Application Rationalization: Your App Development Team is Gonna Love It!

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On April 6th, 2022, Google Cloud established a new partnership with CAST, to help accelerate the migration and application modernization programs of customers worldwide, complementing the Google capabilities already available through the Google Cloud Application Modernization Program (CAMP).
Application Rationalization (App Rat) is the first step towards a cloud adoption or migration journey, through which you go over the application inventory to determine which applications should be Retired, Retained, Refactored, Replatformed, or Reimagined.
Why is this important to you?
Have the majority of your in-house applications still not moved to the cloud? How much time does your development team spend on support (bug fix, tickets, etc.) versus feature(s) development? Have Infrastructure/Platform dependencies ever delayed product rollout? Would an auto-scalable, managed cloud, increase stakeholder buy-in?
Can Google simplify this journey?
Google Cloud Application Modernization Program (CAMP) has been designed as an end-to-end framework to help guide organizations through their modernization journey by assessing where they are today, and provide a path forward. When it comes to App Rationalization, this depends on what your role is.
Step 1 (Assess): Who is the target audience? The Platform team (or) the Application team?
This determines what kind of challenges we are trying to solve. For e.g. the centralized platform team wants to set some guardrails on how the App teams deploy their apps. Streamlining this would allow the platform team to mature themselves into the SRE territory. The application team, on the other hand, loves flexibility, and the ability to perform Continuous Delivery.
These examples are only the tip of the iceberg. Most of the enterprise customers have a majority of their applications in the legacy world. Unless we move those business critical applications to the cloud, it’s impossible to mature as an enterprise. For more information, check State of DevOps 2021 report.

Step 2 (Analyze): Google Cloud offers the tooling and the framework to analyze your legacy applications.
Platform Owner (persona), usually have very little information on which workloads are a good fit for modernization.
Google’s StratoZone® SaaS platform provides customers with a data-driven cloud decision framework. The StratoProbe® Data Collector Application delivers the ability to easily deploy and scale the discovery of a customer’s IT environment for Private, Public, or Hybrid-cloud planning. To ease and accelerate the VM migration journey, Google Cloud offers assistance and guidance in making the right decisions when deciding to go to cloud.
Google’s mFit aims at unblocking customers in their transformation by providing workload selection for successful on-boarding, at scale, to Anthos, GKE and Cloud Run , in both pre-sales (e.g. proof-of-concept/proof-of-value) and post-sales (e.g. pilot and at scale execution) scenarios.
App and/or Business Owners (persona), get involved in a 1-week workshop, using CAST Highlight, which would provide rapid portfolio assessment through automated source code analysis for Cloud Readiness, Open Source risks, Resiliency, and Agility.

Step 3 (Plan & execute): Each organization is different. Some may follow the “Migration Factory” approach, and some may follow “Modernization Factory”, and some may follow both. Irrespective of which approach you choose to follow, it is important to plan just enough, so that you can start your execution. Ensure to set the OKRs, that would help with the right measurements, before you start the execution. The actual learning from the execution helps the team(s) to learn more about the cloud migration process, and refine it based on their organization.
Using CAST Highlight in the assessment step previously, we get the recommendation for the analyzed applications. From there, for certain workloads, we can use Migrate to Containers, to automate the containerization of suitable workloads. However, there are certain applications that require manual code changes. You have a few options for that,
- Our experts can help you get started.
- Our partners can help you
Step 4 (Measure & reiterate): Measure the progress using the predefined metrics in the previous step. Celebrate the wins. Consistently share the learnings and best practices with the developer community. Pick the next challenge
Take the next step
Tell us what you’re solving for. A Google Cloud expert will help you find the best solution.
How to Modernize Your Apps with Migrate to Anthos

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In a perfect cloud world, you would host all your applications in containers running on Kubernetes and Istio, benefitting from the portability and improved resource utilization of containers, plus a robust orchestration platform with advanced application management, networking, and security functionality. This is easy to do if you’re developing a new application, but it can be hard for existing applications to take advantage of those capabilities.
