As an IT leader, you’re asked to do it all: innovate and optimize your tech stack for business outcomes — all while being secure and compliant. It takes heroic efforts to achieve innovation and progress while also tightening budgets and teams. This is why many of you are considering migrating applications to Google Cloud, for benefits like scalability and flexibility, security and compliance, disaster recovery and business continuity, and cutting-edge technologies at lower costs.

To help you do this, we suggest using Google Cloud’s Migrate to Virtual Machines – part of Migration Center. This managed cloud service lets you lift and shift workloads at scale to Google Cloud Compute Engine with minimal changes and risk.

And recently, we rolled out our latest release which introduces support for workload migration from AWS to Google Compute Engine. With this addition, you can now migrate both your on-prem and AWS workloads at scale. This means centralized management for your end to end workload migration journey from both sources via Cloud Console or APIs. 

Simple and easy migrations from AWS and VMware sources to Google Cloud

Migration of AWS EC2 instances directly to Google Compute Engine using Migrate to Virtual Machines follows a well established and easy journey, which means a minimal learning curve for users who are already migrating workloads from VMware. Workload migration is agent-less, which means you do not need to access or alter workloads as a prerequisite for migration, allowing you to execute zero-touch migrations. Migrate instance data with no interruptions to the running workload at the source for a fast cutover to Google Cloud. In addition, our end-to-end cloud console interface surfaces your AWS EC2 inventory, migrations, and groups so you can execute migrations without ever leaving the cloud console interface. 

Large-scale migrations 

Completing a large-scale migration project in a timely manner calls for careful planning and streamlined migration sprints. The Migrate to Virtual Machines’ Groups construct enables you to group source VMs together in the planning phase. When it’s time to execute the planned migration, VM Groups let you execute migration operations on a group level, or on a subset of the group, streamlining the process at scale.

Minimal downtime and risk

Application uptime is key to keeping your business running. Every migration with this latest release of the service periodically replicates data from the source workload to the destination without manual steps or interruptions to the running workload, minimizing workload downtime and enabling fast cutover to Google Cloud. You can also launch non-disruptive migration tests — referred to as test-clones — to help you validate that these workloads will work properly in the cloud before cutting over. This helps avoid issues that might have otherwise been costly or disruptive to your business. 

How the service works

Migrations simply work, at scale, in a managed service fashion. With Migrate to Virtual Machines, there’s no requirement to provision or manage migration-specific resources in the cloud. The service uses replication-based migration technology to lift and shift workloads from source environments to Google Cloud. The Migrate Connection replicates source VM disk snapshots in the background with no interruption to the source workload. Replicated data is encrypted in transit and at rest, and when you instantiate a migrating VM using a test-clone or cut-over, the service seamlessly adapts your source VM operating system to boot and run natively in the cloud — including configuring network settings and deploying Google Cloud guest packages. 

The migration journey of an EC2 instance — or VMware VM — to Google Cloud is comprised of the following steps:

1. Onboarding a source VM for migration: Onboard one or more VMs for migration from the source environment fleet.

2. Configure landing zone target: You can migrate an instance to any Google Cloud project in your environment and update landing zone details at any time before executing a test-clone or cutover.

3. Initiate VM data replication of source workload: Migrate to Virtual Machines periodically replicates instance disks to the cloud with no interruption to the source instance. You can control replication frequently and pause or resume at any point in time. 

4. Test migrating instance: Test-clone creates a copy of your source instance in the defined landing zone to validate the migrating instance in the cloud before executing a cut-over. You can repeat the test-clone multiple times to multiple landing zones for thorough validation

5. Cutover migrating instance: Cutover operation shuts down your source instance and then performs the short final sync to Google Cloud. Migrated VM is instantiated in the target landing zone.

