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.

Today we’re hosting our Retail & Consumer Goods Summit, a digital event dedicated to helping leading retailers and brands digitally transform their business. For me, this is a personally exciting moment, as I see tremendous opportunities for those companies that choose to focus on their customers and leverage technology to elevate experiences.

Our event includes breakout sessions to help retailers and brands become customer centric, embrace the digital moment and transform their operations. Some of my favorite sessions include: 

• Why Search Abandonment is the metric that matters, highlighting Retail Search, and featuring a conversation with Macy’s
• Driving Consumer Closeness in a Privacy-Centric World, discussing how retailers and brands can create a successful first party data strategy, featuring a conversation with P&G
• The Modern Store: 7 Innovation Hotspots, sharing how retailers and brands can approach store transformation to unlock the most value from technology, featuring a conversation with The Home Depot.   

I’ll be speaking in our Retail Spotlight session, discussing the current retail landscape and our industry approach, followed by conversations with Albert Bertilsson, Head of Engineering – Edge at IKEA Retail (Indga Group) and Neelima Sharma, Senior Vice President, Technology Ecommerce, Marketing and Merchandising at Lowe’s. 

Let me share a bit more about the topics we’ll discuss in that session.

In retail specifically, digital-first shopping journeys are blurring the lines between the physical and digital brand experience. Shoppers want to know what’s available before they visit your stores, and they expect fulfillment options like curbside pickup. We see this when tracking trends for interest in curbside pickup or in-stock items.

This has left many retailers asking how they can get smarter with their data, tackle the $300 billion dollar problem of “search abandonment,” move faster to create new customer experiences, and do a better job of connecting their employees and customers – with confidence.

Our team has been spending time thinking about how we can rise and succeed in this new era together. We continue to focus on areas where we can bring the best of our capabilities to our retail customers around the world. And we’re focused on ways we can bring the best of what Google has to offer through cloud integrations.

Our goal is to help retailers become customer-centric and data-driven, capture digital and omni-channel revenue growth, create the modern store and drive operational improvement.

Let’s dig into each of these strategic pillars in a bit more detail. 

Become customer centric and data driven

Customers today expect experiences that are timely, targeted, and tailored for them and their needs, and reject experiences that can’t deliver these features. Data modeling, legacy technology, and siloed systems often prevent retailers from providing that level of personalized experience. 

At Google Cloud, we work with global retailers and our ecosystem partners to activate and bring value from first-party data, particularly in the field of customer data platforms (CDPs). This includes integrations from Google Cloud, such as our business intelligence platform Looker and other popular platforms to power one source of customer data through the organization. We also help retailers modernize their data warehouse with Looker for gathering business intelligence across their organization. This is important not just for consumer data, but inventory, supply chain, and store operations as well. 

Capture Digital and Omnichannel Growth 

We power some of the largest e-commerce sites in the world, helping them scale for Black Friday, Cyber Monday, and other holiday events. While scale is critically important, it’s also important to consider the quality of the online experience. How do your customers find products? How can you help deliver seamless online and omnichannel experiences? 

To help, we’re building product discovery solutions that bring together the best of our technologies that help retailers drive engagement with their consumers. Retail Search, for example, gives retailers the ability to provide Google-quality search on their own digital properties – search that is customizable for their unique business needs and built upon Google’s advanced understanding of user intent & context. 

The imperative is clear. Recent research found that retailers lose more than $300 billion to search abandonment — when purchase intent is not converted into a sale due to bad search results — every year in the US alone. 

Today, we announced that Retail Search is available to a larger set of retailers. If you are interested in learning more about Retail Search you can contact your sales representative for additional details.

Create the modern store  

With the rise of buying trends like curbside pickup and proximity-based search, our Google Maps Platform team is working on new products and features to help raise inventory awareness for your shoppers. We want to help you make it easier for them to understand what’s available to purchase in their channel of choice.

With Product Locator, each product page connects customers with information they need for local pickup and delivery options. This ensures customers are aware of pickup and delivery options throughout the buying journey—not just checkout. 