Many of the applications that you may want to move to the cloud have been around a long time, and you may not have the application-specific knowledge that would be required to rewrite them to be more cloud-native—or it would be incredibly time-consuming to do so.
Another option is to lift-and-shift to a virtual machine (VM) hosting platform like Compute Engine, but that means you still need to maintain the VMs. Even if you’re not able to fully modernize an existing app, it would still be great to get some of the benefits of containers and Kubernetes.
What is Migrate for Anthos?
Enter Migrate for Anthos, a fast and easy way to modernize your existing applications with a service that encapsulates them in a container. Moving your physical servers or existing VMs into Kubernetes containers gives you crucial portability and resource utilization benefits without having to rewrite the underlying application.
Since Migrate for Anthos is built for Google Kubernetes Engine (GKE), you also automatically capture the scaling and flexibility benefits of a managed Kubernetes environment in the cloud. Migrate for Anthos recently became generally available.
Converting an application with Migrate for Anthos happens in two phases. First, it creates a generic container wrapper around your application that makes it seem like it is still running in a full VM environment. Then, you launch Migrate for Anthos software on your Kubernetes cluster that runs the containerized application.
You can find more details about this in the documentation and in our blog post: Migrating from Compute Engine to Kubernetes Engine with Migrate for Anthos.
As the name suggests, Migrate for Anthos works with Anthos GKE. However, you can also use Migrate for Anthos with only GKE—all it requires is your application and a GKE cluster running the Migrate for Anthos software.
Getting started with Migrate for Anthos
Migrate for Anthos works with a variety of workloads, but not all. It’s particularly adept at migrating legacy applications, stand-alone applications, and monolithic applications. As you start the modernization process, here are some questions to ask to determine whether to use Migrate for Anthos with your applications:
1. Should this app be in the cloud?
By its nature, the cloud may not be able to support some characteristics of your on-prem environment, such as geography and legal compliance. The best way to find out whether the cloud will work for each of your applications is to plan out a full migration. That will allow you to identify groups of applications that can benefit from cloud offerings such as a global network and ease of resizing resources. After that, try out a proof of concept by testing the apps in the cloud to see if it fits your business needs.
2. Should this app be in Kubernetes?
Containerizing an application simplifies workload administration, improves scalability (both up and down), and increases host utilization. Kubernetes orchestrates the containers and GKE handles node upgrades, while add-ons like Istio let you manage network and security policies independently of your application.
With those advantages, it’s easy to think that containers are always the right way to go, but there are some cases where it may make sense to stick with VMs. Strict hardware requirements, specialized kernel modules, and license constraints may be harder to run with containers, negating their advantages.
3. Should this app migration use Migrate for Anthos?
Migrating your apps or workloads to the cloud isn’t just about shifting where the compute resources run; it’s also an opportunity to modernize them with containers. Using Migrate for Anthos (or Migrate for Compute Engine) gives you the ability to get your workloads in the cloud quickly, with minimal upfront downtime that’s easy to plan for.
However, even if you use the Migrate for Anthos wrapper, your application is still the same application. The benefits of the modern platform may not outweigh a legacy application and a rewrite may be the only way to meet your business needs. There are also some specific services from your VM that may not work with Migrate for Anthos, for example licensing requirements.
Migrate for Anthos can also be the first step in a larger migration effort. Once you’ve migrated the application to GKE, you can gradually break up a monolithic app into microservices by manually rewriting parts. Spreading out the migration effort gets you in the cloud sooner, giving you more time to modernize.
Next steps
A successful modernization starts with creating a full migration plan, testing the workloads, and monitoring them. You can experience the benefits of modernization with Migrate for Anthos by picking a small workload and trying it out for yourself!
How TapClicks’ Google Cloud Migration Makes Life Easy for Marketers

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Editor’s note: In this blog post we learn how TapClicks migrated to Google Cloud to offer their marketing customers a unified platform for data management, operations, insights, and analysis.
TapClicks is a smart marketing cloud, powered by data, that unifies our customer’s marketing. By choosing to migrate our core applications last year to Google Cloud, we cut costs, solved data-sharing concerns for our customers, and opened our stack up to a new ecosystem of possibilities.