Getting started with Migrate to Virtual Machines 

It’s quick and easy to start migrating your AWS EC2 instances and on-premises VMs today:

1. Enable the vmmigration API in a Google Cloud project 
2. Create an AWS source in your environment
3. Onboard and initiate replication of instance data from source 
4. Set migrating instance target details. 
5. Perform non-disruptive tests of your migrating instance using test-clone
6. Cutover your instance to the cloud with minimal down time

You can also visit our website to learn more about Migrate to Virtual Machines. If you know you have to migrate in 2023 but aren’t sure how to get started, you can sign up for a free discovery and assessment of your current IT landscape so we can help craft the ideal migration plan for you and your business.

Accelerating digital transformation

Digital transformation is what propels businesses and industries forward. Organizations of all sizes—from startups to global enterprises—focus on digital transformation not only to make scaled improvements, but also to drive significant change and fully embrace the digital age. The pandemic has jump started and pushed many organizations into full gear to digitize their business models and transform with increased business agility, resiliency, and velocity, while driving new innovation and business values for the customers.

However, according to the Boston Consulting Group, only about 30% of companies navigate a digital transformation successfully. Many large scale digital transformation programs failed because of lack of clear business priorities, top-down executive sponsorship, or dedicated resources and commitment to see it through.

Laying the foundation for digital transformation success

Digital transformation drives foundational change in how an organization operates, optimizes internal resources, and delivers value to customers; however, this doesn’t just happen overnight. Digital transformation requires a programmatic approach through an incremental yet agile, cost-effective, value-driven, and sustainable strategy to drive successful transformation across the organization.

One of the critical factors foundational to success is Cloud FinOps (Cloud Financial Operations). Cloud FinOps is an operational framework and cultural shift that brings technology, finance, and business together to drive financial accountability and accelerate business value realization through cloud transformation. In the context of Digital Transformation, it requires new ways of working and operating models to drive behaviors and cultural change that foster cross-functional collaboration, drive accountability, provide greater cost transparency, and promote a blameless culture.

Most importantly, Cloud FinOps serves as an enabling function to drive successful digital transformation programs and enable business agility by breaking down the boundaries between technology, finance, and business teams. Through this cross-functional team collaboration, technology leaders partner with finance and business leaders to better understand the technology investments to create sustainable business outcomes. By doing so, business priorities become more clear and the focus shifts to value creation, customer-centricity, and innovation.

As such, companies are reinventing their business models to fund value streams and connect cloud technology investments to strategic business outcomes. With the increased visibility of the cloud costs, finance teams are also gaining greater accuracy in tracking cloud spend against budgets. Organizations can align the TCO of the technology services to the value metrics to make better informed future investment decisions and forecast demand.

Cloud FinOps to accelerate business value realization

The successful deployment and implementation of Cloud FinOps building blocks will enable organizations to accelerate digital transformation beyond cost savings, including the ability to:

• Accelerate business value realization and innovation
• Drive financial accountability and visibility
• Optimize cloud usage and cost efficiency
• Enable cross organizational trust and collaboration
• Prevent cloud spend sprawl
• Break down of departmental silos

Organizations that are successful in digital transformation most often have established processes to measure and track business value. One of the key building blocks of Cloud FinOps is “Measurement & Realization.” By establishing a robust value measurement approach to track and monitor the business value metrics toward business goals, we are bringing technology, finance, and business leaders together through the discipline of Cloud FinOps to show how digital transformation is enabling the organization to create new innovative capabilities and generate top-line revenue.

Business value metrics fall across several factors: cost efficiency, resiliency, velocity, innovation, and sustainability. We suggest assigning KPIs to the following metric categories:

Cost efficiency: Measure cost efficiency through infrastructure savings, migration, and support costs. Customers will commonly start with metrics such as cost of compute and storage per day-week-month, and evolve to unit metrics such as cost per customer served or cost per transaction, where the cost of an application stack is aligned to customer drivers.

