Oden Technologies is using the Internet of Things (IoT) to improve the factories of today. The giant network of “things” (including people) connected to each other via the Internet has the potential to reduce waste, increase efficiency, and improve safety across all walks of life. Oden is leading IoT innovation in manufacturing by combining wireless connectivity, big data, and cloud computing.

The use of data to improve manufacturing is practically as old as manufacturing itself. But the computerization of manufacturing has resulted in broad and rapid changes to the way data is collected and processed, as well as the sheer volume of data available.

Oden’s goal is to help manufacturers tap into this data to quickly identify process trends and even warning signs of machine breakdown. Such visibility can reveal opportunities to improve manufacturing and maintenance processes that reduce waste and increase profit margins.

Oden designs and develops data collection devices that can plug into almost any kind of machine and can wirelessly transmit data with minimal complexity and setup time.

Once devices are installed, the Oden technology platform processes data to give manufacturers cutting-edge analytics that are easy to comprehend. Analysis produced by the platform provides factory engineers with data points such as detailed root-cause analysis down to the second, factory-wide performance in real-time, and trend analysis.

Improving cloud delivery

Oden’s previous cloud platform performed satisfactorily, but the company evaluated alternatives in search of potential reductions in cost and complexity and increases in performance.

When evaluating Google Cloud Platform, Oden discovered it would require fewer virtual machine (VM) instances for equivalent performance, which would cut costs. Furthermore, Oden could gain more sophisticated data analytics and machine learning capabilities compared with its existing cloud provider.

Today, Oden runs its entire platform on Google Cloud Platform including Google Compute Engine, Google Cloud Pub/Sub, Google Cloud Bigtable, Google Stackdriver, and Google Kubernetes Engine.

“In order to serve our customers, we need a cloud platform that can scale reliably while keeping costs low, perform under heavy loads, and consistently deliver sophisticated features such as machine learning,” says Willem Sundblad, CEO and Founder at Oden Technologies. “Google Cloud Platform is way ahead in all of these areas compared to our previous cloud provider.”

Capturing tens of millions of metrics a day

Using Google Cloud Platform, Oden can help an average factory capture and store approximately 10 million metrics on a single manufacturing line every day.

Metrics can include extremely granular detail, such as the amount of electricity going to machines, the amount of raw material consumed, and the volume of material produced. Sensors can also capture and transmit environmental information such as temperature, humidity, and dew point so that manufacturers can identify weather-related and seasonal impacts on production.

The updated Oden Cloud Platform uses Kubernetes Engine—powered by the open source Kubernetes system—to run application program interfaces (APIs) that capture data from Oden’s wireless devices on the factory floor.

Google Cloud Pub/Sub then sends the data in real time to Google Cloud Bigtable, where data is processed using Oden’s proprietary analytics tools. Google Stackdriver supports Google Cloud Platform monitoring, logging, and diagnostics, which help Oden deliver its cloud platform with confidence.

Oden Technologies builds dashboards powered by Kubernetes Engine, which pull analyzed data from Google Cloud Bigtable. The dashboards provide customers with real-time visibility into their manufacturing lines. Oden Factory Cloud dashboards allow customers to delve deeper into their data to fine-tune production processes or discover the root causes of production issues.

With the previous cloud provider, Oden required 80 VM instances to run the dashboards. With Google Cloud Platform that number has been cut to 45, which dramatically reduces costs and complexity.

“We migrated from our previous cloud provider to Google Cloud Platform in just one month,” says Willem. “Further, our storage and data analytics costs have decreased by 30%. Cost savings like these allow us to protect customers from rising expenses, keeping us focused on bringing the best products possible to market.”

Faster data access; more efficient factories

With Google Cloud Platform, Oden can now deliver a complete factory analytics picture to manufacturers. In environments where thousands of variables affect the bottom line, businesses can now automatically and perpetually record machine and performance measurement. Oden Factory Cloud gives customers access to comprehensive data insights and can eliminate reliance on onsite infrastructure investments to run their own analytics.

Because manufacturers have access to live data and can analyze production data quickly, they can troubleshoot and resolve problems in minutes rather than months. Such information helps improve product quality, minimize unplanned downtime, cut costs, and improve profitability.

