Working to put food on all of our tables, today’s farmers are facing a higher amount of instability from input supply chain issues to weather patterns. Adding to this challenge are problems farmers face when trying to correctly time grain purchases, sales and transport. Farmers have always been stewards of the land, but now the demand for sustainable products has them needing to better prove their regenerative practices.

At Bushel, we understand these problems can’t be solved overnight or by a single company. We focus on empowering agribusinesses and farmers to work even more closely together to build a more sustainable agricultural supply chain by rapidly responding to market changes. With Bushel, farmers can track market prices in real time, instantly buy and sell grain, analyze inventory and transactions, and securely share verified information with grain operators and other producers. We provide the digital tools to streamline how farmers buy and sell commodities throughout the agricultural industry’s supply chain to help address market inefficiencies that can lead to waste, and have the information and resources to help them flex and adapt as complexity increases in farming operations.

Approximately 40% to 50% of all U.S. grain transactions now pass through the Bushel platform. As we continue to grow, Bushel continues to focus on what digital tEmpowering Farmers: Bushel Drives 40-50% of US Grain Transactions, Fueling Sustainable Agricultureools can support each point in the supply chain. Many focus on the first mile at the farm or last mile at the store. But Bushel is focused on modernizing the middle where grain purchasing and processing sit. We aim to help local grain industries and stabilize regional agricultural supply chains.

Starting with a simple mobile app; now scaling into an agricultural ecosystem

Bushel began its journey in 2017 as a small-scale platform for farmers that delivered grain contracts, cash bids, and receipts. As Bushel evolved into a comprehensive agricultural ecosystem, we realized we needed knowledgeable technology partners to help us rapidly scale while saving time and administrative costs. That’s why we started partnering with the Google for Startups Cloud Program to get support from Google and work with Google Cloud Managed Services partner, DoiT International to help support our use of GKE and create a multi-regional deployment as well as migrate our CUDs to new Compute Engine families and continue to optimize our footprint. We’ll also use DoiT’s Flexsave technology to reduce the management overhead of CUDs in the future.

In just one year, we expanded to over 1,200 live grain receiving locations and quickly grew our services portfolio with electronic signature capabilities, commodity balances, and web development. Because that relationship between farmer and agribusiness is so important, we provide more than 200 grain companies with white-labled digital experiences so each farmer sees their local grain facility they do business with on both desktop and mobile. To further our extension into the digital infrastructure of agriculture, we subsequently acquired GrainBridge and FarmLogs to help farmers handle specific jobs and tasks, and provide the needed insights to improve their business operations. Over 2,000 grain receiving locations across the United States and Canada now use Bushel products. We accomplished all this on Google Cloud.

We leverage the secure-by-design infrastructure to protect millions of financial transactions and keep sensitive customer data safe. Our data is processed and stored in Google’s secure data centers, which maintain adherence to a number of compliance frameworks. We utilize Google Kubernetes Engine extensively as it reduces operational overhead and offers auto scaling up to 15,000 nodes.

Database provisioning, storage capacity management, and other time-consuming tasks are automated with our Cloud SQL usage. Query Insights for Cloud SQL streamlines database observability and seamlessly integrates with existing apps and Google Cloud services such as GKE and BigQuery.

Empowering farmers and agribusinesses in North America

The Google Cloud Account Team had been instrumental in helping Bushel build an expansive agricultural platform that powers APIs, apps, websites, and digital solutions. Google’s startup experts are incredibly responsive, with deep technical knowledge that can’t be found elsewhere. Google Cloud also has provided us credits to explore new ways of analyzing the vast amounts of data we generate, verify, and transfer with solutions such as BigQuery and Pub/Sub.

With BigQuery, we can run analytics at scale with 26%–34% lower three-year TCO than cloud data warehouse alternatives. BigQuery delivers actionable insights on a highly secure and scalable platform, includes built-in machine learning capabilities, and integrates with Pub/Sub to ingest and stream analytic events via Dataflow.

With Bushel, farmers across North America are rapidly responding to sudden market changes by tracking grain prices in real time and instantly buying and selling crops. We see a future where this business information becomes insights – where a farmer can not just know where to sell their grain, but when to sell. The burden right now to engage with carbon markets is high, full of paper-based binders and verification forms. We see a world where farming practices recorded digitally can be permissioned along the supply chain for a better picture of how our food is grown.

With the Bushel platform, millions of farmers around the world will have the digital tools to modernize local grain industries, build more sustainable agricultural supply chains, and help to address global food inequity.

If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.