Awareness of local inventory can boost a wide range of key metrics for your business. Shopify recently shared that shoppers who opt for local pickup over delivery had a +13% higher conversion rate and that 45% of local pickup customers make an additional purchase upon arrival.

This is just one quick example of how our Google Maps Platform team can improve experiences for your shoppers.

Operational improvement

It can be challenging to operate in a world and at a time when consumer behavior and supply chains are so disrupted and volatile, and where entire retail teams had to go remote during the pandemic and beyond. 

We’re working with retailers to leverage artificial intelligence (AI) to improve consumer experience through chat bots or conversational commerce that solves problems for customers from anywhere. You can learn more about these offerings in our Conversational Commerce with Google breakout session, featuring Albertsons.

As the need for digital transformation continues to accelerate, Google Cloud is helping retailers stay ahead of the curve with solutions for digital and omnichannel growth, data-driven and customer-focused experiences, and operational improvement. For every era of cloud technologies, from the past into the future, Google Cloud is committed to providing solutions to retailers.

Read more about our solutions for retail, and check out additional sessions, including the CPG Industry Spotlight Session How To Grow Brands in Times of Rapid Change – Featuring L’Oréal at our Retail & Consumer Goods Summit.

Editor’s note: Today’s post documents the solution to a problem of how to scale website infrastructure as it moves from on-prem to the cloud. It is the result of collaboration between technical teams of Les Echos Le Parisien Annonces (a division of Groupe Les Echos, subsidiary company of LVMH) and Google in the spirit of finding the best tool for the job together.

All technology starts aging from the first day you set it up, and over time becomes in need of some renewal. At Les Echos Le Parisien Annonces (a division of Groupe Les Echos, subsidiary company of LVMH), we complement the main site (“publication annonce légale”) with a number of local market sites for different regions within metropolitan France, as well as French readers in territories across the world. Each local market site offers a variety of services and content, which are served by a set of CMS-driven sites.

Historically these sites were served from dedicated on-prem infrastructure. As the number of sites grew, vertical scaling was used to increase the capacity of the machine. Over time, this approach presented challenges. First, each new site involved modifying multiple shared configurations, and modifying several monolithic parts of the architecture. Because all the sites shared parts of the serving stack, an issue that developed for one site could take down all of the sites. The reliability of the serving path was not able to reach the availability we and our customers expected. Les Echos and Google put their heads together to solve this with a new serverless deployment pattern where each new site can be quickly and independently launched.

Each site, running a conventional PHP CMS solution, is now containerized and deployed as its own Cloud Run service with an independent configuration and database. This means each site scales vertically, including down to zero at times of day when that locale is quiet. Because Cloud Run is available across GCP regions, we can deploy sites closest to the market we want to reach. To further enhance our customer experience, each of these sites is run behind Cloud Global Load Balancing with Cloud Armor and Cloud CDN, providing extra security and performance. The initial pilot of 30 sites has performed well, and the remainder of the 150 current sites are now being migrated. Adding new sites has gone from taking hours to minutes. This allows Les Echos to quickly explore new opportunities in markets that previously would have taken much longer to assess and qualify for investing in a new site.

Adopting this serverless approach has been a successful step in the modernization journey to Google Cloud, allowing us to use containers to take existing software and both re-architect and re-platform to support growth while reducing toil.

The home lending journey entails processing an immense number of documents daily from hundreds of thousands of borrowers. Currently, home lending document processing relies on some outdated digital models and a high dependency on manual labor, resulting in slow processing times and higher origination costs. Scaling a business that sorts through millions of documents daily, while increasing efficacy and accuracy, is no small feat. When it comes to applying for a mortgage loan, consumers expect a digital experience that’s as good as the in-person one. Roostify simplifies the home lending journey for lenders and their customers.

No time to spare: Overcoming document processing challenges with AI

Roostify provides enterprise cloud applications for mortgage and home lenders. In order to empower its customers to deliver a better, more personalized lending experience, they needed to automate and scale their in-house document parsing functionality.