“With the help of Google Cloud Platform, we are helping our customers to be data-driven, which wasn’t possible before,” adds Willem. “They now understand that data is their most important asset. That allows them to be more innovative and continually improve their production processes.”

At Precognitive, we were able to start with a blank technology slate to support our fraud detection software products. When we started building the initial version of our platform in 2017, we had some decisions to make: What coding language to use? What cloud infrastructure provider to choose? What database to use? The majority of the decisions were straightforward, but we struggled to decide upon a database. We had plenty of collective experience with relational databases, but not with a wide-column database like Cloud Bigtable—which we knew we’d need to scale our behavior and device workloads. At launch, our products were supported by a self-managed database, but we quickly migrated to Cloud Bigtable, and we love it.  

To efficiently support our bursty, real-time fraud detection workloads, we needed a cloud database that could satisfy the following key requirements:

• Stability to keep up with increased adoption of our products
• Intelligent scaling that avoids bottlenecks
• Native integrations with BigQuery and Cloud Dataproc
• Managed services that free up our engineers’ time to work on our products

Adding Cloud Bigtable as our performance database

As we scaled our services and added customers, our data collection services for our Device Intelligence and Behavioral Analytics products were seeing thousands of events per second. Cloud Bigtable provided a stable managed database that could handle the volume we were receiving during peak hours. We weren’t always able to handle this scale, as an early version of our product utilized a self-managed database.

Every month, two or three engineers spent hours managing the database instances. Whenever the instances crashed, it would cost at least one engineer a day or two of productivity attempting to restore the instances and recovering any data from our backup database. Managing this database internally was taking precious time away from product development.

We circled back to Cloud Bigtable. After two weeks of R&D, we decided to switch the Device Intelligence and Behavioral Analytics services to Cloud Bigtable.

Cloud Bigtable solved our scaling issues. Cloud Bigtable had been attractive to us from the start because it was fully managed, and offered regional replication and other features we were lacking in our own managed instances. Cloud Bigtable provides horizontal scaling and automatically rebalances row keys (equivalent to a shard key) over time to prevent “hot” nodes. In addition, Cloud Bigtable provides a connector to BigQuery and Cloud Dataproc that allows us to analyze the terabytes of data we are processing and use that data for unsupervised machine learning.

The perks of using Cloud Bigtable

After the migration to Cloud Bigtable, we noticed a number of additional benefits: improved I/O performance, a significant cost reduction, and a sizable decrease in hours spent on database maintenance.

We measured some of our typical metrics before and after implementing Cloud Bigtable. Our request latency dropped by about 30 ms on average (to sub-10 ms) for API requests. Prior to the change, we were seeing latencies of 40+ ms on average. This latency drop on our Behavioral Analytics and Device Intelligence products allowed us to trim about an additional 10 to 15 ms off our average response time across all dependent services.

Before we moved to Cloud Bigtable, we had to scale our database instances every time a new customer was onboarded. We were over-scaling in an attempt to avoid constantly resizing our database servers. By sunsetting our self-managed database and switching to Cloud Bigtable, we cut database infrastructure costs by approximately 35% and can now scale as needed, with a couple of clicks, during onboarding.

We have spent zero hours managing a Cloud Bigtable database since launch, and we put the time we are saving every month toward product development.

Moving forward with Cloud Bigtable

As an engineering team, we love working with Cloud Bigtable. We are not only seeing improved developer experience and reduced latency, which keeps the engineers happy, but also reduced costs, which keeps the business happy. We’re able to build more product, too, with the time we’ve saved by switching to Cloud Bigtable. Stay tuned to our engineering blog for more on the lessons we’ve learned and our contributions to the wider Cloud Bigtable community.

Where should you run your workload? It depends…Choosing the right infrastructure options to run your application is critical, both for the success of your application and for the team that is managing and developing it. This post breaks down some of the most important factors that you need to consider when deciding where you should run your stuff!

What are these services?

• Compute Engine – Virtual machines. You reserve a configuration of CPU, memory, disk, and GPUs, and decide what OS and additional software to run.
• Kubernetes Engine – Managed Kubernetes clusters. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. You create a cluster and configure which containers to run; Kubernetes keeps them running and manages scaling, updates and connectivity.
• Cloud Run – A fully managed serverless platform that runs individual containers. You give code or a container to Cloud Run, and it hosts and auto scales as needed to respond to web and other events.
• App Engine – A fully managed serverless platform for complete web applications. App Engine handles the networking, application scaling, and database scaling. You write a web application in one of the supported languages, deploy to App Engine, and it handles scaling, updating versions, and so on. 
• Cloud Functions – Event-driven serverless functions. You write individual function code and Cloud Functions calls your function when events happen (for example, HTTP, Pub/Sub, and Cloud Storage changes, among others). 

