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.

Founded in 2015, Rapido operates a mobile app-based two-wheeler taxi service across more than 40 cities in India. More than 100,000 drivers provide Rapido two-wheeler taxi services, while more than 400,000 current or prospective drivers have downloaded the company’s app. Consumers have downloaded the app more than 5 million times, and the business receives about 5 million orders per month for taxi services.

“If a consumer wants to travel from point A to point B, they simply open up the app on their smartphone, select pickup and dropoff locations, and tap ‘request,'” explains Rishikesh SR, Co-Founder, Rapido. “We can track that request to the nearest available two-wheeler taxi and allocate the job to the right driver.”

Google a compelling opportunity

The business started operations on a cloud service. However, Google presented a compelling opportunity to Rapido to improve its location-based intelligence through a wide range of cloud-based map APIs, infrastructure, and mobile app development services. “Google Maps Platform was particularly interesting to our business and we saw enormous potential to use it to improve our service and gain a competitive edge,” says Rishikesh.

Rapido elected to use Geocoding API to enable its app to convert addresses to geographic coordinates, and the reverse, allowing consumers to identify point A and point B on their journey. The company also uses Directions API to identify the fastest route between pickup and dropoff locations, which enables Rapido to provide users with approximate prices for trips. Distance Matrix API is used to calculate the travel times and distances between locations, and Maps SDKs for Android and iOS to add interactive maps to the app.

Google Cloud Results

• Enables the business to optimize use of Maps Platform APIs
• Takes 5 million orders per month
• Establishes a robust platform for expansion

“Google Maps Platform is particularly useful for us as it identifies optimum routes for two-wheel services,” says Rishikesh. “This saves us time and money, while helping us deliver a better consumer experience.”

In addition, Rapido uses the Snap to Roads service to deliver best-fit geometry for sets of GPS coordinates within the Roads API, which identifies and provides metadata about the roads on which drivers travel. “Snap to Roads in Roads API allows us to optimize the path drivers take and helps ensure the fare charged is accurate,” says Rishikesh.

Improving user experiences

As Rapido matured, Rishikesh considered how to improve the user experience of the app while reducing the business’ costs. In 2017, Rapido asked Google Cloud Premier Partner and Google Maps Platform Partner Searce to help meet these objectives. Searce provided the technical and business advice that prompted Rapido to take advantage of the unlimited API calls, 24-hours-a-day, 7-days-a-week support, and strict SLAs available through the Google Maps APIs Premium Plan for Asset Tracking.

Searce also helped Rapido optimize its API calls and integrate directions and distance calls with the Roads API to smooth out variations in GPS readings received from the handsets of two-wheeler taxi owners. Finally, Searce helped Rapido deploy the Firebase mobile and web development platform to automate the mode configuration of the API keys, rather than maintain a time-consuming manual process. This move also minimized the likelihood of any issues arising if Rapido decided to start multiple projects or add more licenses, or combine Google Maps APIs Premium Plan for Asset Tracking with an external license.

Technical skill and experience

Searce finalized its initial engagement with Rapido last year and provides ongoing support and advice. “Searce’s technical skill with Google Maps Platform put us on the right path to provide a better, more relevant user experience,” says Rishikesh.

Rapido also now uses a range of Firebase services for app development, testing, and modification. The business employs Google Analytics for Firebase to measure customer use of and engagement with its app, enabling the business to make informed decisions about where to direct its resources. In addition, the business is using the Firebase Test Lab app-testing infrastructure to test its Android and iOS apps across a range of device configurations, view the outcomes, and make changes as needed.

Rapido uses Firebase Remote Config to change the app’s behavior and appearance on the fly in response to the results of A/B testing across sections of its user base. Furthermore, Rapido uses Firebase Crashlytics to provide app crash reports to its Firebase console.

Firebase Dynamic Links allows Rapido to direct users to linked content in the iOS or Android version of the app, while Firebase Cloud Messaging enables Rapido to deliver notifications and other messages to users. Cloud Firestore provides a NoSQL cloud database to store and sync data for the Rapido app.

Rapido has also started using the Firebase Realtime Database to store and sync information about customers that can be used to provide a more informed, personalized service.

At the same time, Rapido uses a BigQuery data warehouse to process about 10TB of data every month for analysis and reporting that supports decision-making across the business. The organization is also using application containerization through Google Kubernetes Engine on Google Cloud Platform.

“We are moving our apps from dedicated virtual machines to a scalable containerized environment that consumes fewer resources,” says Rishikesh. “It makes sense to work with Google – the business that designed the Kubernetes container-orchestration system.”

