Quanta Services is the leading specialty contractor with the largest and highly-skilled trained workforce in North America. It provides fully-integrated solutions for the electric power

pipeline industrial and telecommunications industries the company’s geographic footprint which includes North America Latin America and Australia.

It’s network of companies ensures world-class execution with local delivery and has over 40,000 employees.

“The exciting thing about Backstory is it allows us to land massive amounts of data from all of our different security tools and then Chronicle worries about how to correlate and aggregate this information for us. We can then focus on the highest priority threats.”

Richard Breaux, Manager Security Operations Quanta Services

Because Quanta Services’ customers provide energy and telecommunications to their customers, they have world-class cybersecurity requirements.

“We must ensure that Quanta leads the industry given the fact that our business is building the core infrastructure that powers people’s lives. It’s crucial that we meet their cybersecurity requirements,” says James Stinson, VP-IT, Quanta Services.

To support this goal Quanta implemented a number of security tools that generate terabytes of security telemetry. Over time, however, these systems generated an information overload for the company’s limited pool of qualified security resources.

“Our logging tools also couldn’t keep up with the rapidly growing information. With limited resources we need to focus our security analysts time on high quality work instead of digging through mountains of data,” says Stinson.

They achieve this by implementing Backstory and Chronicle, which is on Google Cloud.

“The exciting thing about Backstory is it allows us to land massive amounts of data from all of our different security tools and then Chronicle worries about how to correlate and aggregate this information for us. We can then focus on the highest priority threats,” says Richard Breaux, Manager Security Operations Quanta Services.

As a result, the company’s security  team spends less time getting to the core information they need to address these incidents.

“What used to take us 15 minutes or more, we can now accomplish in seconds,” says Breaux.

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.

The ability to quickly introduce and evolve payment options for products or services is essential for businesses, as nearly 50% of consumers who can’t use a preferred payment method abandon their purchase. At the same time, gift cards, branded credit cards and rewards programs are critical tools that companies rely on to build more loyal and lasting customer relationships. With Highnote, companies have an all-in-one embedded platform to quickly create payment cards and wallets, offer innovative rewards programs and credit, and provide sustainable wage access. It is the first platform that allows enterprises to make card issuance an embedded capability of their product without creating an entirely new (and costly) organization.

Creating an exciting fintech future with Google Cloud

When thinking about building the industry’s first end-to-end embedded finance platform, we quickly realized Highnote would only be successful if it enabled companies to truly innovate and quickly roll out new programs. To do so, the platform would have to be built on scalable infrastructure capable of securely delivering services with speed and reliability while offering easy access to actionable Big Data analytics.

Working closely with the team at the Google for Startups Cloud Program, we successfully implemented Google Cloud as a versatile, future-proof foundation of our platform—and built Highnote from the ground up in just one year. Highnote’s GraphQL-based API platform reinvents the card issuance process. Utilizing the developer-friendly Highnote platform, product and engineering teams at digital enterprises of all sizes can easily and efficiently embed virtual and physical payment cards (commercial and consumer prepaid, debit, credit, and charge), ledger, and wallet capabilities into their existing products. This creates compelling value while growing revenue and building a unique and differentiated brand.

We leverage Cloud Spanner, BigQuery, and Google Kubernetes Engine (GKE) to create a unified and highly secure PCI DSS-compliant platform with GraphQL APIs that provide rapid and flexible money transfers. This gives us a reliable platform to deliver and test customer experiences, respond to outcomes, and make better business decisions. Powered by Google Cloud, our data models and application domains are architected to support configurations and customizations that unlock a diverse set of new use cases across industries, including retail, travel, logistics, healthcare, and sustainable wage access programs.

We are especially proud to highlight our enablement of sustainable wage access, as this program helps the 50% of Americans living paycheck to paycheck. Embedding this program within payroll systems provides a viable alternative to payday lenders who often charge exorbitant fees and interest rates. In real world terms, this means Highnote helps people access earned wages before payday at no cost.

