How Eventrac and Workflows Integration Helps Implement Hybrid Architecture in Google Cloud
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I previously talked about Eventarc for choreographed (event-driven) Cloud Run services and introduced Workflows for orchestrated services.
Eventarc and Workflows are very useful in strictly choreographed or orchestrated architectures. However, you sometimes need a hybrid architecture that combines choreography and orchestration.
For example, imagine a use case where a message to a Pub/Sub topic triggers an automated infrastructure workflow or where a file upload to a Cloud Storage bucket triggers an image processing workflow. In these use cases, the trigger is an event but the actual work is done as an orchestrated workflow.
How do you implement these hybrid architectures in Google Cloud? The answer lies in Eventarc and Workflows integration.
Eventarc triggers
To recap, an Eventarc trigger enables you to read events from Google Cloud sources via Audit Logs and custom sources via Pub/Sub and direct them to Cloud Run services:
One limitation of Eventarc is that it currently only supports Cloud Run as targets. This will change in the future with more supported event targets. It’d be nice to have a future Eventarc trigger to route events from different sources to Workflows directly.
In absence of such a Workflows enabled trigger today, you need to do a little bit of work to connect Eventarc to Workflows. Specifically, you need to use a Cloud Run service as a proxy in the middle to execute the workflow.
Let’s take a look at a couple of concrete examples.
Eventarc Pub/Sub + Workflows integration
In the first example, imagine you want a Pub/Sub message to trigger a workflow.
Define and deploy a workflow
First, define a workflow that you want to execute. Here’s a sample workflows.yaml that simply decodes and logs the Pub/Sub message body:
main:params: [args]steps:- init:assign:- headers: ${args.headers}- body: ${args.body}...- pubSubMessageStep:call: sys.logargs:text: ${"Decoded Pub/Sub message data is " + text.decode(base64.decode(args.body.message.data))}severity: INFODeploy the workflow with a single command:gcloud workflows deploy ${WORKFLOW_NAME} --source=workflow.yaml --location=${REGION}
Deploy a Cloud Run service to execute the workflow
Next, you need a Cloud Run service to execute this workflow. Workflows has an execution API and client libraries that you can use for your favorite language. Here’s an example of the execution code from a Node app.js file. It simply passes the received HTTP request headers and body to the workflow and executes it:
const execResponse = await client.createExecution({parent: client.workflowPath(GOOGLE_CLOUD_PROJECT, WORKFLOW_REGION, WORKFLOW_NAME),execution: {argument: JSON.stringify({headers: req.headers, body: req.body})}});
Deploy the Cloud Run service with the Workflows name and region passed as environment variables:
gcloud run deploy ${SERVICE_NAME} \--image gcr.io/${PROJECT_ID}/${SERVICE_NAME} \--region=${REGION} \--allow-unauthenticated \--update-env-vars GOOGLE_CLOUD_PROJECT=${PROJECT_ID},WORKFLOW_REGION=${REGION},WORKFLOW_NAME=${WORKFLOW_NAME}
Connect a Pub/Sub topic to the Cloud Run service
With Cloud Run and Workflows connected, the next step is to connect a Pub/Sub topic to the Cloud Run service by creating an Eventarc Pub/Sub trigger:
gcloud eventarc triggers create ${SERVICE_NAME} \--destination-run-service=${SERVICE_NAME} \--destination-run-region=${REGION} \--location=${REGION} \--event-filters="type=google.cloud.pubsub.topic.v1.messagePublished"
This creates a Pub/Sub topic under the covers that you can access with:
export TOPIC_ID=$(basename $(gcloud eventarc triggers describe ${SERVICE_NAME} --format='value(transport.pubsub.topic)'))
Trigger the workflow
Now that all the wiring is done, you can trigger the workflow by simply sending a Pub/Sub message to the topic created by Eventarc:
gcloud pubsub topics publish ${TOPIC_ID} --message="Hello there"
In a few seconds, you should see the message in Workflows logs, confirming that the Pub/Sub message triggered the execution of the workflow:
Eventarc Audit Log-Storage + Workflows integration
In the second example, imagine you want a file creation event in a Cloud Storage bucket to trigger a workflow. The steps are similar to the Pub/Sub example with a few differences.