The core problem that we’re solving for our customers is how to manage their marketing infrastructures data and operations. Life isn’t easy for marketers now. There are 7,000 different vendors servicing this space today – creating much complexity between digital agencies, media, and brands. Marketers face challenges in navigating all of these systems, logging in and out, understanding pacing goals, and managing the flow of marketing data so they can analyze and report internally as well as to their clients at scale.
We unify omnichannel campaign data (250 API connectors and 6000 Smart Connectors ™ ) from a plethora of marketing sources on an automated data warehousing solution, creating simplicity for organizations. Over 4,000 agencies, media companies, and brands use our Marketing Operations and Data Management Platform, which imports data at scale and creates an automatic data warehouse on Google Cloud. Teams can also leverage TapClicks, like our world class Facebook connector, to import data directly into Google Data Studios. Beyond importing and storing, we also provide data exporting to other Google solutions like Google Data Studio and Google Sheets. We also create interactive dashboards that let stakeholders and clients analyze their data, as well as automated, multi-channel reports that go out to clients at specified times. So channel comparisons, optimizations, attribution, and calculations are easily performed. Some of our customers are able to generate hundreds of thousands of individual reports and dashboards for their clients.
Although we may be best known for our reporting and analytics, we also empower teams managing the marketing operations workflow from customers and internal stakeholders, especially at scale. Our user-friendly, configurable system helps manage their orders and campaigns. Through automation of this process, we deliver tremendous amounts of efficiency, time saving, cost savings, and reduction of errors. The combination of these solutions makes up our unified platform, with additional capabilities like marketing intelligence that offers competitive and brand-level analysis. This is a disruptive solution in use by all leading media companies, agencies and many brands.
Partnering for possibilities
We faced a few challenges with our original tech stack, which included a mix of the leader in web services revenue, leaders in high performance data warehousing, as well as vendors on bare metal servers.
- One challenge was around costs, which were growing.
- Second, many of our customers work with multiple brands, and are very hesitant to share their data with the leader in web services, who’s often viewed as their competitor.
- Third, these vendors are more focused on their own revenue rather than a true long term partnership that would enable their customers to enjoy similar success as they have experienced.
When looking at other cloud providers, Google Cloud emerged for us as the front runner. They were competitive on costs, and their native Kubernetes support was superior— a big selling point for our DevOps team. There’s also a movement in the marketing and advertising industry away from AWS toward Google Cloud because of the data-sharing concern. Finally, most of our customers are already using Google Cloud tools, so there’s brand recognition and familiarity there, and easier integrations with their own systems.
Migrating to Google Cloud
Our migration, which took about five months, involved moving a significant chunk of our infrastructure, including our core applications, using Google Kubernetes Engine (GKE). In our legacy architecture, each of our clients was assigned to one of our virtual machines (VMs), and there was a lot of unused capacity because we had to provision for the max usage. We appreciated GKE’s cloud native capabilities, especially autoscaling, a huge benefit for our web application. We have varying usage patterns during the day, and though our application is mostly used during business hours, there are also days in the month of higher usage, and autoscaling saves us time and costs. GKE also makes deployments much easier, and we anticipate a lot of benefits there for our developer environments. We’ve moved some of our microservices into GKE and plan to move more in the future. All in all, we were able to migrate our core products and the bulk of our AWS spend successfully to Google Cloud.
We also moved from our other vendors Relational Database Service (RDS) to running MySQL on our own VMs on Google Cloud, which gives us more flexibility in terms of settings and fine tuning. We’re still trying to find the best mix as we’re modernizing our infrastructure, and we took this opportunity to migrate from MySQL 5.7 to 8.0.
Our next stage is exploring more of the capabilities and services of Google Cloud, including BigQuery, which we’re considering for our own data warehouse. The fact that we could also run Snowflake on Google Cloud, if needed, was another selling point for our migration.