As a key component of its document intelligence service, Roostify is leveraging Google Cloud’s Lending DocAI machine learning platform to automate processing documents required during a home loan application process, such as tax returns or bank statements with multi-language support. This partnership delivers data capture at scale, enabling Roostify customers to automatically identify document types from the uploaded file and to extract relevant entities such as wages, tax liabilities, names, and ID numbers for further processing, and make things move faster in the cumbersome lending process. 

Roostify’s solutions leverage Google Cloud’s Lending DocAI, which is built on the recently announced Document AI platform, a unified console for document processing. Customers can easily create and customize all the specialized parsers (e.g., mortgage lending documents and tax returns parsers) on the platform without the need to perform additional data mapping or training. All Google Cloud’s specialized parsers are fine-tuned to achieve industry-leading accuracy, helping customers and partners confidently unlock insights from documents with machine learning. Learn more about the solution from the GA launch blog and the overview video.

Integrating Lending DocAI’s intelligent document processing capabilities into the Roostify platform means more innovation for their customers and tangible results: faster loan processing times, fewer document intake errors, and lower origination costs. Additional support in Google Lending DAI for other languages and more documents like global Know Your Customer (KYC) documents or payroll reports is in the near future.

Full integration of AI solutions

Working together with Roostify’s platform team, we were able to help them solve their document processing challenge through integration of various GCP products such as Lending DocAI (LDAI), Data Loss Prevention (DLP) for redacting sensitive data, BigQuery for data warehousing and analytics, and Firestore for API status. To make it very safe and secure, all data was encrypted end-to-end at Rest and in Transit. LDAI won’t require any training data to process. It is an easy plug and play API.

Here is a sneak peek in the high level deployment architecture for LDAI in Roostify environment:

Here are the steps for processing data:

1. Receives document processing request from the client.
2. API Function directs requests to the pre-processing service. For Async requests a processing ID is generated and returned to the caller.
3. Pre-processing service sends the request for further processing (Long/short PDF conversion), calling other microservices and receives back the responses. Any error in the response received is then sent to the response processing service. 
4. If the response is synchronous, the pre-processing service directs it to the LDAI Invoker service. 
   1. If the response is asynchronous, the pre-processing service feeds it into the Cloud Pub/Sub service.
5. Cloud Pub/Sub service feeds the response back to the LDAI Invoker service.
6. LDAI Invoker service routes the request to the Google LDAI API for classification if there are multiple pages in the document.
7. Document will be split based on LDAI response and then saved in a GCS bucket for temporary storage.
8. LDAI entity interface for single page processing and then LDAI Invoker sends LDAI results to LDAI Response Processing
9. If a request is a synchronous request the LDAI Response Processor sends results to the API Function so that it can complete the synchronous call and respond to the rConnect caller.
   1. If the request is an asynchronous request the LDAI Response Processor will respond to the caller’s webhook and complete the transaction.
10. Finally, Data stored in the GCP bucket will be deleted.

All the responses that come from the LDAI API can optionally feed into BigQuery via the Response Processor, after parsing it through Data Loss Prevention (DLP) API to redact the PII/sensitive information.  Throughout the processing of both asynchronous and synchronous requests all transactions are logged using Cloud Logging.  For asynchronous transactions, the state is maintained throughout the process using Cloud Firestore.

Roostify currently uses this technology to power two different solutions: Roostify Document Intelligence and Roostify Beyond™. Roostify Document Intelligence is a real-time document capture, classification, and data extraction solution built for home lenders. It ingests documents uploaded by borrowers and loan officers, identifies the relevant documents, and extracts and classifies key information. Roostify Document Intelligence is available as a standalone API service to any home lender with any digital lending infrastructure already in place. 

Roostify Beyond™ is a robust suite of AI-powered solutions that enables home lenders to create intelligent experiences from start to close. It combines powerful data, insightful analytics, and meaningful visualization to streamline the underwriting process. Roostify Beyond™ is currently available only to Roostify customers as part of an Early Adopter program and will be rolled out to the market later this year.

