
3923
Of your peers have already downloaded this article
5:30 Minutes
The most insightful time you'll spend today!
3196
Of your peers have already watched this video.
1:30 Minutes
The most insightful time you'll spend today!
Start Your Serverless Expeditions Now!
Google Cloud’s fully managed serverless platform like Cloud Run helps build and run highly scalable containerized applications. In traditional scenarios, over or under-provisioning enterprise applications can result in outages and cost hurdles. Severless Experts at the Google Cloud succinctly breakdown what serverless means for an organization and how Engineering Managers and CTO can rest assured with the predictability, developer productivity, automated release process and infrastructure abstraction.
Watch the video to unravel the serverless journey with Cloud Run!
Google Cloud’s Suite of DevOps Speeds Up ForgeRock’s Development

5705
Of your peers have already read this article.
3:00 Minutes
The most insightful time you'll spend today!
Editor’s note: Today we hear from ForgeRock, a multinational identity and access management software company with more than 1,100 enterprise customers, including a major public broadcaster. In total, customers use the ForgeRock Identity Platform to authenticate and log in over 45 million users daily, helping them manage identity, governance, and access management across all platforms, including on-premises and multicloud environments.
Operating at that kind of scale isn’t easy. In this blog post, ForgeRock Engineering Director, Warren Strange discusses the three things that help make their developers efficient and productive, and the Google Cloud tools they use along the way.
At ForgeRock, we’ve been an early adopter of Kubernetes, viewing it as a strategic platform. Running on Kubernetes allows us to drive multicloud support across Google Kubernetes Engine (GKE), Amazon (EKS), and Azure (AKS). So no matter which cloud our customers are running on, we are able to seamlessly integrate our products into customers’ environments.
Making it easier for ForgeRock’s developers and operators to build, deploy and manage applications has been crucial in our ability to continually provide high quality solutions for our customers. We’re always looking for tools to improve productivity and keep our developers focused on coding instead of configuration. Google Cloud’s suite of DevOps tools have streamlined three specific practices to help keep our developers productive:
1. Make developers productive within IDEs
Developer productivity is core to the success of any organization, including ForgeRock. Since developers spend most of their time within their IDE of choice, our goal at ForgeRock has been to make it easier for our developers to write Kubernetes applications within the IDEs they know and love. Cloud Code helps us precisely with that: it makes the process of building, deploying, scaling, and managing Kubernetes infrastructure and applications a breeze.
In particular, working with the Kubernetes YAML syntax and schema takes time, and a lot of trial and error to master. Thanks to YAML authoring support within Cloud Code, we can easily avoid the complicated and time consuming task of writing YAML files at ForgeRock. With YAML authoring support, developers save time on every bug. Cloud Code’s inline snippets, completions, and schema validation, a.k.a. “linting,” further streamline working with YAML files.
The benefits of Cloud Code extend to local development as well. Iterating locally on Kubernetes applications often requires multiple manual steps, including building container images, updating Kubernetes manifests, and redeploying applications. Doing these steps over and over again can be a chore. Cloud Code supports Skaffold under the hood, which tracks changes as they come and automatically rebuilds and redeploys—reducing repetitive development tasks.
Finally, developing for Kubernetes usually involves jumping between the IDE, documentation, samples etc. Cloud Code reduces this context switching with Kubernetes code samples. With samples, we can get new developers up and running quickly. They spend less time learning about configuration and management of the application—and spend more time on writing and evolving the code.
2. Drive end-to-end automation
To further improve developer productivity, we’ve focused on end-to-end automation: from writing code within IDEs, to automatically triggering CI/CD pipelines and running the code in production. In particular, Tekton, Cloud Build, Container Registry, and GKE have been critical to Forgerock as we streamline the flow of code, feedback and remediation through the build and deployment processes. The process looks something like this:

