a strong online presence, with ecommerce accounting for $1 billion of its annual revenues of $1.6 billion. Like many other retailers, L.L.Bean is adopting an omnichannel sales strategy by interacting with customers through various channels including print, physical stores, its website, app, and social media.

By using Google Cloud, L.L.Bean enhanced customers’ online experience through faster page load times and access to transaction history, allowed for a focus on providing value to customers rather than managing infrastructure, and enabled the rapid release of cross-channel services by reducing development cycles.

“GKE has significantly streamlined the process of upgrading nodes and masters. By comparison, upgrading even minor releases of another container solution that L.L.Bean tested resulted in the need to rebuild that solution’s clusters four times.” —Randy Dyer, Enterprise Architect, L.L.Bean

LPP is a Polish fashion retailer established in 1991 by Lubianiec and Piechocki, whose initials make up the company’s name. LPP currently manages five clothing brands that are popular in 38 countries across Europe, Africa, and Asia, and has over 24,000 employees based in its main offices in Central and Eastern Europe. Growing demand for its ecommerce services led LPP to migrate from an on-premises setup to Google Cloud, harnessing automation to ensure great shopping experiences globally.

By using Google Cloud, LPP promoted a DevOps culture among developers through streamlined deployment of new features, provided 90% more time for engineers to work on innovative solutions instead of managing infrastructure, instantly created and updated new VMs, allowing developers to quickly launch new features, ensured a seamless online shopping experience by automatically adjusting capacity to meet demand.

“GKE enables us to deploy new features for our ecommerce sites very quickly. Previously, it took weeks to launch new instances for each brand. Today, it takes seconds: we simply launch a new machine, deploy the code, and changes are reflected automatically across our environment.” —Marek Maciejewski, Head of IT Service Operations, LPP

Noon.com, based in Riyadh, Saudi Arabia, is a local ecommerce marketplace focused on serving the Middle East. The company aims to become the top online retailer in the region, supporting the growth of a digital economy for both consumers and local businesses.

By using Google Cloud, Noon.com built its ecommerce platform to access self-managed services, allowed developers to establish a fully operational staging environment within two weeks, provided uninterrupted service to nearly four times as many daily users during busy seasons using autoscaling on GKE, used real-time data streaming on BigQuery to inform business decisions and personalize the customer experience, and achieved 99.999% availability with no downtime for planned maintenance or schema changes using a fully managed relational database.

“Google Cloud-managed services are playing a major role in enabling Noon.com customers to get their shopping done whenever they need it, without experiencing any delays or glitches, and without us having to lose sleep at night to ensure our platform is functioning as it should.” —Alex Nadalin, SVP of Engineering, Noon.com

In conclusion, the retail industry is constantly evolving and retailers must stay up-to-date with the latest technology and customer preferences to remain competitive. Digital commerce has changed the landscape of retail, allowing businesses to reach a global customer base but also increasing competition. The use of Kubernetes on Google Cloud can help retailers improve the customer experience, streamline internal processes, and make data-driven and AI-inspired decisions. By embracing these changes, retailers can stay ahead in a constantly evolving industry. Get started today with an exclusive workshop, Unlocking efficiency and innovation with Kubernetes on Google Cloud.

Based in Mountain View, California, Khan Academy is a not-for-profit that produces and posts a vast collection of free educational online videos about math and science topics ranging from algebra and trigonometry to biology and economics.

Millions of students, educators, and self-learners around the world watch the videos, both on the Khan Academy’s YouTube channel and on its hugely popular website (www.khanacademy.org), where students answer some 1.5 million practice questions per school day. The Khan Academy development team continually tweaks the site based on how visitors choose to learn.

Challenge

Khan Academy’s beginnings date back to 2004, when Sal Khan’s cousin asked him to remotely tutor her daughter in math. Khan was happy to help and more than qualified, given his three MIT degrees and his Harvard MBA.

As more relatives and friends asked Khan for tutoring assistance, he began videotaping short lessons and posting them to YouTube. His knack for distilling complex concepts into easy-to-follow tutorials helped the videos go viral.