Resiliency: Enhance operational resiliency with improvement in service quality and security risk posture. Traditional measures such as system service level and the frequency and duration of critical downtime events are effective measures of IT durability. Customers can also augment these metrics by associating a cost per minute of downtime events, reflecting not only the direct impact of these events but opportunity costs as well.

Velocity: Decrease time to market by accelerating fluidity in product and service delivery. By moving to a cloud-based microservices architecture, customers commonly achieve benefits of increasing software release frequency, as well as being able to run many more test scenarios prior to release, resulting in higher quality code. As an example, our recent Google’s State of DevOps Report 2021, shows that elite performers have 973x more frequent code deployment and release frequency than the low performers.

Innovation: Enable a culture of rapid experimentation to drive innovation and cloud transformation. With cloud technology, companies can avoid the financial constraints of fixed cost investments and lengthy procurement lead times. As a result, the marginal cost of experimentation and time from ideation to experimentation can drop significantly while the number of experiments per unit of time can grow dramatically.

Sustainability: Embed true environmental and social sustainability metrics across the organization by adopting a circular economy strategy and building sustainability into everything we do – from running applications on zero net emissions virtual machines to reducing carbon footprint with enhanced productivity and collaboration services. According to Accenture, companies with average on-premise to cloud migrations can drive 65% energy reduction and carbon emission reduction of 84%1.

Getting started

The Cloud FinOps journey starts with defining or updating your metrics. Since business goals and strategic imperatives will likely change over time, it is important to review the Cloud FinOps metrics whenever the goals change. The review of metrics should include the changes in business goals when there are changes in the internal priorities of the team. Executive leaders need to identify dependency relationships between technology and business outcomes to improve the impact of metrics on decision making and to better prioritize and invest in evolving business and technology capabilities. Defining good metrics is not just about aligning to business goals and demonstrating value. It is also important to help prioritize strategic initiatives, guide effective resource allocation, and generate awareness across the organization to drive a shift in mindset with the new way of operating in the cloud.

The pandemic has accelerated the need for companies to modernize their digital capabilities. With technology-driven disruptions across all industries, it has never been more important for organizations to transform themselves, embrace an agile mindset, and make bold investments in cloud technology and capabilities to achieve sustainable business outcomes.

So, where are you now in your cloud FinOps journey, and how do you move beyond the challenges ahead? Google can help you start the conversation and accelerate your path to maximizing business value with the cloud.

No matter where you are on the cloud transformation journey, through an interactive session with Google, we can bring executives across the organization together to work toward a shared vision and a plan to accelerate and realize business value in the cloud. If you are interested in more information, please contact us.

Special thanks to Pathik Sharma, Bruce Warner, Jon Naseath, and Nihar Jhawar for their contributions and sharing their domain expertise to this important Cloud FinOps topic.

Cloud offers a proven way to accelerate end-to-end chip design flows. In a previous blog, we demonstrated the inherent elasticity of the cloud, showcasing how front-end simulation workloads can scale with access to more compute resources. Another benefit of the cloud is access to a powerful, modern and global infrastructure. On-prem environments do a fantastic job of meeting sustained demand but Electronic Design Automation (EDA) tooling upgrades happen much more frequently (every six to nine months) than typical on-prem data center infrastructure upgrades (every three to five years). 

What this means is that your EDA tool can provide much better performance if given access to the right infrastructure. This is especially useful in certain phases of the design process.

Take for example, a physical verification workload. Physical verification is typically the last step in the chip design process. In simplified terms, the process consists of verifying design rule checks (or DRCs) against the process design kit (PDK) provided by the foundry. It ensures that the layout produced from the physical synthesis process is ready for handoff to a foundry (in-house or otherwise) for manufacturing. Physical verification workloads tend to require machines with large memories (1TB+) for advanced nodes. Having access to such compute resources enables more physical verification to run in parallel, increasing your confidence in the design that is being taped out (i.e., sent to manufacturing).

