Being Cloud-native Means Sustainability and Growth-native for Nuuly!
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They say black never goes out of style. It’s something the team at Nuuly, URBN’s digital rental and resale business, know well. And it’s not just true of the company’s garments but their gadgets, too.
“I was having an offhand conversation with a UX designer recently,” Rebecca Sandercock, Nuuly’s strategy and insights manager, recalled in a recent interview from the company’s sunny, South Philly headquarters. “The designer was talking about how we had chosen dark mode for a number of interfaces internally because it actually saves so much on electrical output. They had the data to back that decision up, but more importantly, it’s just the kind of thing everyone is thinking about all the time here.”
Of course most every business is thinking about sustainability in some way these days. What makes Nuuly stand out is how quickly it can act, thanks in large part to the technology platform that’s made the entire enterprise possible.
“We’re kind of sustainable by our very nature,” Kim Gallagher, Nuuly’s director of marketing and customer success, said.
While she meant the rental and resale business, which helps customers buy fewer clothes and sees Nuuly items worn many times by many people—Gallagher could just as well have been referring to the sustainability inherent in, and enabled by, cloud computing.
There are the obvious, and oft-cited, advantages, such as how centralized data centers can operate more efficiently (some have been carbon neutral since the beginning). Yet there are even more subtle yet substantial benefits. In a marketplace and climate that are both changing faster and faster, sustainability requires a certain amount of agility. Such adaptability and scalability are intrinsic to the cloud technology that threads its way throughout Nuuly.
It turns out that being cloud native also means being sustainability native—as well as growth native. Since its 2019 launch, Nuuly’s net sales have risen roughly 6x over the first three fiscal years.
Cloud fits any situation
When URBN was developing Nuuly—launching in just 10 months—it chose to create everything from scratch on Google Cloud. Despite being part of a larger organization with decades of history and expertise, the company recognized the limitations presented by legacy systems and, more importantly, the necessity of building a wholly new platform that could be fully responsive.
The company has to react not only to new fashion trends but, crucially, the changing behaviors of customers. And not just their evolving tastes but also shopping habits, delivery preferences, unexpected customer service requests—is this a pattern, or a stain?—and social media chatter.
The pressure for a successful launch was high. The URBN portfolio, which also includes Urban Outfitters, Anthropologie, and Free People, had to keep evolving to satisfy a new generation of shopper who exists in an increasingly crowded and demanding digital marketplace.
The cloud’s responsiveness has thus proven its worth in creating a financially sustainable business as well as an environmentally sustainable one. Those even go hand in hand, as Gallagher points out: “Every customer who keeps renting is one who isn’t buying more occasion-specific clothes that go unworn most of the time.”
Dr. Alan Rosenwinkel, director of data science at URBN, had heard from his team about one garment that has become an emblem for the power of the platform. “It had been rented 25 different times before someone loved it enough to buy it and keep it forever,” he explained. (It’s also an emblem of the power of the cloud, that they would have the data awareness to track a single item so closely.)
It’s a new way of shopping made possible by a new way of computing. As one writer for Business Insider cheered, Nuuly “completely cured my addiction to fast-fashion.”
It makes for a healthy business, too. Sales for fiscal year 2019 exceeded $8 million and surpassed $24 million in 2020—one of the few URBN segments to grow during a tough year for fashion—and reached $47 million in 2021. The subscriber base had grown to 51,000 at the end of January.
Agility drives sustainability drives agility
For digital retailers to achieve such customer enthusiasm often relies as much on how the clothes get there as how they look. And those deliveries turn out to be a prime example of where Nuuly’s sustainability and technology meet.
For now, all shipping is handled through a state-of-the-art distribution center in Bucks County on the Philadelphia outskirts. Garments are shipped six-at-a-time, in fully reusable packaging, using ground transportation to keep the carbon footprint to a minimum. In certain limited geographic areas, shipments were sometimes taking longer than the two to five days most members would find acceptable.