The last few years have underscored the importance of speed in bringing new drugs and medical devices to market, while ensuring safety and efficacy. Over this time, healthcare and life sciences organizations have transformed the way they research, develop, and deliver patient care by embracing agility and innovation.

Now, the industry is set to reap the benefits of cloud technology and overcome the existing barriers to innovation.

What’s holding back innovation?

Costly clinical trials: The process of trialing and developing new drugs and devices is still long and costly, with more than 1 in 5 clinical trials failing due to a lack of funding.1 The high failure rate comes as no surprise when you consider the average clinical trial costs $19 million and takes 10-15 years (through all 3 phases) to be approved.2

Stringent security requirements: Pre-clinical R&D and clinical trials use large volumes of highly sensitive patient data – making the life sciences industry one of the top sectors targeted by hackers.3 On top of this, the FDA and other regulatory bodies have strict requirements for medical device cybersecurity.

Unpredictable supply chains: Global supply chains are becoming increasingly complex and unpredictable. This can be brought on by anything from supply shortages, to geo-political events, and even bad weather. Making things worse is the lack of visibility into medical shipment disruptions – so when disaster strikes you’re often caught off guard.

Google Cloud for life sciences

At Alphabet, we’ve made significant investments in healthcare and life sciences, helping to tackle the world’s biggest healthcare problems, from chronic disease management, to precision medicine, to protein folding.

Together with Google, you can transform your life sciences organization and deliver secure, data-driven innovation across the value chain.

• Accelerate clinical trials to deliver life-saving treatments faster and at less cost. Clinical trials require relevant and equitable patient cohorts that can produce clinically valid data. Solutions like DocAI can enable optimal patient matching for clinical trials, helping organizations optimize clinical trial selection and increase time to value. How that patient data is collected is also important. Collection in a physician’s office captures a snapshot of the participant’s data at one point in time and doesn’t necessarily account for daily lifestyle variables. Fitbit, used in more than 1,500 published studies–more than any other wearable device–can enrich clinical trial endpoints with new insights from longitudinal lifestyle data, which can help improve patient retention and compliance with study protocols. We have introduced Device Connect for Fitbit, which empowers healthcare and life sciences enterprises with accelerated analytics and insights to help people live healthier lives. We are able to empower organizations to improve clinical trials in key ways:

1. Enable clinical trial managers to quickly create and launch mobile and web RWE collection mechanism for patient reported outcomes
2. Enable privacy controls with Cloud Healthcare Consent API and, as needed, remove PHI using Cloud Healthcare De-identification API
3. Ingest RWE and data into BigQuery for analysis
4. Leverage Looker to enable quick visualization and powerful analysis of a study’s progress and results

• Ensure security and privacy for a safe, coordinated, and compliant approach to digital transformation. Google Cloud offers customers a comprehensive set of services including pioneering capabilities such as BeyondCorp Enterprise for Zero Trust and VirusTotal for malicious content and software vulnerabilities; Chronicle’s security analytics and automation coupled with services such as Security Command Center to help organizations detect and protect themselves from cyber threats; as well as expertise from Google Cloud’s Cybersecurity Action Team. Google Cloud also recently acquired Mandiant, a leader in dynamic cyber defense, threat intelligence and incident response services.

• Optimize supply chains and enhance your data to prepare for the unpredictable. With a digital supply chain platform, we can empower supply chain professionals to solve problems in real time including visibility and advanced analytics, alert-based event management, collaboration between teams and partners, and AI-driven optimization and simulation.

Ready to learn more? We’ll be taking a deep dive into each of the challenges outlined above in our life sciences video series. Stay tuned.

1. National Library of Medicine
2. How much does a clinical trial cost?
3. Life Sciences Industry Becomes Latest Arena in Hackers’ Digital Warfare

As a leading French agricultural cooperative, Groupe Dauphinoise places collaboration at the heart of its philosophy. Working with farmers in the Rhone-Alpes region, Groupe Dauphinoise takes on a diverse range of activities from agricultural production to research and development to running retail outlets.

As its operations expanded and strained its existing infrastructure, Groupe Dauphinoise saw the opportunity to upgrade its technology solutions and adopted G Suite, Chrome devices and ultimately Google Cloud Platform (GCP).

“We transitioned to G Suite to improve our staff’s collaboration. We quickly realized that as the company grew, we needed a new infrastructure. Based on our satisfaction with G Suite, we chose GCP. With Google, ‘any device, anytime, anywhere’ is not just a dream,” says Sylvain Claudel, Head of IT at Groupe Dauphinoise.