At the other end of the spectrum are functional verification workloads. Unlike the physical verification process described above, functional verification is normally performed in the early stages of design and typically requires machines with much less memory. Furthermore, functional verification (dynamic verification in particular) accounts for the most time (translating directly to the availability of compute) in the design cycle. Verifying faster, an ambition for most design teams, is often tied to availability of right-sized compute resources. 

The intermittent and varied infrastructure requirements for verification (both functional and physical) can be a problem for organizations with on-prem data centers. On-prem data centers are optimized for maximizing utilization—this does not directly address access to right-sized compute to deliver the best tool performance. Even if the IT and Computer Aided Design (CAD) departments choose to provision additional suitable hardware, the process of provisioning, acquiring and setting up new hardware on-prem typically takes months for even the most modern organizations. A “hybrid” flow that enables use of on-prem clusters most of the time, but provides seamless access to cloud resources as needed would be ideal.

Hybrid chip design in action

You can improve a typical verification workflow simply by utilizing a hybrid environment that provides instantaneous access to better compute. To illustrate, we chose a front-end simulation workflow, and designed an environment that replicates on-prem and cloud clusters. We also took a few more liberties to simplify the environment (described below). The simplified setup is provided in a GitHub repository for you to try out.

In any hybrid chip design flow, there are a few key considerations:

1. Connectivity between on-prem infrastructure and the cloud: Establishing connectivity to the cloud is one of the most foundational aspects of the flow. Over the years, this has also become a very well-understood field, and secure, high availability connectivity is a reality in most setups. 
   
   In our tutorial, we represent both on-prem and cloud clusters as two different networks in the cloud where all traffic is allowed to pass between these networks. While this is not a real-world network configuration, it is sufficient to demonstrate the basic connectivity model.
   
2. Connection to license server: Most chip design flows utilize tools from EDA vendors. Such tools are typically licensed, and you need a license server with valid licenses to operate the tool. License servers may remain on-prem in the hybrid flow, so long as latency to the license server is acceptable. You can also install license servers in the cloud on a Compute Engine VM (particularly sole-tenant nodes) for lower latency. Check with your EDA vendors to understand if you can rehost your license services in the cloud.
   
   In our tutorial, we use an open source tool (Icarus Verilog Simulator) and therefore, do not need a license server.
   
3. Identifying data sources and syncing data: There are three important aspects in running EDA jobs: the EDA tools themselves, the infrastructure where the tools run, and the data sources for the tool run. Tools don’t change much, and can be installed on cloud infrastructure. Data sources, on the other hand, are primarily created on-prem and updated regularly. These could be SystemVerilog files that describe the design, the testbenches or the layout files. It is important to sync data between on-prem and cloud to maintain parity. Furthermore, in production environments, it’s also important to maintain a high-performance syncing mechanism.
   
   In our tutorial, we create a file system hierarchy in the cloud that is similar to one you’d find on-prem. We transfer the latest input files before invoking the tool.
   
4. Workload scheduler configuration and job submission transparency: Most environments that leverage batch jobs use job schedulers to access a compute farm. An ideal environment finds the balance between cost and performance, and builds parameters in the system to enable predictive (and prescriptive) wrappers to job schedulers (see picture below).
   
   In our tutorial, we use the open-source SLURM job scheduler and an auto-scaling cluster. For simplicity, the tutorial does not include a job submission agent.

Other cloud-native batch processing environments such as Kubernetes can also provide further options for workload management.

Our on-prem network is called ‘onprem’ and the cloud cluster is called ‘burst’. Characteristics of the on-prem and burst clusters are specified below:

Once set up, we ran the OpenPiton regression for single and two-tile configurations. You can see the results below:

Regressions run on “burst” clusters were on average 30% faster than on “onprem”, delivering faster verification sign-off and physical verification turnaround times. You can find details about the commands we used in the repository. 