“If we were an older company or weren’t set up from a technology perspective to be agile, we might have just said, ‘All right, we’re going to just go to three-day shipping for everyone,’” Rosenwinkel said. “That would drive up the cost, and the environmental impact. But we were able to be more strategic and more targeted about it.”
By regularly analyzing customer sentiment and retention data through BigQuery and Cloud Composer, and tying those to historical shipping times, Nuuly has been able to understand how shipping speed impacts its customers. Using a custom-built order management system, deliveries can be automatically adjusted to arrive more quickly, particularly when certain regions or days of the week are proving difficult to reach customers in time. These accelerated deliveries, like all Nuuly shipments, are made via UPS’s Carbon Offset program.
“Because we have the data, and the platforms to analyze it all,” Rosenwinkel said, “we’re delivering faster with the bare minimum impact on cost and emissions.”
It’s just one example of how modern retailers must juggle so many demands from consumers, workers, suppliers, and even regulators. Adding sustainability to that mix could be seen as a burden, but Nuuly shows how the right technology can lead to a holistic approach that makes all those interests work together even better.
And it allows for more opportunities and more kinds of sustainability, reaching from the designer’s atelier to the customer’s doorstep.
Sustainable details at every level
Back at the distribution center, workers can experience sustainability in a different way, as data is leveraged to enhance their well-being.
All workers are equipped with customized Android devices that help guide order tracking and fulfillment, plus cleaning, repairs, and reselling of garments as needs change throughout their lifecycle. Yet the insights go even deeper. The data science team has closely analyzed routes and repetitive motions for workers to keep their strenuous jobs as low-impact as the company’s broader environmental footprint.
“Through machine learning, we estimate we’ll be able to save our workers over 300,000 miles of steps over a five year period,” Rosenwinkel said. That’s enough walking to circumnavigate the globe 12.5 times.
The company has also applied ingenuity to one of the most notorious aspects of digital retail: packaging. Made from 100% post-consumer recycled materials like plastic bottles, Nuuly’s reusable carriers require no disposable bags or hangers to send goods back and forth. And once the packages have reached their end of life, the team is working with designers on ways to repurpose them into items that can then be offered for rental or sale on Nuuly.
“We’re really looking at the circular economy from every angle,” Gallagher said. “It’s built into the business.”
That includes not just the research the team did on-site at the Dry Cleaning & Laundry Institute—”We went to laundry school,” Gallagher jokes—but the digital tools that take those lessons even further. The team is always looking for ways to optimize fabric care, both to cut down on chemicals and water usage and extend the life of a garment. By analyzing the lifespan of every item, Nuuly not only makes them last longer but can identify problems faster. Employees even use custom apps to mark stains and damage so repair teams can more easily identify and fix the issues.
With its meticulous inventory tracking, Nuuly can even take marginal items, like a white gown or jeans with a small stain, and turn them into a custom dye job or an upcycling opportunity with a partner. These reworked items are then inserted back into the Nuuly Rent inventory as part of a growing collection of one-of-a-kind pieces, called Re_Nuuly.
Other services have launched quickly and easily thanks to the company’s cloud-enabled backend. Wanting to encourage more community and more reuse, the company created Nuuly Thrift. Debuting last fall after just a year in development, the team built everything from new interfaces to an evolved point of sale system.
It’s enabled Nuuly to offer many garments for rent or sale simultaneously, with “truly real-time inventories,” Rosenwinkel said. “So when it’s gone on one site, it shows up as gone on every site—no more surprises.”
Except for the good kind.
“I like to think we’re helping our customers think about ownership in a completely new way,” Sandercock said. “Once they run out of a use for a garment, they can offer it back, and sell it, and someone else will get to enjoy it and give it a new life. And Nuuly, we get to keep it in the community and keep it in the ecosystem, which is really cool—we’re taking extended responsibility over what happens to the clothing we create.”
Speed Up Data-driven Innovation in Life Sciences with Google Cloud
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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:
- Enable clinical trial managers to quickly create and launch mobile and web RWE collection mechanism for patient reported outcomes
- Enable privacy controls with Cloud Healthcare Consent API and, as needed, remove PHI using Cloud Healthcare De-identification API
- Ingest RWE and data into BigQuery for analysis
- 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.