Define and deploy a workflow
As an example, you can use this workflow.yaml that logs the bucket and file names:
main:params: [args]steps:...- log:call: sys.logargs:text: ${"Workflows received event from bucket " + bucket + " for file " + file}severity: INFO
Deploy a Cloud Run service to execute the workflow
In the Cloud Run service, you read the CloudEvent from Eventarc and extract the bucket and file name in app.js using the CloudEvent SDK and the Google Event library:
const cloudEvent = HTTP.toEvent({ headers: req.headers, body: req.body });//"protoPayload" : {"resourceName":"projects/_/buckets/events-atamel-images-input/objects/atamel.jpg}";const logEntryData = toLogEntryData(cloudEvent.data);const tokens = logEntryData.protoPayload.resourceName.split('/');const bucket = tokens[3]
Executing the workflow is similar to the Pub/Sub example, except you don’t pass in the whole HTTP request but rather just the bucket and file name to the workflow:
const execResponse = await client.createExecution({parent: client.workflowPath(GOOGLE_CLOUD_PROJECT, WORKFLOW_REGION, WORKFLOW_NAME),execution: {argument: JSON.stringify({bucket: bucket, file: file})}});
Connect Cloud Storage events to the Cloud Run service
To connect Cloud Storage events to the Cloud Run service, create an Eventarc Audit Logs trigger with the service and method names for Cloud Storage:
gcloud eventarc triggers create ${SERVICE_NAME} \--destination-run-service=${SERVICE_NAME} \--destination-run-region=${REGION} \--location=${REGION} \--event-filters="type=google.cloud.audit.log.v1.written" \--event-filters="serviceName=storage.googleapis.com" \--event-filters="methodName=storage.objects.create" \--service-account=${PROJECT_NUMBER}-compute@developer.gserviceaccount.com
Trigger the workflow
Finally, you can trigger the workflow by creating and uploading a file to the bucket:
echo "Hello World" > random.txtgsutil cp random.txt gs://${BUCKET}/random.txt
In a few seconds, you should see the workflow log the bucket and object name.
Conclusion
In this blog post, I showed you how to trigger a workflow with two different event types from Eventarc. It’s certainly possible to do the opposite, namely, trigger a Cloud Run service via Eventarc with a Pub/Sub message (see connector_publish_pubsub.workflows.yaml) from Workflows or a file upload to a bucket from Workflows.
All the code mentioned in this blog post is in eventarc-workflows-integration. Feel free to reach out to me on Twitter @meteatamel for any questions or feedback.
Macy’s Uses Google Cloud to Streamline Retail Operations
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As retailers strive to meet the growing expectations of shoppers, they are turning to Google Cloud to transform their businesses and tackle opportunities in an increasingly challenging industry. From optimizing inventory management to increasing collaboration between employees across locations and roles, to helping build omnichannel experiences for their customers, we are working together with retailers to help make the shopping experience as seamless and personalized as possible.
A standout Google Cloud customer is Macy’s, one of the world’s largest retailers. Founded in 1858, Macy’s operates approximately 680 Macy’s and Bloomingdale’s, and 190 specialty stores including Bloomingdale’s The Outlet, Bluemercury and Macy’s Backstage. And through macys.com, bloomingdales.com, and bluemercury.com, it also serves millions of customers across more than 100 countries.
By moving its infrastructure to the cloud, and taking advantage of Google Cloud data warehousing and analytics solutions, Macy’s is streamlining retail operational functions across its network.
With the opening of its new approximately 675,000 square-foot distribution center in Columbus, Ohio, Macy’s is leveraging the scalability of Google Cloud to ensure that merchandise is accurately and efficiently received, sorted, ticketed, picked, packed and shipped from the distribution center to the stores—even during peak retail seasons like back to school and the holidays.