We’re especially interested in BigQuery ML’s machine learning and natural language processing capabilities, which enabled better predictive insights. Our customers want insights from their campaigns— which are working, which are paying off, where should they invest next? Using our platform, they’re looking not only to generate reporting, but also identify opportunities to improve campaign performance. We plan to use AI and ML to improve those capabilities, so that our customers can seamlessly unlock insight and intelligence from their marketing data and campaigns.
Double-clicking on Google Cloud
For us, being able to deeply leverage and partner with Google Cloud to deliver those solutions on a single stack is critical, and we think our customers will love it. We see TapClicks and Google Cloud partnering at a level beyond what you typically see in a cloud provider relationship. Already, fifty percent of our company is working with various Google Cloud solutions, and we envision TapClicks and Google Cloud as extensions of each other, providing a single, powerful platform solution.
Google Cloud understands the partnership concept, and their team was able to shine a light on their services and what they could bring to the table. Compared to our previous experiences, dealing with the Google Cloud team has been a true pleasure. Now that we’ve migrated, we’re ready to take our next steps into the services available to us in the Google Cloud ecosystem, and the problems we’ll continue to solve for our customers. Learn more about TapClicks and BigQuery ML.
Plainsight Vision AI Available for Google Cloud Customers to Unlock Accurate, Actionable Insights

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Data-savvy businesses increasingly rely on images and videos for critical functions, and yet are challenged by the sheer mass of information—more than 3.2 billion images and 720,000 hours of video are created daily. This explosion in visual data has paved the way for the growth of computer vision, a form of artificial intelligence (AI) that enables computers to “see” the world similarly to the way people do, but with unblinking consistency, and greater accuracy.
The transformational impact and value of computer vision solutions are significant and has been a guiding objective for companies and AI developers. And yet, even as the applications for computer vision increase dramatically, architecting and implementing vision AI solutions remain highly complex. Visual data, such as images and video, are made up of thousands of pixels of information that represent millions of different patterns and meanings, which can make interpreting even a single image overwhelming from a computational perspective.
Many organizations struggle with deployments and fail to operationalize vision AI solutions due to development delays, machine learning and data science hiring challenges, inaccurate output, a lack of integration with existing infrastructure, difficulty of use, and high cost. Plainsight, with the power of Google Cloud resources, is addressing all these challenges and helping businesses by enabling the deployment of vision AI within enterprise private networks that can be managed easily and scaled economically.
Plainsight has announced availability of its vision AI platform on Google Cloud Marketplace. Businesses can now easily deploy end-to-end vision AI to private clouds to realize the full value of their video and other visual data for accurate, actionable insights across diverse use cases.
Delivering on the Promise of AI: Seeing What’s Hiding In Plain Sight
For organizations to integrate AI and machine learning into their businesses successfully, the technology must be powerful enough to solve real challenges, yet fast, easy, and accessible enough to ensure the innovation potential is realized. Plainsight on Google Cloud delivers the power of enterprise vision AI that’s quick and easy to use with Google Cloud resources that enable global scale, increased security, bolstered privacy, unified billing, and cost savings.
To streamline vision AI workflows, Plainsight facilitates the entire pipeline, from visual data ingestion and annotation, through continuous model training, deployment, and monitoring for easier innovation and faster time-to-production. Our platform accelerates vision AI development in a manner that is complete, accurate, and accessible to non-technical business leaders. We believe that AI should be available and accessible to anyone and everyone—so that teams across entire organizations can reap the benefits.
By integrating Plainsight into their private networks, companies worldwide can now leverage one intuitive platform for centralized control of streamlined vision AI model creation and training with optimized visual data handling for diverse enterprise solutions. These use cases include: social distancing monitoring, medical imaging, drug compound screening, defect detection in manufacturing processes, identifying gas leaks, or even livestock counting and crop health monitoring for agriculture, to name a few.https://www.youtube.com/embed/A7U_0UkjvEg?enablejsapi=1&
We enable customers so they can create successful solutions that enable them to clearly see their business from all angles and to take advantage of the knowledge visual data can reveal by simply and quickly operationalizing practical vision AI applications.