“We transitioned to G Suite to improve our staff’s collaboration. We quickly realized that as the company grew, we needed a new infrastructure. Based on our satisfaction with G Suite, we chose GCP. With Google, ‘any device, anytime, anywhere’ is not just a dream.”

—Sylvain Claudel, Head of IT, Groupe Dauphinoise

Flexible workforce, stable infrastructure

Many of Groupe Dauphinoise’s 1,500 employees spend their days out of the office. Five years ago, with the help of Google partner GoWizYou, the company transitioned to G Suite to improve the flexibility and collaboration of its staff.

As Groupe Dauphinoise began to expand and collect more data, the company reached the limits of its on-premise infrastructure. Adding new storage was not a simple matter. Acquiring, configuring and synchronising new servers costs Groupe Dauphinoise time as well as money. In addition, with all its servers stored in a single room, security was a concern. Groupe Dauphinoise needed a new infrastructure.

Google Cloud Platform was the only solution in mind after Groupe Dauphinoise’s experience with G Suite and Chromebooks. Disruption was kept to a minimum thanks to Google’s licensing agreements with Microsoft products, allowing the company to migrate without affecting its operations.

After migrating its infrastructure to Compute Engine, Groupe Dauphinoise can let Google look after the security and maintenance. Cloud IAM makes it easy for Groupe Dauphinoise to hand out permissions to sensitive resources across a number of sites with maximum security and minimum fuss. The company placed its archives in Cloud Storage, while Cloud SQL allows it to continue to make use of its MySQL databases without disrupting the day to day business. Meanwhile, BigQuery provides Groupe Dauphinoise with the raw power to analyse large datasets quickly.

“Our company is growing and we have more and more data to collect and analyze like sales data, weather patterns or production numbers. With GCP, we have more than a single on-premise data store, so our disaster recovery plan is much more flexible. Compute Engine allows us to add more storage quickly and easily, without having to spend days synchronizing data and installing new servers. We have improved security and maintained the stability of our infrastructure while keeping costs down,” says Sylvain.

Safeguarding the present, looking to the future

With Google Cloud Platform, Groupe Dauphinoise has expanded and secured its infrastructure without sinking costs into on-premise servers or DevOps staff. Its investment in Chrome devices and adoption of G Suite mean that its mobile workforce can fully reap the benefits of a cloud-based infrastructure while dramatically cutting the cost of hardware. Meanwhile, working with a 200 million line table of sales data in Google BigQuery, the cooperative found that queries ran ten times faster than with its previous database provider. Groupe Dauphinoise is experimenting with Google BigQuery to expand its BI capabilities. Products like Google BigQuery help Groupe Dauphinoise grow its business, safe in the knowledge that its infrastructure is stable and secure.

“The amount of data we collect is growing very quickly. We need to break our rules and evolve from the mindset that we had with on-premise infrastructure and our old databases. We can now look at collecting more customer fidelity data, or big data for our farmers. With our data and infrastructure in Google’s care, we can concentrate on growing our customer base instead of our IT department!” says Sylvain.

VMs and their relevance to a cloud-native future: A conversation

Last week, we published the first episode of VM End-to-End, a series of curated conversations between a “VM skeptic” and a “VM enthusiast”. Join Brian and Carter as they explore why VMs are some of Google’s most trusted and reliable offerings, and how VMs benefit companies operating at scale in the cloud. Here’s a transcript of the first episode:

Carter Morgan (VM skeptic): My team asked me to research VMs and see how they compare to other cloud-native approaches, like microservices, containers, and serverless. And to be honest with you, I am not excited about it at all. So I’ve brought in someone who is, Brian, resident VM expert. Welcome, Brian!

Brian Dorsey (VM enthusiast): Hello. I’m super happy to be here, because I am really excited about VMs.

Carter: How? See this is why I wanted to bring you here. I don’t understand how you can be so excited about VMs, already?

Brian: How can you not? It is like the best of both worlds. You’ve got a stable, reliable system you can run anything on, and you’re in the cloud, close to all of the new features, and you get new automation tooling.

Carter: See, that’s what I’m kind of skeptical about. When I think about the features of a modern system, I’m not sure that a VM can provide me with those.

Brian: Okay. Well, let’s be kind of specific there. What do you mean by a modern system?

Carter: When I think about a modern system, I think about things like modularity. I think about scalability and reliability. I want automation. I don’t want to have to do everything manually. I even think about portability and being able to move my workloads wherever they need to go. I also don’t want to implement everything by hand. I don’t want to have to do everything myself. Is that something I can get with a VM?