Hybrid solutions for faster time to market

Of course, on-prem data centers will continue to play a pivotal role in chip design. However, things have changed. Cloud-based, high performance compute has proved itself to be a viable and proven technology for extending on-prem data centers during the chip design process. Companies that successfully leverage hybrid chip design flows will be able to better address the fluctuating needs of their engineering teams. To learn more about silicon design on Google Cloud, read our whitepaper “Using Google Cloud to accelerate your chip design process”.

Operating for 23 years, Rustomjee has carved a niche for itself in the ever-growing real estate sector. Rustomjee’s portfolio includes 14.32 million square feet of completed projects; 12 million square feet of ongoing development; and another 28 million square feet of planned development. These projects span the best locations of the Mumbai Metropolitan Region. Rustomjee adds value to the lives of its homeowners through its core business, its corporate social responsibility initiatives, and its philanthropy. The business strives to ensure that every blueprint includes child-friendly spaces for parks, playgrounds, and learning rooms, encouraging families to spend quality time with each other.

In the 17 years Rustomjee’s Corporate Head of Information Systems, V M Samir, has worked with the business, it has grown from 100 employees to more than 800 employees – primarily professionals such as engineers, architects, lawyers, accountants, and regulatory consultants. The remainder work in marketing, sales, administration, security, human resources, and other associated areas.

Historically, Samir says, the real estate industry globally has lagged in embracing new workplace technologies, making building business cases, securing sponsorship, completing implementations, and encouraging adoption a difficult task.

G Suite powers cloud journey

Rustomjee started operations running an on-premises email service. However, the business wanted to upgrade its anti-spam capabilities and, in 2007, turned to G Suite. “There was no practical way I could build an anti-spam engine within that service that could match the power of the G Suite anti-spam engine and the intelligence held within its databases,” says Samir. “Our second key reason for moving was the lower cost of G Suite relative to an on-premises service that required us to spend on compute, backup, storage, and administration resources. Running G Suite would also help ensure users could still access their emails if their machines experienced an outage.”

Finally, G Suite enabled Rustomjee to access and compose emails from any location – a luxury for a real estate organization whose workers often attended construction projects with poor connectivity. “Finally, G Suite was the only service in those days that integrated calendar, meeting, and storage repositories through single sign-on. Google was so far ahead of the curve at that time and we saw the potential of G Suite to transform our communications and ultimately our business.”

“We did not have to shut down the business operations during the migration because Google Cloud Platform complemented every idea we had. And when my business users came to work on the Monday morning [after the final migration], everything was stable and the performance had improved. We told them our infrastructure had changed and they should start thanking Google Cloud!”

—V M Samir, Corporate Head, Information Systems, Rustomjee

The business started its cloud and IT modernization journey by decommissioning its on-premises email servers and using G Suite for Business. It began testing in March 2007 and went live with all production email services for 500 users in June 2008.

The intuitive nature and ease of use of G Suite made the transition seamless. “I did not have to undertake a large-scale change management exercise,” says Samir. “Users bought into the program and acquired the necessary knowledge quickly, meaning our adoption rate was extremely fast.”

With G Suite, email became the new norm to complete a range of tasks at Rustomjee. “We started exchanging CAD drawings, videos, high-resolution images, and other large files with our consultants,” says Samir. “These files had been difficult to store in on-premises environments.”

Rustomjee has improved collaboration and performance with G Suite, primarily due to four services. Gmail enables workers to communicate seamlessly externally and with each other, while Calendar enables them to set up and synchronize meetings. These meetings can be conducted through Hangouts Meet. “If a group of people internally need to discuss a work order or contract, they can coordinate calendars, sit at different locations within our organization, and collaborate using audio and video on a common service,” says Samir. “They can also work from and update a single document in Drive.”

With email and other collaboration applications running smoothly, Rustomjee saw an opportunity to enhance its technology infrastructure. The business had started operations running workplace applications on servers in small air-conditioned rooms. These servers ran databases and applications that sent data across a network to endpoints including desktops and laptops.