We begin by developing Kubernetes manifests and dockerfiles using Cloud Code. Then we use Skaffold to build containers locally, while Cloud Build helps with continuous integration (CI). The Cloud Build GitHub app allows us to automate builds and tests as part of our GitHub workflow. Cloud Build is differentiated from other continuous integration tools since it is fully serverless. It scales up and scales down in response to load, with no need for us to pre-provision servers or pay in advance for additional capacity. We pay for the exact resources we use.
Once the image is built by Cloud Build, it is stored, managed, and secured in Google’s Container Registry. Just like Cloud Build, Container Registry is serverless, so we only pay for what we use. Additionally, since Container Registry comes with automatic vulnerability scanning, every time we upload a new image to Container Registry, we can also scan it for vulnerabilities.
Next, a Tekton pipeline is triggered, which deploys the docker images stored in Container Registry and Kubernetes manifests to a running GKE cluster. Along with Cloud Build, Tekton is a critical part of our CI/CD process at ForgeRock. Most importantly, since Tekton comes with standardized Kubernetes-native primitives, we can create continuous delivery workflows very quickly.
After deployment, Tekton triggers a functional test suite to ensure that the applications we deploy perform as expected. The test results are posted to our team Slack channel so all developers have instant access and insights about each cluster. From there, we are able to provide our customers with their finished product request.
3. Leverage multicloud patterns and practices
The industry has seen a shift towards multicloud. Organizations have adopted multicloud strategies to minimize vendor lock-in, take advantage of best-in-class solutions, improve cost-efficiencies, and increase flexibility through choice.
At ForgeRock, we’re big proponents of multicloud. Part of that comes from the fact that our identity and access management product works across Google Cloud, AWS, and Azure. Developing products using open-source technologies such as Kubernetes has been particularly helpful in driving this interoperability.
Tekton has been another critical project that has allowed us to prevent vendor lock-in. Thanks to Tekton, our continuous delivery pipelines can deploy across any Kubernetes cluster. Most importantly, since Tekton pipelines run on Kubernetes, these pipelines can be decoupled from the runtime. Like Tekton and Kubernetes, both Cloud Build and Container Registry are based on open technologies. Community-contributed builders and official builder images allow us to connect to a variety of tools as a part of the build process. And finally, with support for open technologies like Google Cloud buildpacks within Cloud Build, we can build containers without even knowing Docker.
Making it easier for developers and operators to build, deploy and manage applications is critical for the success of any organization. Driving developer productivity within IDEs, leveraging end-to-end automation, and support for multi-cloud patterns and practices are just some of the ways we are trying to achieve this at ForgeRock. To learn more about ForgeRock, and to deploy the ForgeRock Identity Platform into your Kubernetes cluster, check out our open-source ForgeOps repository on GitHub.
11249
Of your peers have already watched this video.
1:30 Minutes
The most insightful time you'll spend today!
Indian Retailer Figures Optimizes Hyperlocal Delivery to Increase Customer Experience
Anyone who follows the Indian e-commerce scene knows that one of the largest challenges these companies face is hyperlocal delivery.
That was a problem facing Wellness Forever, a retail chain of pharmacies with 150-plus stores across India.
“Exactly a year ago, we started our journey of hyperlocal deliveries. This optimization was a big time challenge for us to understand how to optimize this,” Palani Subbiah, CTO, Wellness Forever.
The problem in front of Wellness Forever was to identify which customer could can be sold from which store, so that a delivery could be made within 90 minutes.
“We handle a large amount of customer data and we wanted to use insights to help and improve the customer satisfaction index,” says Subbiah.
To do that Wellness Forever leveraged Google Big Query to run massive amount of data to come up with the operational insights. They also used Firebase and Google Maps.
“By 2021, we are going to have about 450 stores. Those stores are going to be not only a physical store, which is a digital store.
3230
Of your peers have already watched this video.
2:00 Minutes
The most insightful time you'll spend today!
Simplified Document Processing with AppSheet Automation
Move over legacy, time-consuming systems and processes to update data from documents and invoices into disparate data systems. AppSheet integrates no-code development with Google Cloud’s state-of-the-art Document AI to automate the data extraction and validation from invoices, documents, receipts, etc.
You can end all ‘guesstimates’ and rely on the accuracy of the intelligent document processing feature, and set custom triggers for automation events or the way data is displayed from its unstructured source. Watch the video to understand how your business can save time and resources with automation and seamlessly manage high-volume, unstructured data.
4933
Of your peers have already watched this video.
9:37 Minutes
The most insightful time you'll spend today!
L’Oréal: Managing Big-data Complexity with Google Cloud
L’Oreal is a global company with a presence in 150 countries worldwide. Between managing all of its brands and requirements for different countries, L’Oreal looks to data to make insightful business decisions. How does L’Oreal unify its data across all its systems and databases? How does L’Oreal make the data accessible to thousands of employees? In this video, Antoine Castex, Enterprise Architect at L’Oreal, discusses with Martin Omander how L’Oreal built a serverless, multi-cloud warehouse based on Google Cloud.
Chapters:
0:00 – Intro
0:23 – Why does L’Oreal need a new data warehouse?
0:51 – Who is the L’Oreal group?
1:35 – Which systems does L’Oreal use?
2:14 – How does L’Oreal manage complexity?
3:59 – What is ELT?
4:57 – Who are L’Oreal’s data consumers?
5:41 – How L’Oreal built the data warehouse
8:51 – L’Oreal’s future plans
9:10 – Wrap up
Google Cloud Workflows → https://goo.gle/3q20M1V
Cloud Run → https://goo.gle/3CSWbXG
Eventarc → https://goo.gle/3B7qhFy
BigQuery → https://goo.gle/3KHgyJ3
Looker → https://goo.gle/3Rx4Ind
Checkout more episodes of Serverless Expeditions → https://goo.gle/ServerlessExpeditions
Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
More Relevant Stories for Your Company

Booking.com’s Apigee Hybrid on Anthos is the Largest Hybrid Deployment Ever
Apigee API Management Platform helps unlock the value of data in legacy systems and applications to accelerate end-user/customer experience by modernizing apps and building multi-cloud environments. With Apigee Hybrid on Anthos, a service mesh technology, Booking.com was able to achieve its goal of providing customers a connected trip experience. Watch

Groww’s Google Cloud-Powered Platform: The Key to Secure and Successful Investing
Groww makes investments simple and accessible, using Google Kubernetes Engine to ensure a reliable platform for customers, and makes data-backed decisions to grow its business with BigQuery. Google Cloud results Reduces hardware costs with Preemptable Virtual Machines Enables a lean DevOps team with Google Cloud Analyzes data effectively and quickly

Ease Your Migration and Modernization Journey with Microsoft and Windows on Google Cloud Demo Center
If you’re looking to migrate and modernize your Microsoft and Windows workloads, Google Cloud is your premiere destination. No matter what migration strategy you’ve selected or what value you’re looking to achieve, with Google Cloud you’re able to: simplify your migration and modernization journeyreduce your on-prem footprint and increase agilityoptimize license

Predict User Churn on Gaming Apps with Google Analytics Data using BigQuery ML
User retention can be a major challenge for mobile game developers. According to the Mobile Gaming Industry Analysis in 2019, most mobile games only see a 25% retention rate for users after the first day. To retain a larger percentage of users after their first use of an app, developers can