Rapido has also started using the Cloud Functions event-driven serverless compute platform to process smaller jobs. “This is ideal for small use cases in particular as we do not have to spin up virtual machine instances,” says Rishikesh.

Finally, Rapido is using image classification through the Vision AI service to analyze riders’ documentation, such as driving licenses. This allows the business to verify details such as names, addresses, and expiry dates with more than 90 percent accuracy – a high rate in a country where each state has its own license template.

Expanding rapidly to new cities

The Rapido app enables drivers to pick up customers quickly – in most cases, between 2 and 5 minutes.

Overall, the high-quality experience for consumers and drivers delivered by Google Maps Platform, combined with Firebase, has helped power Rapido to robust growth. The business now takes more than 5 million orders per month.

“With Google, we are delivering the right experience to users through Google Maps Platform, Firebase, and Google Cloud Platform services,” concludes Rishikesh. “We have realized our vision faster and now have a robust platform to grow in the future.”

Digital technology offers increasing flexibility and choice to consumers. As a result, the retail industry is dramatically shifting toward more tailored and personalized experiences for shoppers, and businesses are rethinking how they deliver value to customers.

This couldn’t be more true for the beauty retailing industry where leading companies are turning to digital technology to create customized shopping experiences.

At Google Cloud, we’re particularly excited about our work with Ulta Beauty, the largest beauty retailer in the United States with more than 1196 stores in all 50 states, and how the company is using Google Cloud technology solutions to power personalization and redefine beauty retailing.

Established in 1990, Ulta Beauty has had incredible success as a company, and as customers become more discerning and curious about their purchases, the company is finding new ways to meet their changing needs.

Recently, leaders at Ulta Beauty recognized a huge opportunity to complement and enhance the shopping experience by helping beauty enthusiasts navigate through more than 500 brands and 25,000 products carried in their stores and online channel.

They decided to leverage the data from Ulta Beauty’s successful Ultamate Rewards loyalty program to create and offer more unique and personalized user experiences.

With more than 30 million members generating data through sales, transactions, product reviews, and social media engagement, Ulta Beauty’s Loyalty Program creates a comprehensive data set, and the company sought the right technology partner to help organize, analyze and transform that data into valuable insights for its customers.

Ulta Beauty’s leaders knew they had an opportunity to leverage data analytics and machine learning to reach customers in new ways, enhance the guest experience, and continue to grow their active loyalty member base. After considering a number of cloud providers, they chose to expand their existing partnership with Google Cloud.

“Google Cloud listened to our needs and worked in tandem with our engineering team to address our challenges,” said Michelle Pacynski, vice president of digital innovation at Ulta Beauty. “The ease of working with the Google Cloud team and their breadth of experience made the decision a no-brainer, laying the foundation for a great partnership.”  

In 2019, Ulta Beauty announced it was working with Google Cloud Platform to unify and organize its data, using:

• BigQuery to perform data analysis and generate dynamic content, personalized product recommendations, and event-based messages for customers.
• Cloud Storage to provide highly available, secure, resilient and cost-effective access to data across the entire enterprise.
• Compute Engine for the high-performance scalability needed to grow with customer demand while painlessly migrating existing applications to the cloud.
• Anthos to build a hybrid cloud foundation that allows their applications to take advantage of all this data, combining the power and flexibility of GKE with the ability to leverage their existing investment in secure infrastructure on-premises.

Our partnership with Ulta Beauty has enabled increased engagement with customers in store and online, and the creation of new tools and capabilities, including a new Virtual Beauty Advisor tool to deliver tailored recommendations and help shoppers choose the right products, and a Customer Conversation Platform that’s enabling deeper connections with guests, ultimately driving customer loyalty.

“It’s been a really efficient process so far due in part to the ease of working with the Google team,” said Michelle Pacynski, vice president of digital innovation at Ulta Beauty. “They’re experienced, approachable, and their can-do style makes for a great partnership. They listened to our needs and worked in tandem with our engineering team, figuring things out, and getting it done.”

Most enterprise companies enforce strict requirements for how APIs should be exposed to the public internet that require centralized handling of the authentication credentials, the collection of metrics metrics and other classic API management capabilities. Before the introduction of sidecars in Cloud Run, developers either had to implement these requirements within the service itself or add a full-lifecycle API management platform in front of their service as described in a previous blog post.

In this post we want to demonstrate a new way to fulfill the requirement for API management in Cloud Run. Specifically we want to look at how the recently announced multi-container feature in Cloud Run enables a sidecar pattern that can be used by developers of Cloud Run services to add pre-packaged API management capabilities. This includes self-service developer onboarding in a developer portal, credential validation and quota enforcements. As an additional operational benefit the described solution also adds centralized analytics and metrics for APIs that are exposed via Cloud Run.