Expansion and the changing demands of workplace technology prompted Rustomjee to upgrade its capabilities, and the business commissioned a data center. However, Rustomjee’s continuously fast-growing compute and storage requirements, as well as the need to access new technologies to innovate and compete, quickly strained its technology model. “We required eight weeks each time we needed to add new compute and storage to our environment,” says Samir. “In addition, the heavy investments in our captive data center meant we were unable to easily leverage new technologies and decommission old technologies.”

Public cloud supports growth

Rustomjee reviewed its options and decided public cloud services could best meet its ongoing needs. “The rising cost of maintaining old hardware would force us to refresh data center technologies every five to seven years,” says Samir. “More broadly, a hardware-defined data center could not adapt quickly in the cloud-computing world, making it difficult to align compute with growth.”

The business started by moving its corporate website and microsites to a public cloud service to accommodate increased traffic delivered from a change in business strategy. “We saw an opportunity to shift our marketing and advertising from print advertising to digital platforms,” says Samir. “We wanted to be available to buyers from the point at which they start looking at properties online.”

However, Rustomjee’s digital marketing teams found it difficult to scale instances in line with demand, and work with complex user administration screens and control panels.

“With Google Cloud Platform, we’ve achieved a considerable reduction in timelines and simplified technology management and administration. All of our business users are delighted.”

—V M Samir, Corporate Head, Information Systems, Rustomjee

Google Cloud Platform presented an opportunity for Rustomjee to run its websites and microsites in a reliable, scalable, and responsive infrastructure. “Our evaluation confirmed Google Cloud Platform could support our growing demand for compute and storage,” says Samir. ‘In addition, because we undertake projects that are geographically distributed, networking – not only within the data center, but that could be accessed from any location – was very important. Only Google Cloud Platform had its own networking infrastructure.”

“More broadly, in a cloud environment, we could select any database we needed and start consuming operating systems as a service,” he adds. “In addition, we did not have to invest capital in licenses and hardware and we could always resize network bandwidth. Further, we could take advantage of pay-as-we-use cloud services, and link this to business growth.”

Google Cloud Platform also allowed Rustomjee to reduce the size of the teams needed to manage and operate its infrastructure. “When you have infrastructure running in the data center and in disaster recovery locations, you need to have a large pool of resources working around the clock to ensure constant uptime, sound backup, and good replication measures in place,” says Samir. “With the cloud, everything is simplified and we do not have to consider issues like how many hard drives have failed in on a particular morning.”

The business started testing and created its first virtual machine instance to Google Cloud Platform in April 2017. Because the Mumbai data center was not yet operating Rustomjee initially hosted its instances in the Google Cloud Platform Singapore Region. This initial move enabled the business to reduce the number of required virtual machine instances from six to one. After a year of running the website on Google Cloud Platform, the business found the simplicity of scaling compute resources meant its digital marketing teams were running more campaigns and servicing more leads, while compute spend had fallen by 56 percent. Furthermore, Rustomjee was not experiencing latency that impacted the user experience.

The opening of the Google Cloud Platform Region in Mumbai in late 2017 gave Rustomjee an opportunity to use compute, storage, and networking services located domestically. The business decided to go all-in on Google Cloud Platform and migrated a range of applications to the service.

These included an SAP enterprise resource planning system, running initially on Oracle but moved to the SAP HANA in-memory computing platform, with the assistance of advisory consultants from a leading firm. This system is integral to Rustomjee’s successful operations, meaning it has to be highly available and responsive. “All our financials are captured and stored in this system, as well as projects, materials management, order management, financial systems, and sales ordering systems, both procurement and supply-side,” says Samir. “In short, we cannot live without SAP ERP!”

Rustomjee turned to SAP specialist partner InfraBeat Technologies, a leading network implementation provider, and Google engineers to complete the migration successfully. “We were all in this together and collaborated closely to deliver the project successfully,” says Samir. “We were very impressed by the expertise and skills of everyone involved.”