Brian: Yeah. Great, because I actually think we can get most of that, and I wonder, why not? Let’s go one level deeper and then we’ll come back out. In your mind, what is a VM?

Carter: Oh, you’re putting me on the spot, Brian?!

Brian: Yep.

Carter: Okay. A VM, it’s a computer, but it’s a virtualization. It’s a slice of a computer. And so, what it lets you do is it lets you run multiple operating systems on one machine, so it looks like you have multiple machines running on one physical machine.

Brian: Yep. Absolutely. And in the cloud kind of not.

Carter: Oh, what?

Brian: Yeah. So here’s why I say not. The obstructions are all there, so you’ve got memory CPU, disk, networking. And instead of from one computer, in the cloud, that’s coming from all of the computers in a data center. So the CPU is coming from a lot of machines. The networking is from the whole data center. And so, I like to think about it as instead of a slice of a computer, it’s a slice of the data center

Carter: Instead of a slice of a computer, it’s a slice of a data center. That sounds interesting. Impressive, even. But also abstract. Do you have some examples of features that you can get from a cloud VM that you can’t get from a traditional VM on one machine?

Brian: My turn to be specific. Yeah. I think one example is like bin packing. You talk about these VMs, and their different shapes. So you have one that needs a lot of CPU and another that needs a lot of memory. Maybe you’ve got a bunch of them that need a lot of CPU and they don’t fit so well in the same box without orphaning some of the memory or CPU. And if you’re running those in a whole data center, or you can basically just leave it to Google to solve that problem, you can just have whatever shape machine you want and we’ll figure out where to put it. Basically, that lets you customize your machines to exactly what you need.

Carter: Okay. That’s very interesting, because that’s a hard problem. And so, if you can just let Google handle where your workloads are going to go, that’s a good benefit. If that’s the only benefit of cloud VMs though, I’m not sure I’m sold on them over other approaches. Is there anything else we got?

Brian: Absolutely. There’s a ton of stuff we could talk about in terms of automation and other things. But I think another really concrete example is disks, and it’s kind of my favorite there, because you think about a physical disk and you read and write blocks from it, right? It’s a block device. In the data center level, those blocks could be on hundreds or thousands of different machines, and so all of them are working together to give you more reliability and make things smoother, more predictable in terms of performance. So what you get out of it is something that looks a lot like a SAN, you can take backups of disks that are running even, or if you’ve run out of space, like I think almost all of us have, you can just make the disk bigger. So, things like that.

Carter: That’s impressive, especially like you’re saying being able to run and just scale up, scale down or resize. Okay. Then another very targeted question. It’s going to sound like a dig. I don’t mean it to you. Google’s putting a lot of effort and resources into Google Kubernetes Engine (GKE). And so, is Google even still investing in VMs?

Brian: Absolutely. Where do you think these containers run? Every Kubernetes cluster is running on top of a whole bunch of VMs. And so, everything you learned about VMs applies to those clusters that you’re running. Also, another example is our managed databases, so Cloud SQL. So if you’re running Postgres or MySQL on a Cloud SQL, that’s running on VMs. And there’s a bunch of other examples, too.

Carter: I can’t get away from VMs, even if I tried, it sounds like.

Brian: Nope.

Carter: Okay. The way you’re saying that is making me think that maybe I need to rethink my idea that VMs are just old, dusty pieces of technology. So I want to be clear, definitively, are you saying that VMs have a place in a cloud-native future?

Brian: Absolutely. I want to take old and dusty and turn that into mature and reliable. Then the future part, all these things are built on top of it and we’re building new things over time. So we’ve got tools for scaling clusters of machines up and down. That’s using Kubernetes, but you can use it directly. And we keep investing and doing more and more things there. So, absolutely, part of the future as well.

Carter: Okay. Then what about if I wanted to switch to them? I’m pretty familiar with Kubernetes. It’s fairly easy to get started. What about with VM? Is it going to take me years to get started on these?

Brian: No. It’s just a computer. Basically, anything that’s already running on a computer somewhere, even if you don’t have the team who built it nearby, you can run that on a VM and in turn you can run it on a cloud VM and get a bunch of the cloud benefits as well.

Carter: All right. I must admit that you’ve swayed me a little bit. I’m still skeptical, but what you said made a lot of sense. I still have a lot of questions. I want to know about keeping costs down. I want to know how to update VMs. I have this idea in my head that they’re really slow to start and stop. Stateful data, I’m curious about that.

Brian: Awesome. How much time do you have?

Carter: All right. You know what, let’s have this convo another day, and maybe, just maybe we can agree that VMs do matter in a cloud-native future.