Through this partnership, Roostify has enabled its customers to adopt a data-first approach to their home lending processes, which will lead to improved user experiences and significantly reduced loan processing times.

Fast track end-to-end deployment with Google Cloud AI Services (AIS)

Google AIS (Professional Services Organization), in collaboration with our partner Quantiphi, helped Roostify deploy this system into production and fast-tracked the development multifold to generate the final business value.

The partnership between Google Cloud and Roostify is just one of the latest examples of how we’re providing AI-powered solutions to solve business problems.

Product teams often serve as the nexus between all organizational units within a company, ensuring that a specific line of business follows a clear roadmap and that cross-functional alignment drives success. At their most empowered, product owners are like miniature CEOs for each offering within a company.

Unfortunately, in today’s complicated IT landscape, not everything that should be thought of as a product receives the designation. In my time as a digital consultant, I’ve seen one particular technology too often dismissed as back-office minutiae — application programming interfaces, or APIs.

APIs can be the glue that binds a company’s resources together and the mechanisms through which an enterprise’s data, functionality, and other digital assets are accessed and distributed. They enable software systems to communicate and let developers leverage software for new applications and digital experiences, abstracting underlying complexity into a consistent interface that allows data and functionality to be combined and reused with unprecedented flexibility.

Unfortunately, many business leaders see APIs as middleware and thus as undeserving of the resources of a full-fledged digital product. Their organizations create APIs as one-off projects, with engineers moving on to other projects when they are done and no one looking after an API’s maintenance or whether it offers utility beyond the bespoke use case for which it was created.

This is a problem because APIs can unlock digital assets that otherwise would be captive within enterprise silos. An API that exposes a customer database can likely be used and reused for numerous purposes, for example, and treating developers as customers of this API can help increase adoption of and the amount of innovation around it. But such a powerful outcome is unlikely if an API has been created only as a system integration detail rather than as a product with an owner who oversees a full lifecycle, from ideation to adoption to iteration. Put bluntly, a project-oriented attitude toward APIs misses the boat.

Pitney Bowes, a company I’ve worked with at Google Cloud, offers a high-profile example in which a notable enterprise has treated APIs as products and given its API program the same treatment it would give to any go-to-market offering. After selling traditional mailing and shipping solutions for nearly 100 years, the company transformed itself into a provider of digital logistics and e-commerce solutions by building out 160 public APIs and 400 internal APIs. This enabled its developers and partners to easily consume the company’s location intelligence and shipping services in new, agile ways. It also accelerated the company’s internal project timelines, shortening the average project lifecycle from over a year to just a few months. What’s more, APIs not only introduced efficiencies and reduced costs, but also opened new revenue streams. Because developers can more easily leverage individual Pitney Bowes business capabilities for their applications, the company’s services are manifesting in new ways — such as when Pitney Bowes technology is harnessed to let customers print USPS shipping labels from within the context of an online marketplace.

Manage APIs as products

Traditionally, but wrongly, APIs have been considered pieces of other products. They’ve been built by the IT team at the request of product owners every time a project came up that required one. When the funding spigot is flowing, APIs generally receive support. But once the project runs its course, the APIs are neglected and quickly grow outdated.

Without consistent resources, APIs can’t be adapted to fluctuations in the enterprise and market dynamics. Worst of all, project-oriented APIs often end up siloed within the business unit that gave birth to them, which defies the benefit of modern APIs: to not only allow enterprise assets to be reused by other business units and partners but also accelerate the business’s innovation by increasing the number of developers interacting with its capabilities.

In contrast, if an API is treated as a product in its own right with its own owner lobbying for consistent funding, the API can be iterated according to shifts in internal and market trends. Ideally, the product owner should continually monitor an API’s engagement and collect and synthesize analytics to improve quality of service. Product-minded companies frequently launch APIs as minimum viable products in order to get ideas to market faster, then use API consumption analytics to understand developer engagement and refine APIs to be even more attractive, powerful, and intuitive.