Our solution for adding API management capabilities for Cloud Run is provided by the following three components:

• The Cloud Run service that hosts a traditional RESTful web application and is fronted by a vanilla Envoy proxy.
• An Apigee Envoy Adapter aka. Remote service that runs in GKE Autopilot and acts as a policy decision point PDP for Envoy’s external authorization filter and is responsible for accepting or rejecting calls to the Cloud Run service.
• An Apigee API Platform that is used to manage the API lifecycle of the Cloud Run service. Apigee also offers a turn-key developer portal where developers can obtain access credentials to access an API.

The user journey of an incoming request to our new Cloud Run Service with API management looks as follows:

1. An API Developer self-registers in the Apigee Developer Portal and obtains access credentials for the API
2. They call the Cloud Run endpoint and provide their credential for authentication
3. In Cloud Run service the Envoy proxy container intercepts the request and initiates a gRPC call to the Apigee Envoy adapter to authenticate the client.
4. The Apigee Envoy adapter verifies the request’s credentials and identifies the corresponding API product as defined in Apigee. The Envoy adapter also verifies the call quota associated with the client and sends the analytics data and access logs back to the control plane.
5. If the credentials are valid and the client hasn’t exhausted their call quota the Apigee Envoy adapter forwards the request to its co-located container in the Cloud Run service.

The step by step instructions for how to configure the architecture above can be found in this blog post. 

Starting from a pre-existing Apigee installation the Apigee Envoy adapter is used to connect back to the Apigee runtime and control plane for accessing the API product definitions to link the incoming requests to the issued credentials and quotas. The Apigee remote service component can be replicated for high availability and is shared between multiple Cloud Run services that require a gRPC target for the sidecar’s external authorization filter.

The Cloud Run service connects to the Apigee Remote Service via an Envoy proxy that acts as a sidecar to the main application. The configuration for the envoy proxy can either be embedded within a customized Envoy image or mounted via the secret manager integration of cloud run as shown in the diagram above. Externalizing the configuration simplifies the maintenance and upgrade of the sidecar container as it can just pull the latest patch version of Envoy regularly.

The newly added API management capability is transparent for the primary application container within the Cloud Run service and does not require any changes in the application source code. Once the Cloud Run service is re-deployed with the sidecar in place, consuming applications can start to use credentials that they obtained via the Apigee API Management platform or the API developer portal to consume the Cloud Run service. At an operations level the platform operators will start to see requests to the Cloud Run service popping up in Apigee’s analytics dashboards and be able to track consumption and exposure at an API product level.

Next Steps

If you are interested in trying the multi-container support for Cloud Run yourself, check out the release announcement with many more use case descriptions. For another example and a detailed walkthrough on how to use sidecars in Cloud Run to report custom metrics to Google Cloud managed service for Prometheus you can head over to this tutorial in the Cloud Run documentation. Lastly, if you’re interested in the broader picture of how the latest features in Cloud Run are moving serverless forward, then make sure you check out this video.

Earlier this year, we launched the Google Cloud skills challenge, which provides 30 days of free access to training to build your cloud knowledge and an opportunity to earn skill badges that showcase your Google Cloud competencies. Today, we’re adding a Native App Development track to the skills challenge, joining the Getting Started, Data Analytics, Kubernetes, Machine Learning (ML) and Artificial Intelligence (AI) tracks. 

The Native App Development track is designed for cloud developers who want to learn to build serverless web apps and Google Assistant applications on Google Cloud using Cloud Run and Firebase. Specifically, you’ll have an opportunity to earn three skill badges in the Native App Dev track: Serverless Firebase Development, Serverless Cloud Run Development, and Build Interactive Apps with Google Assistant. To earn a skill badge, you complete a series of hands-on labs and take a final assessment challenge lab to test your skills.

Here’s an overview of each badge.

Serverless Firebase Development

To earn this skill badge, you’ll learn how to build serverless web apps, import data into a serverless database, and build Google Assistant applications using Firebase, Google’s backend-as-service platform for creating mobile and web applications.

Serverless Cloud Run Development

For this badge, you’ll discover how to use Cloud Run, a fully managed serverless platform, to connect and leverage data stored in Cloud Storage. You’ll learn how to use Cloud Run to build a resilient, asynchronous system with Pub/Sub, build a REST API gateway as well as build and expose services. 

Build Interactive Apps with Google Assistant

To earn the final skills badge, you’ll build Google Assistant applications by creating a project in the Actions console, integrating Dialogflow, testing your action in the Actions simulator, and adding Cloud Translation API to your assistant application. 

Ready to jump into the skills challenge? Sign up here. 

You can also check out this quick video below to learn how to join the skills challenge.