The other customer we just went live with was Tillful, and their Tillful card helps small businesses build their business credit. This program will help new and emerging businesses as well as underrepresented owners of small businesses by making the credit ecosystem accessible. Highnote’s platform is designed to support multiple use cases across many industries. For example, we also help the trucking and logistics companies to develop fleet and fuel cards, and spend management companies who are looking to uplevel offerings.

Delivering high-performance transactions with Cloud Spanner

Building one of the world’s most modern card platforms would not have been possible without Cloud Spanner. We needed a solution that would keep our massive petabyte databases from buckling and more securely deliver data anywhere in the U.S. Cloud Spanner does all this and more, as it routinely connects purchases from millions of customers to tens of thousands of vendors. We also wanted to reduce overhead by 80% by eliminating manual sharding, partitioning, and optimization of data. These processes are automatic with Cloud Spanner so we can operate at maximum efficiency.

We specifically selected Cloud Spanner as our distributed SQL database management and storage solution because of its outstanding availability, zero plan maintenance downtime, security certifications, and the highest consistency guarantees of any scale-out database. We continue to optimally scale without any downtime or compromises to the integrity or security of our data. This is key for us because we can address unexpected spikes, long-term growth, and new services without costly rearchitecting.

Highnote is designed to perform over billions of transactions on Cloud Spanner, and the average latency of less than 250 ms is a testament to the robustness of Google Cloud services.

Enabling actionable customer insights at scale

BigQuery is another key Google Cloud solution that we rely on to deliver deep insights and visibility for our customers on a highly secure and scalable platform. When building Highnote, we knew we needed a cost-effective solution that excelled at data analytics. This is particularly critical for accurately measuring the performance—whether profitability or efficacy—of any program or card.

Using BigQuery, we successfully run analytics at scale with as much as a 34% lower three-year TCO than cloud data warehouse alternatives. Over the past year, BigQuery has enabled our customers to unlock data-rich capabilities with a ledger that tracks money in real time and serves up complete debit and credit entries for every event across their accounts. Companies also access real time balances for revenue, fees, customer accounts, and available funds management without complicated spreadsheets.

To quickly and efficiently roll out Highnote to our customers, we needed a simple way to automatically deploy, scale, and manage Kubernetes. When selecting a Kubernetes management tool, our top priorities were rapidly spinning up and securely scaling across multiple sites. As part of Google Cloud’s expansive ecosystem, Google Kubernetes Engine (GKE) was the top choice due to seamless and automatic Kubernetes scaling and management.

We quickly got off the ground with single-click clusters and scaled up by using the high-availability control plane—including multi-zonal and regional clusters—to easily accommodate multiple active-active regions (which other solutions cannot do). As an embedded finance platform, stringent security protocols were obviously a key consideration for us. GKE is secure by default and runs routine vulnerability scans of container images and data encryption. Further security assistance was provided by Google Cloud partners 66degrees and DoiT International to help us rapidly validate VPC PCI compliance and ensure the uninterrupted performance of thousands of transactions per second.

Winning in fintech with Google for Startups

Building the industry’s first end-to-end embedded finance platform would have been extremely challenging without the extensive Google Cloud support. By working closely with our Startups team and Google partners, we had access to Google Cloud services to more easily validate VPC PCI compliance and address most issues before we exited stealth. Their responsiveness is incredible and stands out compared to support services we’ve seen from other technology providers.

Our participation in the Google for Startups Cloud program has been instrumental to our success. With Google Cloud, we are making embedded payments accessible to our customers without a big budget price tag. By doing so, we help unleash the creativity of emerging enterprises by enabling them to innovate with payment services and rewards programs to reach new markets and customers. If companies can dream, we can enable them to realize it on Highnote. Our platform really is that flexible. We’re excited where we can go and grow with Google Cloud.

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.