AI-Powered Dataset Creation, Automated Model Training & Easy Deployment Without A Single Line Of Code
For vision AI applications, success is inextricably dependent on the quality and quantity of the datasets required to train the relevant models. To aid enterprises in this vital stage, the Plainsight platform provides built-in data annotation for the fast and easy creation of datasets. This includes AI-powered features that accelerate the speed and quality of labeling such as SmartPoly, for the automated polygon masking of objects, TrackForward, to predict and automatically label objects from frame to frame in video annotations, and AutoLabel for automated object recognition and labeling based on pre-trained machine learning models, to highlight a few.

In addition, to ensure the success of AI integration, we significantly reduce time-intensive processes with Plainsight vision AI’s automated machine learning with continuous model training and easy deployment capabilities. In just a few clicks, users can leverage optimizations for the most reliable model training without endless experimentation cycles. And, models are easily deployed at scale all within one, easy-to-manage model operationalization process for the business.
Growing With Google Cloud
Plainsight is a vision AI innovation leader, developing solutions that address unmet needs for challenger brands and Fortune 500s across vertical markets. As a team recognized for succeeding where others have failed, our expanding partnership with Google Cloud provides a powerful combination that helps customers see and activate the value of their visual data with a suite of services in a secure and private manner.
Our vision AI Platform simplifies building and operationalizing AI to solve business problems enterprises are facing every day—and the demand is increasing. To accelerate our journey to faster, more accessible AI for enterprises, we knew we needed strong support to grow Plainsight and scale our backend tools to match our vision.
Google Cloud delivered everything, and more, in one program. The Startup Program by Google Cloud provided the technology and services for scale and the support we needed to maximize the value the Program provided us. The Startup Program has been a springboard for architecting Plainsight vision AI in the cloud, accelerating our goals and optimizing innovation, efficiency, and growth. The team also helped us optimize Google Ads campaigns, fueling adoption of Plainsight.
After launching the SaaS version of Plainsight Data Annotation in November 2020, we grew our user base by nearly 110x in just three short months. Google Ads has also dramatically increased website traffic, growing new users by nearly 5.75X and page views by over 5X. The Google team helped us identify where Google Cloud offerings could be leveraged instead of developing in-house solutions and offered best practices that enabled us to deliver faster on our initiatives.
Kubernetes was already the underlying component of our platform and leveraging Google Kubernetes Engine (GKE) as a managed service removed a layer of complexity. By combining GKE and Anthos, we were able to standardize our deployments, aligning to how our customers leverage Anthos for enterprise applications in their own organizations. In addition, as a fast-moving, customer-centric company we use Google Workspace to help us centralize and manage our day-to-day work internally. By leveraging multiple products across Google’s ecosystem, we take advantage of a holistic partnership that has helped our business tremendously as we scale.
Leveraging Google’s Partners for Strategic Consultation
To facilitate this expansion of our partnership with Google and to maximize our use of Google Cloud services, we are working with DoiT International, a Google Managed Services Provider and 2020 Global Reseller Partner of the Year. DoiT provides us with ongoing technical consultation for cloud-native architecture, Google Cloud Marketplace integration, production-grade Kubernetes support, Google Cloud cost optimization, and technical support. The DoiT team has been invaluable in compiling best practices, tips, and strategies from their vast experience with various cloud customers to ease our Marketplace integration and is providing input for infrastructure strategy to support our continued rapid growth.
Plainsight Delivers Enterprise Vision AI Through The Google Cloud Platform Marketplace
Plainsight vision AI is now available to Google Cloud Customers on Google Cloud Marketplace enabling organizations across industries to deploy private Plainsight instances within their own environments. Marketplace customers will benefit from Google Cloud privacy, security, scalability and unified billing through their Google Cloud account.
Combining the powerful benefits provided by Google Cloud resources with Plainsight’s vision AI Platform into private networks, enterprises worldwide can now leverage one intuitive platform for centralized control of streamlined vision AI model creation and training with optimized visual data handling for diverse enterprise solutions.