What level of abstraction do you need?

• If you need more control over the underlying infrastructure (for example, the operating system, disk images, CPU, RAM, and disk) then it makes sense to use Compute Engine. This is a typical path for legacy application migrations and existing systems that require a specific OS. 
• Containers provide a way to virtualize an OS so that multiple workloads can run on a single OS instance. They are fast and lightweight, and they provide portability. If your applications are containerized then you have two  main options. 
  • You can use Google Kubernetes Engine, or GKE, which gives you full control over the container down to the nodes with specific OS, CPU, GPU, disk, memory, and networking. GKE also offers Autopilot, when you need the flexibility and control but have limited ops and engineering support. 
  • If, on the other hand, you are just looking to run your application in containers without having to worry about scaling the infrastructure, then Cloud Run is the best option. You can just write your application code, package it into a container, and deploy it.  
• If you just want to code up your HTTP-based application and leave the scalability and deployment of the app to Google Cloud then App Engine — a serverless, fully-managed option that is designed for hosting and running web applications — is a good option for you. 
• If your code is a function and just performs an action based on an event/trigger, then deploying it with Cloud Functions makes sense. 

What is your use case? 

• Use Compute Engine if you are migrating a legacy application with specific licensing, OS, kernel, or networking requirements. Examples: Windows-based applications, genomics processing, SAP HANA.
• Use GKE if your application needs a specific OS or network protocols beyond HTTP/s. When you use GKE, you are using Kubernetes, which makes it easy to deploy and expand into hybrid and multi-cloud environments. Anthos is a platform specifically designed for hybrid and multi-cloud deployments. It provides single-pane-of-glass visibility across all clusters from infrastructure through to application performance and topology. Example: Microservices-based applications. 
• Use Cloud Run if you just need to deploy a containerized application in a programming language of your choice with HTTP/s and websocket support. Examples: websites, APIs, data processing apps, webhooks.
• Use App Engine if you want to deploy and host a web based application (HTTP/s) in a serverless platform. Examples: web applications, mobile app backends
• Use Cloud Functions if your code is a function and just performs an action based on an event/trigger from Pub/Sub or Cloud Storage. Example: Kick off a video transcoding function as soon as a video is saved in your Cloud Storage bucket.

Need portability with open source? 

If your requirement is based on portability and open-source support take a look at GKE, Cloud Run, and Cloud Functions. They are all based on open-source frameworks that help you avoid vendor lock-in and give you the freedom to expand your infrastructure into hybrid and multi-cloud environments.  GKE clusters are powered by the Kubernetes open-source cluster management system, which provides the mechanisms through which you interact with your cluster. Cloud Run for Anthos is powered by Knative, an open-source project that supports serverless workloads on Kubernetes. Cloud Functions use an open-source FaaS (function as a service) framework to run functions across multiple environments. 

What are your team dynamics like?

If you have a small team of developers and you want their attention focused on the code, then a serverless option such as Cloud Run or App Engine is  a good choice because you won’t have to have a team managing the infrastructure, scale, and operations. If you have bigger teams, along with your own tools and processes, then Compute Engine or GKE makes more sense because it enables you to define your own process for CI/CD, security, scale, and operations. 

What type of billing model do you prefer? 

Compute Engine and GKE billing models are based on resources, which means you pay for the instances you have provisioned, independent of usage. You can also take advantage of sustained and committed use discounts. 

Cloud Run, App Engine, and Cloud Functions are billed per request, which means you pay as you go. 

Conclusion

It’s important to consider all the relevant factors that play a role in picking appropriate compute options for your application. Remember that no decision is necessarily final; you can always move from one option to another.

To explore these points in more detail, please take a look at the “Where Should I Run My Stuff?” video.

For more #GCPSketchnote, follow the GitHub repo &  thecloudgirl.dev. For similar cloud content follow us on Twitter at @pvergadia and @briandorsey

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.”