With the help of management tools that facilitate dynamic changes, an API product owner can also help ensure that developers benefit from the latest and greatest build with minimal interruption.

Virtually all traditional product ownership responsibilities can be easily applied to an API. An API product owner is responsible for galvanizing the entire company around their API’s value. Their team can answer any questions users may have about the API’s value proposition or how to use it. It may sound trivial but having dedicated experts available to assist with any question that may arise can be a boon to an API’s velocity.

Additionally, if a dedicated product owner is assigned to pilot a company’s aggregate API program, they can use comprehensive monitoring and analysis of all API traffic to derive insight into which APIs drive value and which don’t. This can save considerable time and money from being wasted on the wrong bets. The product owner can also create API bundles segmented according to each developer community the program wants to serve. Here, the goal is not just to expose enterprise assets, but also to encourage repeat consumption. When it comes to third-party engagement, these bundles should seek to improve partner stickiness to cultivate and maintain new revenue channels. Just as any product is only useful if it has users adopting it and sticking with it, APIs are typically valuable when they attract communities of repeat users.

Tools and processes that turn APIs into strategic assets

To drive an API as a strategic asset, an API product manager should support the API with management tools and processes.

First off, it’s necessary to establish comprehensive security layers for an API so cross-functional internal groups and third-party partners are comfortable using it. Mechanisms that apply protection with introducing user friction — such as OAuth, API key verification, XML/JSON threat protection — are strongly encouraged. It’s also often prudent to integrate machine learning functionality that can detect bot attacks and other adversaries before they breach an API and affect either its developer users or the end users consuming those developers’ apps.

Enterprise software products are typically afforded visualization tools, dashboards, reports, and self-service functionality to drive adoption — and APIs should be no different. Comprehensive portals that highlight API features (including knowledge centers, interactive documentation, blogs, and forums) should be crafted to promote developer consumption. Anything that is likely to magnetize collaborators and expedite registration should be provided for an API. A primary goal of API-first development is to increase velocity, so offering developers a self-service experience while maintaining visibility and control over API usage is crucial.

Manage with an “outside-in” perspective

Perhaps the most important role an API product owner must fulfill is maintaining a staunch outside-in approach.

In an inside-out perspective, enterprise leaders look internally for gaps and fill them with existing IT capabilities. Internal intuition untested by the market can define planning, and the resources that IT already has — rather than those that customers demand — typically restrict options. In contrast, an outside-in approach requires the company to listen to what the market is asking for and to respond appropriately. Outside-in thinkers start by asking what the customer needs, then build strategies from there. Because customer preferences are moving targets, an outside-in perspective is constantly evolving and seeking new data. In the case of API programs, product managers should find ways to align API user data with business KPIs, which can be essential to organizing stakeholders and achieving buy-in for the program throughout the organization.

Because both consumers and developers will abandon products that do not meet their needs, an outside-in perspective is increasingly non-negotiable. The product owner needs to analyze rapidly-changing market trends, understand the competitive landscape, keep a pulse on customer and stakeholder needs, and facilitate a backlog of changes that can help the company satisfy the market. Essentially, API product owners are the end-user advocate — and that’s for both for developers using the APIs and the people touching the applications powered by those APIs.

None of this means product owners need to be entirely risk averse, however. They should have the freedom to experiment with hypotheses and to make adjustments — but to make experimentation viable over the long run, they also need to have the foresight to kill a project immediately if the early end-user response is poor. If the product owner is not learning and iterating, they probably are not pushing the API program forward.

Calling all product professionals

If an enterprise plans to pursue an API-first mandate, it’s crucial that the API program is a well-funded, autonomous business unit. Without a visionary owner, APIs will not be able to usher in the transformation experienced by companies such as Pitney Bowes. The API-first philosophy requires that APIs are built prior to applications and that the API provide a value proposition of its own — which means that if an enterprise wants to accelerate innovation and take advantage of APIs, its first step should be to hire API product managers.