- National Library of Medicine
- How much does a clinical trial cost?
- Life Sciences Industry Becomes Latest Arena in Hackers’ Digital Warfare
New Enterprise Capabilities and Changes to Cloud Spanner Reduces Cost of Running Workloads by 90 Percent
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Customers love Cloud Spanner because it gives them the benefits of relational semantics and SQL while also delivering the scale and availability of non-relational databases. Many of these customers want to move even more of their work to Spanner, and have requested smaller instance sizes to support development, testing and small production workloads. We’re happy to announce that they’ll soon get what they asked for: more granular instance sizing is coming to Spanner.
Granular instance sizing will be available in Public Preview soon. With this feature, you can run workloads on Spanner at as low as 1/10th the cost of regular instances, equating to approximately $65/month.
In addition, we are launching new enterprise capabilities to break down operational silos for real-time insights and provide greater database observability to developers:
- Datastream, now in public preview, is a change data capture (CDC) service that allows enterprises to synchronize data across heterogeneous databases and applications. With Spanner support in Datastream, users will be able to stream data from MySQL or Oracle to Spanner reliably and with minimal latency.
- BigQuery federation to Spanner (coming soon) lets users query transactional data residing in Spanner, from BigQuery, without moving or copying data.
- Key Visualizer, available now in public preview, provides interactive monitoring so developers can quickly identify trends and usage patterns in Spanner.
Democratizing access with more granular instance sizing
Today, customers provision Spanner instances by specifying the number of nodes they need to run their workloads. Each node can provide up to 10,000 queries per second (QPS) of reads or 2,000 QPS of writes (writing single rows at 1 KB of data per row) and 2 TB of storage. A Spanner node is replicated across 3 zones for regional instances, and 5 or more zones for multi-regional instances. The choice of node count determines the amount of serving and storage resources that are available to the databases in a given instance.
Historically, the most granular unit for provisioning resources on Spanner has been one node. To enable more granular control, we are introducing Processing Units (PUs); one Spanner node is equal to 1,000 PUs. Customers can now provision in batches of 100 PUs, and get a proportionate amount of compute and storage resources. This will allow teams to run smaller workloads on Spanner at much lower cost. With this feature, customers can start at 100 PUs and scale up as needed in batches of 100 PUs, to up to 1,000 PUs (1 node), all with zero downtime. Subsequently, customers can continue to scale up by adding more nodes, just like what they do today. Customers do have the choice of using either PUs or nodes to provision resources within workloads, when those workloads occupy multiple nodes of capacity.
To illustrate with an example, let’s say a game developer creates a Spanner instance called “baseball-game” in us-central1, with 100 PU compute capacity at $65/month price.
As you can see below, proportional maximum storage of 205 GB is assigned to the 100 PU instance.
Once the game starts becoming popular and resource demands increase, the user edits the instance to increase the compute capacity to 500 PUs with proportional maximum 1 TB of storage.
The game grows in popularity, and the gaming company prepares to launch a much-awaited capability in the game. Anticipating a sharp increase in usage at launch day, the game developers increase the compute capacity to 3,000 PUs. Compute capacity assigned to the instance over a period of time can be viewed in Cloud Monitoring graphs:
Request Access
You can request early access to granular instance sizing feature by filling this form.
Breaking down operational silos with Datastream CDC and BigQuery federation
BigQuery Federation. BigQuery has made analytics easy by bringing together data from multiple sources for seamless analysis. Soon you’ll also be able to analyze data in Spanner directly in BigQuery. With Spanner’s BigQuery federation, you’ll be able to instantly query data residing in Spanner in real-time without moving or copying the data. Simply set up the Spanner as an external data source in BigQuery, as shown below.
Change Data Capture ingest. Now in public preview, Datastream lets you stream change data into Google Cloud from MySQL and Oracle databases. As of today, you can ingest this change data directly into Spanner using a built-in Dataflow template. This lets you migrate data from MySQL and Oracle databases into Spanner in near-real time.