Commercial trucks often travel partially empty because many shippers don’t have enough cargo to fill an entire container or trailer. Although offering available space to other shippers helps minimize carbon emissions and reduce operating costs, most trucking companies can’t efficiently schedule, track, or deliver multiple freight loads.

Companies have always struggled to ship over-the-road freight efficiently. However,recent economic events have created an unprecedented logistics and transportation crisis that continues to disrupt supply chains, delay deliveries, and significantly raise the price of basic goods. Since some stores can’t keep their shelves fully stocked, many people across the country are finding it more difficult than ever to buy the things they need at an affordable price.

Although exacerbated by the pandemic, many of these supply chain issues have existed for decades. That’s why, in 2015, Flock Freight was started with the mission of reducing waste and inefficiency from the supply chain by reimagining the way freight moves. First to market with advanced algorithms that enable pooling shipments at scale, we create a new standard of service for shippers, increase revenue for carriers and reduce the impact of carbon emissions through shared truckload (STL) service.

Our technology helps lower prices compared to full truckload (FTL) by enabling shippers to only pay for the space they need—and maintain full control over pickup and delivery dates. Flock Freight also optimizes travel routes to speed up deliveries compared to traditional less than truckload (LTL), while eliminating unnecessary shipping hub transfers to minimize damage to cargo.

Today, thousands of shippers and trucking companies across the U.S. use Flock Freight to schedule shared truckloads, lower shipping costs, quickly deliver and track goods, and reduce their carbon footprint by up to 40%. Flock Freight further offsets carbon emissions by buying carbon credits for every FlockDirect™ guaranteed shared truckload shipment—at no extra cost to shippers.

Moving Flock Freight to Google Cloud

We founded Flock Freight with a small team based in southern California. We soon realized we needed a more scalable and affordable technology stack to support our rapidly growing platform and team. After joining the Google for Startups Cloud Program and consulting with dedicated Google startup experts, we decided to move all our data and applications to Google Cloud.

The highly secure-by-design infrastructure of Google Cloud now enables thousands of Flock Freight customers to move their freight faster, cheaper, and with less damage than traditional shipping methods. Specifically, we rely on Google Kubernetes Engine (GKE) to support the combinatorial optimization and machine learning (ML) algorithms and services that identify, pool, and schedule shared truckloads. We also leverage GKE to rapidly develop, deploy, and manage new applications and services.

In addition, we leverage Cloud SQL to automate database provisioning, storage capacity management, and other time-consuming tasks. Cloud SQL easily integrates with existing apps and Google Cloud services such as GKE and Pub/Sub. Lastly, we use Compute Engine to create and run virtual machines, optimize resource utilization, and lower computing costs by up to 91%. These cost savings allow us to shift more resources to R&D and rapidly develop new solutions and services for our customers.

Building a greener, more resilient, and responsive supply chain

The Google for Startups Cloud Program and dedicated Google startup experts were instrumental in helping us manage cloud infrastructure cost and maintaining very high SLAs, helping Flock Freight to focus on developing a comprehensive shipping platform that powers shared truckloads and drives positive industry change.

We especially want to highlight the Google Cloud research credits we relied on to launch Flock Freight and make rapid progress toward transforming the shipping industry. To this day, we continue to work with Google Cloud Managed Services partner DoiT International International to further scale and optimize operations on Google Cloud.

We’re proud of the results we’re delivering for our customers. For example, a home improvement importer now enjoys faster, safer, and easier shipping with 99.9% damage-free service and a 97.5% on-time delivery rate. A packaging supplier continues to maintain a 99% on-time delivery streak and decrease carbon emissions by 37%, while a mineral water company consistently reduces delivery expenses upwards of 50%.

Nationwide demand for shared truckloads continues to increase as the shipping industry works to lower costs and alleviate supply chain disruptions. With the Flock Freight platform, companies are building a more sustainable and resilient supply chain by efficiently combining multiple shipments into shared truckloads.

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.