“Powered by software developed at Macy’s technology, this new distribution center is a fantastic first step in our cloud journey. Working with Google Cloud allows us to be more nimble, efficient and flexible in how we utilize our warehouses,”
Naveen Krishna, CTO, Macy’s
Leveraging Google Cloud’s data management and analytics solutions, Macy’s new warehouse management system will initially service 200+ Macy’s Backstage off-price stores at launch. Macy’s will begin rolling out this software solution to additional distribution centers that service its nationwide fleet of Macy’s and Bloomingdale’s department stores, as well as Macys.com and Bloomingdales.com direct-to-customer orders.
Our continued work with Macy’s reflects their investment in technology to improve digital and mobile experiences, site stability, store technology, fulfillment, and logistics, and integrate its front line and back office to reinvent retail. I look forward to deepening our partnership with Naveen and his team to help them achieve these goals.
The Future of Retail: Automated Customer Journeys Powered by Technology
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Editor’s note: To kick off the new year and in preparation for NRF The Big Show, we invited partners from across our retail ecosystem to share stories, best practices, and tips and tricks on how they are helping retailers transform during a time that continues to see tremendous change. Please enjoy this entry from our partner.
If you put a pot of water on the stove, it doesn’t heat up instantly. It simmers slowly at first, eventually picking up steam to reach a rolling boil. The retail landscape is not so different. Capgemini’s research shows the sector has evolved over four generations, from the early days of fragmented outlets to omnichannel and customer-centric focuses, with a fifth generation on the horizon that promises to be centered on consumption.
- Generation 1: Fragmented outlets
- Generation 2: Chain concentration
- Generation 3: Omnichannel
- Generation 4: Consumer-centric
- Generation 5: Consumption-centric
Although incremental change allows companies to experiment and iterate during their digital journeys, the COVID-19 pandemic rapidly accelerated the evolution of online and contactless shopping. Evolution became a revolution, with most Consumer Product and Retail (CPR) companies still mastering the omnichannel generation of their digital transformation to create a seamless shopping experience. Companies that are more digitally mature are already aspiring to the consumer-centric phase, embracing opportunities made possible by technology such as personalization and automation.
What consumers want
Customers have more choices in how they shop and engage with brands. This has made it harder for brands to predict and anticipate needs across customer journeys. And that’s convincing some companies to innovate more quickly as consumer demand drives the need for speed and scale.
Think about your own online behavior. Say you’re shopping for an item and searching online for the closest store in your neighborhood. Google is likely your go-to for finding that information. Looking to troubleshoot an issue with a product or seek out a service? Again, you’ll likely hit up Google first, not even considering going directly to a brand’s website for answers.
Both scenarios point to a disconnect between virtual and physical worlds, a gap technology can bridge in numerous ways such as breaking down silos and integrating fragmented media channels. Interestingly, though, not everything will be centered online all the time. In our recent study on consumer behavior, The great consumer reset, Capgemini discovered 57 percent of shoppers plan to return to brick-and-mortar stores post-pandemic, which is basically unchanged from the 59 percent who often interacted with physical stores before.
But business as usual? Not even close. Consumers have come to expect a frictionless shopping experience (buy online, pick up in store) or an immersive one (products displayed online using augmented reality), and are not content to return to in-store lineups, empty shelves, or a one-size-fits-all approach. Moreover, customers want personalized interactions while ensuring their data and privacy are protected.
So the role of the store is changing. In fact, many online-only brands are opening brick-and-mortar establishments to drive customer experience. In our research on “smart stores,” we found the majority of consumers (66 percent) believe automation can improve their shopping experience by solving the challenges they face at retail stores.
From personalization to serendipity
Retailers must recognize that they have to win consumer trust and confidence. Many consumers believe retailers’ use of tech is focused on reducing costs rather than easing friction. And they’re right. That same Capgemini research found that only one-third (35 percent) of retailers consider “solving customer pain points” as the most important criteria when deciding which automation use cases to implement.
“Retailers are largely in the early stages of adopting automation, and that’s an opportunity to rethink how they’re using technology, not just to smooth out friction and engender consumer trust but to build unexpected consumer benefits,” says Neerav Vyas, Head of Customer First, Co-Chief Innovation Officer, Insights & Data, North America, Capgemini. “We’re trying to move towards this idea of delivering serendipitous experiences to bridge the physical and digital divide.”