Understanding performance and resource usage with Key Visualizer
Key Visualizer is a new interactive monitoring tool that lets developers and administrators analyze usage patterns in Spanner. It reveals trends and outliers in key performance and resource metrics for databases of any size, helping to optimize queries and reduce infrastructure costs. Designed for performance tuning and instance sizing, Key Visualizer is available today in public preview in the web-based Cloud Console for all Spanner databases at no additional cost. Learn more in the Key Visualizer blog.
Learn more
- To request early access to granular instance sizing in Spanner, fill out this form.
- To get started with Spanner today, create an instance or try it out with a Spanner Qwiklab.
How Google Cloud Helps SAP Admins Create Scalable, Secure Networks
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SAP forms the critical backbone of thousands of enterprises, supporting critical business functions such as finance, supply chain, warehouse management, and more. Google Cloud provides a highly scalable and resilient infrastructure to run such workloads and offers tools, such as Smart Analytics and Machine Learning that can accelerate your organization’s digital transformation.
In fact, a recent study by Forrester found that running SAP on Google Cloud can generate a 160% return on investment and a payback period of six months or less, thanks to legacy infrastructure cost savings, downtime avoidance, and productivity improvements.
How you deploy your SAP systems across your network has a tremendous impact on its availability, resilience, and performance. In addition to separate production and high-availability (HA) environments, SAP deployments typically include sandbox, development, quality assurance (QA), and disaster recovery environments as well.
Because most of the Google network is virtual, SAP administrators can easily design complex landscapes that suit your organization’s SAP deployment and organizational structure while also meeting security and operational requirements.
As you get started with SAP on Google Cloud, you’ll need to decide how to configure your networking to ensure the availability and performance of various SAP systems. Here’s a look at your options.
VPC and shared VPC
A virtual private cloud (VPC) is a secure, isolated private network hosted within Google Cloud. VPCs are global in Google Cloud, so a single VPC can span multiple regions without communicating across the public internet. Similarly, subnets can span across zones within a region. A zone represents a single failure domain, so typical SAP deployments place production and HA systems in different zones to ensure resiliency. Google Cloud simplifies this type of deployment, because subnets containing both production and HA systems can span multiple zones.
This capability also simplifies SAP clustering, since the cluster’s virtual IP (VIP) address can be in the same range as those of the production and HA machines. This configuration shields the floating IP using Google internal load balancers and is applicable to HA clustering of the application layer (ASCS and ERS) and the HANA database layer (HANA Primary and Secondary).
Shared VPCs are a feature unique to Google Cloud that allows an organization to connect resources from multiple projects to a common VPC network. This lets them communicate with each other securely and efficiently using internal IPs. You can also centrally control the network for all SAP projects (service) from the Host project while using firewalls to inspect communication between compute engines in the same subnet, and between those in different subnets. (Best practice is to limit the communication between these systems to only the required ports — typically via SAP remote function call (RFC) communication at Layer 4.)
When designing your network, start with a host project containing one or more Shared VPC networks. You can attach additional service projects to a host project, which allows them to participate in the Shared VPC. It’s common practice to have multiple service projects operated and administered by various departments or teams in your organization.
Depending on your needs, you can deploy SAP on a single Shared VPC or multiple ones. The two scenarios differ in terms of network control, SAP environment isolation, and network inspection. Let’s look more closely at these differences.
Scenario 1: Deploying SAP on a single Shared VPC
If you require only a single network inspection, deploying SAP on a single Shared VPC has the advantage of simplicity and reduces administrative overhead.
- Network control: The Shared VPC serves as the network hub, allowing central network management based on identity access management (IAM) roles for the network team(s) in both production and non-production environments.
- SAP environment isolation: You can create projects and subnets for each SAP environment. Projects help group resources together for finer IAM control and billing visibility, while subnets provide network isolation for individual SAP environments. In service projects, compute engines can communicate by default; however, you can adopt simple firewall rules to block communication between compute engines within a subnet or in separate subnets.