Sal knew he needed to offload the technical and maintenance concerns so he could work on what was important. To grow, it was important for him to be able to stop worrying about things like deployment issues and running his own server.

Ben Kamens, lead developer for Khan Academy

Khan maintained a website for his growing video library for several years, but the platform experienced limitations as traffic increased.

At the same time, media attention was growing, and technology industry leaders, including Microsoft founder Bill Gates and Silicon Valley venture capitalist John Doerr, began lending their support and evangelizing Khan’s mission and work. It was at this point that Khan quit his job as a hedge fund analyst to devote his full-time attention to the site’s growing potential.

“With Google App Engine, we don’t need a system administrator or anyone dedicated to deploying our app, so 99 percent of our time is spent working on our application,” says Ben Kamens, lead developer, Khan Academy.

“Sal knew he needed to offload the technical and maintenance concerns so he could work on what was important, which was to make more videos for the Khan Academy library,” explains Ben Kamens, lead developer for Khan Academy. “To grow, it was important for him to be able to stop worrying about things like deployment issues and running his own server.”

Solution

Khan Academy chose App Engine as its hosting and application development platform because App Engine could easily house its growing collection of 2,000-plus videos, resolving the organization’s overall server and maintenance issues with a single solution.

Using App Engine freed the team to focus on the user experience and the array of content that makes the academy such a powerhouse.

“A lot of what the Khan Academy is about is collecting data on student behavior so we can teach them better,” Kamens says. “Did they use a hint? Have they watched the video before? That data is being stored on Google App Engine so we can figure out what the most effective videos are, or where students struggle the most.”

Khan Academy provides individual profiles to students so they can analyze their learning progress, which means the organization needs systems running in the background to collect and track of all this data. Because App Engine takes care of server support, Khan Academy’s five developers can spend almost all of their time improving site functionality.

“If we didn’t have Google App Engine, we’d be spending a lot more time figuring out server setup and working on routers,” Kamens says. “Our ability to focus on the actual product is the benefit of Google App Engine.”

With the App Engine dashboard, which provides information like response time, uptime, and error rates, the development team also has an easy way to watch over site performance. “It lets us see what the average response time is, so we can keep it really low,” Kamens explains.

Results

During the US school year, Khan Academy receives more than 3.8 million unique visits a month — all served through App Engine. To support this much traffic, a typical company would need an internal system administration staff.

“With Google App Engine, we don’t need a system administrator or anyone dedicated to deploying our app, so 99 percent of our time is spent working on our application,” explains Kamens. “Our application lives on Google App Engine, and we bank all of our scalability and traffic concerns on Google App Engine. Even huge traffic spikes from Sal’s media appearances don’t worry us since we know that Google App Engine will handle the spike.”

Kamens also likes the fact that he and his team can turn to the Google App Engine support team for assistance when they need it. He also finds helpful tips on the Google App Engine blog.

The Khan Academy staff has come to completely rely on App Engine. “We are constantly using more of Google App Engine’s capabilities and have been happy with the performance,” Kamens says. “It’s nice to have an easy deployment process since we deploy the site on average at least once a day, [and] sometimes up to nine or 10 times [a day].”

If you build apps and services that your customers consume, two things are certain: 

1. You’re exposing APIs in some form or the other. 
2. Your apps are made by multiple functions working together to deliver products and services. 

As you scale up and grow, your enterprise architecture can benefit from a sound strategy for both API management and service management, both of which impact your customer and developer experience. In this article, we’ll explore how these two technologies fit into your application modernization strategy, including how we’re seeing our customers use Anthos Service Mesh and Apigee API Management together. 

How APIs, microservices, and a service mesh are related

APIs accelerate your modernization journey by unlocking and allowing legacy data and applications to be consumed by new cloud services. As a result, organizations can launch new mobile, web, and voice experiences for customers. 

The API layer acts as a buffer between legacy services and front-end systems and keeps the front-end systems up and running by routing requests as the legacy services are migrated or transformed into modern architectures.  In addition, an API management platform, like Apigee, manages the lifecycle of those APIs with design, publish, analyze, and governance capabilities.