The focus is not solely on shoppers seeking out a specific product. “When consumers are in an exploratory mood, retailers can recommend products and services customers didn’t even know they wanted,” says Vyas. For example, business teams that use personalization platforms as part of an integrated media strategy can optimize algorithms against outcomes such as improving conversion and driving engagement.
Vyas says the elevated experience from “personalization to serendipity” fosters trust in the ability of recommendation architectures to persuade and influence consumers’ choices in beneficial ways. A case in point: our research found that half (52 percent) of spending by millennials goes towards experience-related purchases. As always, the key is to meet consumers where they are. Even better, according to Vyas, is to anticipate and understand when signals like customer intent are changing.
How to create value throughout the customer journey
One solution companies can implement right now is an integrated media spend platform that incorporates reporting, planning, and strategy across the entire customer journey. This offers value throughout the customer journey by using technology to reduce friction along the way. Think of it as starting with the customer looking for a product (search and discovery), moving on to the purchase (omnichannel basket, “shoppable” screens) and pick up/delivery (QR code scan in store), and through to post-purchase engagement with the retailer (Google Contact Center AI).
Such a holistic approach also accelerates data acquisition, integration, and reporting using advanced analytics to break down silos and emphasize the importance of privacy and first-party data. This in turn guides end-to-end interventions across customer journeys that enable optimized media spend, empowers businesses to analyze their spend distribution, fine-tunes owned and paid tactics with agencies, and promotes stewardship to support audit efficacy.
A culture of experimentation
With this data-driven focus, CPRs can create a 360-degree perspective of the customer. That intelligence can be used to enhance and humanize automated shopping experiences by putting the customer in control, whether online, in store, or across company brands. Moreover, by using Google Cloud’s emerging technologies such as artificial intelligence (AI), we help companies accelerate value across the spectrum, from supply-chain optimization and customer innovation to consumer experience.
Building a culture of experimentation is a team effort. “It’s not ever just one person who had a big idea. It’s all incremental steps,” says Jennifer Marchand, Google Cloud COE Leader, Capgemini. “Finding the right use case and timing is everything.” Take Google Glass Enterprise, she continues. For greater consumer experience, it can enable in-store associates to better serve with hands-free checkout, customer personalization and recommendations, and special offers. At the same time, Computer Vision and Smart Shelves can help prioritize tasks for employees, notifying them of low stock or a spill in the store.
Marchand points out that companies and consumers alike might not be ready to fully adopt some technology like facial recognition, but since almost everyone has a smartphone these days, they can benefit from automation with ease. “What’s interesting,” she adds, “is the way Google thinks about these types of problems, solving them for the long term.”
The store of tomorrow
Imagine a truly frictionless shopping experience, where state-of-the-art computer vision and AI identifies the products you pick up, put back, and keep, allowing you to head home, completely bypassing the checkout, with a 99 percent accuracy rate and receipts sent directly to your mobile app. That utopian experience is already taking shape at CornerShop, Capgemini’s live experimental store in London, UK.
Jamie MacLoud, Transformation & Strategy Consultant at frog, part of Capgemini, describes the retail space, which runs on Google Cloud, as the store of tomorrow, and not the distant future. It’s an experiential space where retailers and brands can explore, develop, and test technological shopping innovations in real-time. The outcome is a clearer understanding of how digital innovation can enable new ways to progress the customer experience, improve in-store operations, and help consumers to rediscover the joy of in-person retail through new ways to shop and engage with brands.
“We build, test, and learn about store concepts of tomorrow that we believe could be implemented into actual stores in the next one to two years. Getting these experiences in front of real customers in the CornerShop allows us to generate tangible learnings that we can share with our clients and use to shape future store strategy” says MacLeod. CornerShop was opened to the public in two eight-week stints, which allowed real-time testing to see what technologies resonated with customers, which brands can adapt and scale. Frictionless checkout, not surprisingly, was a big win for customers, but the technology underpinning the “virtual try-on” of clothing was deemed more suitable for the store of the future.