- Network inspection: Use Google Cloud firewalls to allow only the required ports for communication between SAP systems. Leverage network tags and service accounts to define granular control for both north-south and east-west traffic.
Scenario 2: Multiple Shared VPCs for SAP deployment
In scenarios requiring additional network inspections, you can create multiple Shared VPCs, typically one per environment. Use peering between these Shared VPCs to enable RFC communication among the SAP development, QA, and production systems.
- Network isolation: Multiple Shared VPCs are completely isolated from each other except via specific ports opened in Google Cloud firewalls. This allows additional East-West traffic inspection by a Network Virtual Appliance (NVA) within a Google Cloud network.
- Network control:As the number of Shared VPCs increases, activities such as peering and firewall policies also increase. This diminishes the central network control that Shared VPCs offer, so the network team should plan to manage the policies in each VPC separately.
Hybrid scenarios – for example, one Shared VPC for the production environment and one Shared VPC for all non-production systems — are also possible. This arrangement allows network inspection between production and non-production systems, and limits the number of central network administration layers to two.
Configuring the networking environment for multiple SAP systems can be a complex process. Thanks to Google Cloud’s Shared Virtual Clouds and other tools, SAP administrators can create scalable, secure networks that provide logic, resilience, and visibility to their cloud deployments.Learn more about these networking capabilities and our full offerings for SAP customers.
Google Cloud Platform Gives Us 5x the Processing Power to Analyze Physician Performance at 75% Lower Cost
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Patients about to undergo a healthcare procedure understandably want the best medical professionals they can get. But how can they know which doctors have had the most experience and the best outcomes with that particular procedure? How can they make an informed decision about which doctor to select when the information they have is limited to the doctor’s practice area and subjective reviews from other patients?
MD Insider is working to solve that problem using machine learning (ML) to objectively analyze doctor performance. By analyzing data from thousands of institutions and millions of doctor-patient interactions and medical events, MD Insider identifies physician performance insights based on their experience and outcomes. Insights are then integrated into a triage engine, that enables consumers to search for and schedule appointments with providers who meet their clinical criteria and convenience preferences, such as insurances accepted, office hours, locations, and language.
MD Insider also offers robust data APIs to help health systems, health plans, and employers reduce costs and improve quality of care. Payers use the APIs to curate high-quality provider networks and manage provider directories. Examples of MD Insider’s data APIs include Provider Experience and Share of Practice metrics, Provider Quality and Outcomes, Network Modeling, Expert Clinical Search Taxonomy, Find a Provider, Acute-Care Hospital Quality, and Provider and Facility Metadata.
“We use Google Cloud Platform the way the cloud was supposed to be used. By comparison, other cloud providers feel like you’re renting somebody else’s data center.”
—Ed Holsinger, Lead Data Engineer and Head of Data Science, MD Insider
MD Insider is continuously ingesting the latest performance data about physicians and analyzing billions of rows of data. Requiring constant scalability, the company was born in the cloud; however, it had difficulty configuring server instances for the optimal balance of memory and CPU, and its Hadoop cluster had to be kept running 24/7. Network performance was often slow for no apparent reason. As a result, failure rates from node timeouts increased, and costs grew along with the data. MD Insider had to estimate its usage and pay up front, and received little financial benefit from sustained use commitments.
Knowing that data would continue to grow, MD Insider decided to move its data services — the most demanding and complex portion of its infrastructure — to Google Cloud Platform (GCP), and took advantage of GCP managed services for container management and big data analytics.
“One of the reasons we decided to move to Google Cloud Platform is because it feels like a unified, well-designed cloud architecture and pricing model,” says Ed Holsinger, Lead Data Engineer and Head of Data Science at MD Insider. “We use Google Cloud Platform the way the cloud was supposed to be used. By comparison, other cloud providers feel like you’re renting somebody else’s data center.”