Once microservices architectures become prevalent in an organization, technical complexity increases and organizations find a need for deeper and more granular visibility into their applications and services. This is where a service mesh comes into play. 

A service mesh is not only an architecture that empowers managed, observable, and secure communication across an organization’s services, but also the tool that enables it. Anthos Service Mesh lets organizations build platform-scale microservices with requirements around standardized security, policies, and controls, and it provides teams with in-depth telemetry, consistent monitoring, and policies for properly setting and adhering to SLOs. 

How API management and a service mesh compliment one another

Many organizations ask themselves, “Do I really need both an API management platform and a service mesh? How do I manage them together?” 

The answer to the first question is yes. These two technologies focus on different aspects of the technology stack and are complementary to each other. A service mesh modernizes your application networking stack by standardizing how you deal with network security, observability, and traffic management. An API management layer focuses on managing the lifecycle of APIs, including publishing, governance, and usage analytics. 

Most organizations draw a logical boundary at business units or technology groups. Sharing these microservices outside that boundary with other business units or with partners is where Apigee plays a significant role. You can drive and manage the consumption of those services through developer portals, monitoring API usage, providing authentication, and more, with Apigee. 

Google Cloud offers Anthos Service Mesh for service management and Apigee for API management. These two products work together to provide IT teams with a seamless experience throughout the application modernization journey. The Apigee Adapter for Envoy enables organizations that use Anthos Service Mesh to reap the benefits of Apigee by enforcing API management policies within a service mesh. 

Accelerate your application modernization journey

Though the journey to application modernization doesn’t always follow a clear-cut path, by adopting API management and a service mesh as part of a modernization journey, your organization can be better equipped to rapidly respond to changing markets securely and at scale. 

Wherever you are on your application modernization journey, Google Cloud can help. To learn more about how service management and API management can be part of your application modernization journey, read this whitepaper.

Cloud Functions is a fully managed event-driven serverless function-as-a-service (FaaS). It is a small piece of code that runs in response to an event. Because it is fully managed, developers can just write the code and deploy it without worrying about managing the servers or scaling up/down with traffic spikes. It is also fully integrated with Cloud Operations for observability and diagnosis. Cloud Functions is based on an open source FaaS framework which makes it easy to migrate and debug locally. 

To use Cloud Functions, just write the logic in any of the supported languages (Go, Python, Java, Node.js, PHP, Ruby, .NET), deploy it using the console, API or Cloud SDK and then trigger it via HTTP(s) request from any service, for example: file uploads to Cloud Storage, events in Pub/Sub or Firebase, or even direct call via Command Line Interface CLI. 

There is a generous free tier and the pricing is based on number of events, compute time, memory and ingress/egress requests and costs nothing if the function is idle. For security, using Identity and Access Management IAM you can define which services or personnel can access the function and using the VPC controls you can define network based access. 

Cloud Functions use cases

Some Cloud Functions use cases include:

• Integration with third-party services and APIs
• Asynchronous workloads like lightweight ETL
• Lightweight APIs and webhooks
• IoT processing and update of the sensors/devices in the field
• Real-time file processing for use cases such as media transcoding or resizing as soon as the file is uploaded in Google Cloud Storage.
• Real-time ML solutions for use cases such as media translation or image recognition for files uploaded in GCS.
• Backend for chat applications and mobile apps.

Firebase Functions and Cloud Functions, are they different?

 If you are a Firebase developer, you’d probably use Firebase Functions. Those are created from the Firebase dashboard / website. Both Cloud Functions and Firebase Functions can do the same things, they just have slightly different signatures and slightly different ways of deploying. Firebase Functions have a local emulator, which Cloud Functions uses the Functions Framework.

For a more in-depth look into Cloud Functions check out the documentation.  Once you’ve got your Function up and running, check out some tips and tricks.https://www.youtube.com/embed/LTMChfWBHb0?enablejsapi=1&

For more #GCPSketchnote, follow the GitHub repo. For similar cloud content follow me on Twitter @pvergadia and keep an eye out on thecloudgirl.dev