Through our Google partnership, we’re able to leverage a powerful foundation that allows us to rapidly innovate, scale and accelerate delivery on our vision AI platform capabilities. By executing on our vision to make AI easier, faster and more accessible for all users across entire enterprises, we’re helping businesses see more and by seeing more, they’ll have the power to solve more.
If you want to learn more about how Google Cloud can help your startup, visit our page here where you can apply for our Startup Program, and sign up for our monthly startup newsletter to get a peek at our community activities, digital events, special offers, and more.
Why America’s Leading Mortgage Technology Provider Runs its Business on Apigee

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Black Knight is a leading provider of technology, data, and analytics to the mortgage industry, catering to both large and mid-tier banks in the United States. Over the past few decades, we tended to manage customer integrations on a case-by-case basis. Whenever a bank needed to connect with a Black Knight app, we’d launch another integration project. Lather, rinse, repeat. Needless to say, this was inefficient; we knew we had to do something to centralize this process.
Building versus buying an API management platform
To start, we created some homegrown API solutions. Despite being largely successful with one of these solutions, we saw that technology advances were outpacing our capacity to update our solutions in-house. We knew we needed to move toward an API platform that would support RESTful architecture and that would fully enable mobile solutions. It also had to be extremely secure. Knowing how complicated such a platform would be to build ourselves, we decided that our developers were better off focusing on providing core solutions to Black Knight clients; engaging with an outside provider was the right way for us to advance our API strategy.
After a lengthy proof-of-concept process, we went into production with the Apigee API Management Platform from Google Cloud in 2018. In our opinion, Apigee was the most complete, robust, technically sound and full-featured option from among all of the API management tools we evaluated. Its ease of use was the deciding factor for our developers, and the Apigee analytics capabilities provided considerable insight into the anatomy of an API call—something the other platforms we considered didn’t do as well.
Choosing Apigee meant that we didn’t have to focus on developing and maintaining a tool or spend enormous amounts of money trying to keep up with security patching. For a large company like Black Knight, an API management tool is something we don’t want to spend a lot of time on. We know that Google Cloud devotes tremendous resources to it, and it would be difficult to replicate that in-house.
Black Knight has more than 150 client-facing applications. Almost half of them now are built with APIs that are externally facing, and many of these apps use APIs that integrated with other Black Knight applications. Add to that the huge number of applications out there that come from clients and third-party vendors, and suddenly, we had a management challenge from an API perspective.
Driving cultural change
We came to Apigee with the goal of containing and empowering our huge ecosystem of APIs, customers, third parties, and internal users.
Given Black Knight’s size, our developers and customers understandably each have different business goals, so getting everyone to come to a centralized platform is a great opportunity. My role is to help people consider other options so they can be open to the benefits that Apigee brings us.
Now that we’ve engaged with Apigee for over a year, we see two big benefits. First, the huge reduction in point-to-point integrations has produced tremendous efficiencies for us and our customers, who now get instant integration once they’ve been authorized for a particular API. Second, Apigee’s capacity for mobile enablement lets us satisfy our customers’ needs for secure mobile apps.
Simplifying security
From a technical perspective, security is complicated for mobile apps. We’re often accessing sensitive information on a mobile device that can’t always be trusted. This kind of scenario requires us to implement a number of security precautions to help ensure confidential information remains protected.
The Apigee API management platform addresses these needs in the simplest way possible. It solves complex problems related to security without having to deploy a new API proxy each time we need to support a particular mobile device upgrade. Our back-end applications remain protected because Apigee helps manage security, requests, access tokens, and authorizations. Today, our back-end applications work with Apigee to communicate with mobile devices or servers coming over the internet.
Apigee has also enabled us to do a better job sharing a variety of APIs. The developer portal lets us stitch together APIs and get more creative about how we can innovate and build new solutions based on these collections of APIs. At this point, anybody that has a nondisclosure agreement with us can register for the developer portal. The nature of our business is such that we can’t just open up our APIs to anybody, but it’s available to our contracted third parties.
Our Apigee journey has been exciting, and we’re making great progress. I’m looking forward to what innovations we will come up with next, thanks to the way Apigee enables us to create, implement, and deliver.
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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.
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