“Moving to Google Cloud Platform and using Kubernetes Engine gave us 5x the processing power for analyzing physician performance at 75% less cost. Our data scientists have more power than ever before to generate insights for our customers.”
—Ed Holsinger, Lead Data Engineer and Head of Data Science, MD Insider
5x the performance, 75% less cost
MD Insider now uses Kubernetes Engine to automate container management and deploy clusters in minutes with just a few clicks. When hundreds of machines are required to analyze a large dataset, automation in Kubernetes Engine deploys ML models as containers, each of which manages the full lifecycle of its task, including scaling up resources, deploying results, and scaling back down when the task is finished. It’s easy for MD Insider to specify exactly how much CPU and memory each container needs, helping maximize performance while reducing costs.
“Moving to Google Cloud Platform and Kubernetes Engine gave us 5x the processing power for analyzing physician performance at 75% less cost,” says Ed. “Our data scientists have more power than ever before to generate insights for our customers. Data scoring jobs that used to take three business days now take four hours.”
Adds Galen Meurer, Senior Software Engineer at MD Insider: “Even if all Google Cloud Platform had to offer was Kubernetes Engine, I would still want to use it. Previously we spent up to 30% of our time managing our container infrastructure, which we can now use for product development.”
A foundation for data science
MD Insider was happy to find that GCP offers a wide variety of managed services. For example, the company is supplementing its Kubernetes Engine clusters with BigQuery for its big data masters and selection jobs, enabling scientists to analyze new and different types of data as well as analyze larger datasets in less time. MD Insider also uses Cloud Storage for big data staging and Cloud Dataproc to run managed Apache Spark clusters for data processing.
“Google Cloud Platform gives us an incredibly powerful cloud architecture for data engineering and data science,” says Eric Wilson, CEO of MD Insider. “That gives our scientists independence, they can do what they need to do without waiting and with no contention between them.”
A developer-friendly platform
Migrating its data services was such a success that MD Insider decided to move the rest of its infrastructure to GCP, including the front end for its web application. Since the migration, MD Insider has experienced no unplanned downtime on GCP, allowing it to easily meet the 99.5% uptime SLA it promises to customers. It’s also taking advantage of Build Triggers in Kubernetes Engine to automate container builds and reduce build times by more than 40%. Production code can be updated in seconds, with no impact to end users other than making new features available.
“GCP has simplified our workflow in so many ways, from intelligent load balancing to content delivery and automating builds,” says Matthew Frey, Software Engineer. “Everything on GCP is cohesive and developer friendly, with a superior UI and better network performance than other cloud providers.”
Ryan Beaini, Senior Software Engineer at MD Insider, agrees: “Since we moved to GCP, our developers are definitely happier. The pain and the headaches we experienced because of the limitations of our previous toolset all went away.”
“We’re a small company, but what we’re doing is incredibly important. We’re helping people make decisions about healthcare providers that could impact their lives and even be life-saving. Google Cloud Platform is helping us make our mission bigger, better, and brighter.”
—Eric Wilson, CEO, MD Insider
Securing billions of rows of clinical and non-clinical healthcare data
As a healthcare technology company, MD Insider processes billions of rows of clinical and non-clinical healthcare data. To control user access to GCP, it uses Identity & Access Management (IAM) along with Yubico YubiKeys for hardware-based two-factor authentication when logging into Google Workspace. MD Insider takes comfort that GCP encrypts data at rest by default, and encrypts and authenticates data in transit when data moves outside physical boundaries not controlled by Google or on behalf of Google.
“On GCP, everything that we need to be encrypted for compliance purposes is encrypted, which is fantastic,” says Eric. “When I tell our potential clients and partners about the resources that Google has dedicated to security, it gives them the confidence that their data will be protected.”
Transforming how teams work
As a growing company, MD Insider must collaborate seamlessly between offices in California, Colorado, and Illinois. It relies on Google Workspace for communication and productivity, using Docs, Sheets, and Slides to drive the business. Employee and team files are stored in Drive, and meetings are conducted via Google Meet with Chromebox for Meetings videoconferencing hardware kits. Google Workspace also helps MD Insider maintain information security by authenticating email domains with digital signatures in Gmail and scanning outgoing email using Gmail Data Loss Prevention (DLP).