So, unlike an innovation lab, CornerShop lets companies experiment risk free, speeding up the process from hypothesis to full-scale implementation. It’s also another step toward solving the challenges customers face, while delivering those serendipitous experiences that build brand loyalty and longevity.
Learn more about how Capgemini is partnering with Google Cloud to help retailers create next-generation shopping experiences today.
We would like to acknowledge Jamie MacLoud, Transformation & Strategy Consultant at frog, part of Capgemini and Neerav Vyas, Head of Customer First, Co-Chief Innovation Officer, Insights & Data, North America at Capgemini who supported with invaluable insights and subject matter expertise in the writing of this blog post.
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Every business is a digital business. That’s what you’ll hear from technology folks these days. But, what exactly is a digital business? How does one define it?
Simply put, digital businesses are those that have thoroughly capitalized on the opportunity to connect people with technology. There are four parts to a digital business:
Real-time data and analytics: To stay relevant in the age of Big Data, businesses must analyze copious amounts of data to derive actionable insights—both from historical data, and in real time.
Fast, flexible application development: Rapid and continuous delivery of software to your stakeholders is no longer optional. Businesses need platforms for their applications strategy — from using container-based development tools to fully managed serverless platforms.
Secure, reliable infrastructure: How secure is your on-prem datacenter? What happens if it goes down? How many dedicated security engineers do you have on staff? What’s the cost of a system upgrade? What digital businesses need is a secure and reliable infrastructure that can power their applications.
Constant collaboration and productivity: Digital businesses are designed to keep teams seamlessly connected not only to each other, but also to the applications that keep the company running. This enables everything and everyone to work together, no matter where they sit—across the office or across the ocean.
Download this infographic to know more.
Ulta Beauty: Managing Holiday Surges and Architecting Innovation
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As we enter the holiday season, retailers are working behind the scenes to ensure they can provide the best experiences for customers, in store and online. Challenges in retail do not begin or end during the holiday season as sudden shifts in customer preferences, supply chain nuances, and overall demand ebbs and flows take place year round and retailers must be prepared to adapt swiftly.
Google Cloud’s retail customers globally, in total, saw more online traffic in the first six months of 2022 than all of 2019. This year, retailers can expect an early launch to holiday shopping activities, as 50% of consumers plan to start purchasing goods before the traditional Black Friday kick-off.
The very same improvements made to automate and improve retail infrastructure can prepare it for holiday surges and support year-round innovation. Let’s take a look at how Ulta Beauty, the largest beauty retailer in the U.S., is partnering with Google Cloud, MongoDB Atlas, commercetools, and HCLTech to cover these two areas and more.
Architecting for innovation
Creating personalized shopping experiences in stores and online is key to Ulta Beauty’s success. This commitment is best demonstrated through Ulta Beauty’s Virtual Beauty Advisor. Built on Google Cloud, this tool enhances shoppers’ experiences with personalized recommendations in addition to the ability to try on makeup virtually with GLAMLab.
As innovators in support of the best possible guest experience, Ulta Beauty needed to re-architect its infrastructure for greater agility and stability.
To start, Ulta Beauty chose to use Google Kubernetes Engine (GKE) as the backbone and orchestrator to build and deploy cloud-native applications. The Google Cloud deployments coincided with an organizational move from end-to-end application development to one that focuses on individual features, specific modules, and micro-applications.
This strategic change allowed Ulta Beauty to fix bugs, experiment with new offerings, and drive customer experiences faster and more efficiently. Thanks to the transformation and GKE, Ulta Beauty’s developer team now accelerates time to market for new products and services, and delivers new ways to engage with customers more quickly. These efforts all ladder to create ‘WOW’ experiences for the retailers’ guests who have emotional and personal connections to beauty and wellness. They can now discover and experience products that are served to them based on individual preferences.
Adapting to the new environment comes with its own set of challenges. “Microservices are not a silver bullet,” says Sethu Madhav Vure, IT Architect, Ulta Beauty. “For Ulta Beauty, the biggest challenge was how to break up a monolithic environment into multiple applications. We had to evolve our core systems—without impacting today’s services—and address what was needed for the future.”