A nine-day migration

With assistance from Google Cloud and the partners, Rustomjee moved all its SAP workloads, from sandbox to development, development to quality, and quality to production, in just nine calendar days, without impacting the business. “We did not have to shut down the business operations during the migration because Google Cloud Platform complemented every idea we had,” says Samir. “And when my business users came to work on the Monday morning [after the final migration], everything was stable and performance had improved. We told them our infrastructure had changed and they should start thanking Google Cloud!”

Moving to Google Cloud Platform enabled the business to complete certain customer invoicing workloads in just two hours, down from 13 hours previously. Backups of the SAP enterprise resource planning system that had taken up to six hours, were now being completed in six minutes.

“We have now fully embraced a cloud-first approach and have moved 100 percent of our workloads to the cloud. We depend totally on Google Cloud Platform to run our business.”

—V M Samir, Corporate Head, Information Systems, Rustomjee

Eight weeks down to 20 minutes

Rustomjee has also cut the eight-week cycles needed to set up the infrastructure and applications for a new real estate project, and integrate it into the SAP system, to just 20 minutes. “With Google Cloud Platform, we’ve achieved a considerable reduction in timelines and simplified management and administration,” says Samir. “All of our business users are delighted.”

With its website and enterprise resource planning system running successfully on Google Cloud Platform, the business decided to move its virtual application delivery environment into the service. “We decided to move all 800 of our employees into the cloud, so they could access applications through any endpoint, be it a mobile phone, tablet, thin client, desktop, or laptop,” says Samir.

The business decided to replace an existing application virtualization product with public images available on Compute Engine, with testing of Android, iOS and Windows operating systems across a range of devices proving highly successful. “Running the remote desktop service in Compute Engine and using public images enabled us to operate a leaner, simplified desktop as a service environment,” says Samir. “We have been able to deploy business function-specific virtual machine instances on the cloud and compartmentalize data to the business functions that need them. The business completed the move – including 8.1TB of data – in just six weeks. “The only workloads we did not move during that period were intensive workloads for visualization,” says Samir.

However, the four teams that did not use the remote desktop as a service environment – and that created visualization-intensive workloads – were working in traditional ways, compromising productivity and increasing risk. “They used to be given a desk in their respective offices and their workstations loaded with the applications,” says Samir. “There was no way of taking hourly backups of these devices and there was no recovery mechanism for the applications, because they were not in the data center.

“The other challenge was what happens to the data, because we operate out of multiple locations. The users in these four teams always had to come back to pre-assigned desks and continue working from there. This was counterproductive.”

The business subsequently implemented virtual machine instances with GPU access for visualization-intensive workloads. “We started evaluating Nvidia T4 (Tesla) GPUs in the Mumbai Region on 13 February and went live on 11 March in Mumbai,” says Samir. “By moving these 40 team members to Google Cloud Platform, we have enabled them to work with visualization workloads from any location, improving productivity and flexibility.”

Focus on core business

With Google Cloud Platform, Rustomjee can focus on running real estate projects and using technology to enable them. “I don’t have to refresh my technology every five to seven years, and I can leverage new technologies as they come on stream,” says Samir.

Reliable application access

With the flexibility and scalability of Google Cloud Platform, Rustomjee is now well-positioned to support further growth and operate in accordance with the time-limited nature of the real estate industry in India. “If we have promised to hand over the keys to a customer by a certain deadline and we fail to do so, we face a penalty of 10 percent of the cost of the project,” explains Samir. “The Indian Government introduced this regime in 2017 and business and technology have to align with its requirements.

“Google Cloud Platform is the right service to move us forward and enable us to overcome these challenges,” he adds. “We have now fully embraced a cloud-first approach and have moved 100 percent of our workloads to the cloud. We depend totally on Google Cloud Platform to run our business.”