“I use Google Workspace every day, and everyone else here does too,” says Eric. “Team Drives are a big time saver for us. We’ve let our previous office software expire, because there’s no need to pay for those licenses anymore.”
Promoting healthcare transparency
With GCP helping MD Insider increase velocity and momentum, the company is making exciting progress. For example, it has entered into a strategic partnership with Zelis Healthcare, which will use MD Insider’s API to provide insights for a next-gen analytics platform that will give health plans unprecedented transparency around physician performance.
“We’re a small company, but what we’re doing is incredibly important,” says Eric. “We’re helping people make decisions about healthcare providers that could impact their lives and even be life-saving. Google Cloud Platform is helping us make our mission bigger, better, and brighter.”
*Google Workspace was formerly known as G Suite prior to Oct. 6, 2020.
Google Cloud Featured at TechCrunch Disrupt 2021
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Startups need to move quickly and focus their limited resources on areas where they can differentiate. If infrastructure isn’t your differentiator, don’t put a lot of energy into your infrastructure when someone else can do it for you. What’s more, time-to-market matters to startups more now than ever. Successful early stage companies know this, and leverage existing tools, libraries, frameworks and innovations whenever possible.
Next week Google Cloud will be featured at TechCrunch Disrupt, the iconic annual event where “founders and investors shaping the future of disruptive technology” come together to share stories, network, and learn from each other. Google Cloud will host a session and Google Cloud engineers will be available in a virtual booth to answer startup questions.
The session, “Demo Derby – How startups are disrupting the status quo with innovative data analytics, AI and modern app development” will be a fun, fast-paced set of presentations showing short demos of startups and startup projects built with Google Cloud.
Demo Derby Presenters
- Andrea Le Vot, Chief Data Protection Officer with startup BlueZoo will deliver a demo showing how they are revolutionizing the property insurance industry with AI and Cloud – and doing so while actually protecting people’s privacy.
- Dale Markowitz and Zack Akil, Applied AI Engineers, will show how easy it is to use AI for everything from video search to editing to automated translation.
- Vidya Nagarajan, Group Product Manager from Google Cloud will deliver a fast paced demo that shows how startups can drive developer productivity with serverless innovations.
“Disrupt is iconic for its engagement with founders, investors, and the broad community of early stage companies,” said Andrea Le Vot, Chief Data Protection Officer at BlueZoo. “We are thrilled to share our insights with others in our community, and to show how we have partnered with Google Cloud to innovate faster than most of the larger, well funded insurance companies in our market.”
The series of snippet sized demos will be followed by a roundtable discussion with the demo developers focused on lessons learned, best practices, how to reduce time-to-market, and how to focus on where you can most effectively differentiate.
The session will air on Day One of the event: Tuesday September 21, 2021 at 1pm PT and will be available on demand after the event for all Disrupt attendees.
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Do you want to fire up a bunch of techies? Talk about multicloud! There is no shortage of opinions. I figured we should tackle this hot topic head-on, so I recently talked to four smart folks—Corey Quinn of Duckbill Group, Armon Dadgar of Hashicorp, Tammy Bryant Butow of Gremlin, and James Watters of VMware—about what multicloud is
Marxent Leverages Google Cloud to Elevate Customer Journeys on Retail Apps with 3D Shopping Experiences
As ecommerce for home goods exploded in popularity during COVID, furniture and DIY retailers looked to find new ways to grow online transaction sizes to in-store levels. Shopping for furniture and home improvement projects has always been challenging online. Furniture, kitchen cabinets, fixtures, and appliances become a part of daily
Why the C-suite Can No Longer Ignore Cloud Computing
Gone are the days when technology was relegated to the sidelines of a business, only considered essential for industries and professionals directly dealing with it. Today, it is not just a value-add, but an integral part of every enterprise’s operations and ultimately, its success. This has wrought many changes in