Google Cloud partner HCLTech provided expert guidance throughout the re-architecting process, defining the solution blueprint and cloud-native deployment architecture through cross-functional workshops. HCLTech then assisted with the actual migration and platform setup, paving the way for fully automated, continuous integration and continuous delivery (CI/CD) pipelines to support faster rollouts and deployment architecture to drive higher availability and scalability.
Ulta Beauty took a domain-driven design approach to identify operations that could be grouped together to reduce complexity and improve scalability. Now, the applications are based on multiple domains, such as Commerce, Promotions, Catalog, Order, Customer, and Inventory. The new architecture prompted a fresh look at storage requirements to scale dynamically alongside its modernized applications.
For Ulta Beauty, MongoDB Atlas proved to be the best database solution for dynamic scaling, ease-of-use, and integrations with Google Cloud. The company also leveraged an entry-level plan to prove the value of MongoDB Atlas before investing in the technology.
“MongoDB Atlas offers a free tier that gave us an opportunity to quickly demonstrate tangible benefits of a proof of concept,” says Vure. “Once we proved the value of MongoDB Atlas, we benefited from the straightforward resource allocation supported by Google Cloud and MongoDB.”
Integrations between MongoDB Atlas and Google Cloud allow Ulta Beauty to take an iterative approach to new projects. The company creates new clusters in an existing project, then piggybacks them onto an existing Private Service Connect setup between a MongoDB project and Google Cloud project.
By removing complexities within infrastructure management, Ulta Beauty can manage its incredible amount of data, such as member preferences and purchases, that fuels its event-driven architecture. The much more agile infrastructure enables Ulta Beauty to deploy and scale offerings faster than ever.
“We recently had an unplanned traffic surge that impacted our domain services. It took less than an hour for MongoDB Atlas to scale up to the next level of the cluster and manage that traffic,” says Vure. “The on-demand, dynamic scaling, plus GKE, has saved the day more than once.”
Preparing for a happy holiday season
This holiday season, Ulta Beauty has a stronger technical foundation to manage demand surges and provide customers seamless shopping experiences. Previously, the company used 50 pods in a cluster, each with 6 GB of RAM without domain stores, to handle about 100 transactions each second. With domain stores, the same 6 GB of RAM with just 20 GKE pods was able to scale up to 2,400 transactions per second.
With Google Cloud as its technology foundation, Ulta Beauty partnered with Google Cloud partner commercetools to evolve its application APIs as products and properly separate interfaces and capabilities.
Ulta Beauty uses event-based integrations within commercetools to identify how best to leverage Cloud Pub/Sub middleware on top of MongoDB Atlas integrations. Patterns established here were extended into MongoDB change streams and in turn improved business processes.
“Working with the right technology partners has helped us to avoid analysis paralysis that can happen when developer teams spend a lot of time trying to understand and manage every detail,” says Vure. “Instead, we convert a proof of concept into a working solution, and quickly bring it to market. It’s been a major shift in our IT culture as we try out new things weekly and see incredible support from leadership.”
The improvements enable Ulta Beauty to maintain a high level of innovation, performance, and customer service year-round. Now, when the holiday shopping season begins, Ulta Beauty is prepared to handle surges in traffic through auto-scaling with Google Cloud and MongoDB Atlas. Customers get what they want, when they want, free from the frustrations of outages.
“With these changes, we are ready for a holiday season that everyone–even those of us in IT—gets to enjoy. We’re positioned to continuously focus on new, better ways to serve our guests,” says Vure.
Check out MongoDB and commercetools on Google Cloud Marketplace to learn more about what these partners can do for your business.
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Value Realization with Google Cloud for Retail SAP Data
Retail engagements have changed drastically over the last few years, and by the virtue of COVID-19 pandemic, retail data and customers’ expectations plummeted. To drive value and transformation across the entire value-chain retailers can make most of Google Cloud’s secure, reliable IaaS by migrating their SAP systems and taking advantage of integrations, insights and innovations. In times of change retail companies can gain maximum visibility of SAP data unlocking Google Cloud’s infrastructure modernization and Big Data and analytics capabilities. Watch the video to understand how Google Cloud and SAP partnership is a golden handshake for retail businesses’ future.
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