Editor’s note: Earth Day reminds us that we all can contribute to creating a cleaner, healthier, and more sustainable future. Google Cloud is excited to celebrate innovative startup companies developing new technology and driving sustainable change. On this year’s Earth Day we’re highlighting Enexor BioEnergy and their initiative to produce clean, sustainable energy from plastic and agro-waste with the help of Google Cloud solutions.

Picture a world without electricity where billions of people burn dangerous fuels and trash from landfills to cook meals and heat their homes. Children constantly cough, choking on toxic smoke that lingers in houses and sickens entire families. Because there are no pumps or purification plants, contaminated water is hauled in buckets from dirty rivers and polluted wells. Without power or lights, hospitals and emergency medical clinics can only provide basic services during the day.

Although it is 2022, this harsh life is a reality for billions of people living in developing countries around the world.

Producing clean energy from plastics and organic-waste

This Earth Day, let’s imagine what life would be like in these countries if people had access to safe and inexpensive bioenergy. In this world, indoor air is fresher. Clean water runs from faucets, while homes, businesses, and schools have electricity. Doctors and nurses have the power to treat patients 24 hours a day and save lives with advanced medical equipment. Local economies boom and entrepreneurs thrive.

This is the sustainable future Enexor BioEnergy and its partners are building—one village at a time. With the Enexor Bio-CHP™ system, we produce clean and sustainable energy from discarded plastics, organic, and biomass-waste such as rice and corn husks, seaweed, coconuts, and other biomatter while offsetting significant Carbon emissions. The Bio-CHP can be commissioned and easily installed in just a single day, with multiple systems installed side-by-side when more power is needed. By being offered under its novel Energy-as-a-Service business model, Enexor ensures that the Bio-CHP can generate immediate environmental positive impact and customer adoption.

Each Bio-CHP unit generates enough energy to power over 100 homes—and provides much-needed renewable electricity and thermal power for schools, businesses, manufacturing facilities, water pumps, Wi-Fi systems, and telecommunications towers. The Bio-CHP creates clean energy by safely oxidizing plastics and biomatter in a secure container using a high-temperature system to power a micro-turbine. This produces bioenergy, significantly reducing harmful greenhouse gas emissions.

By solving a community’s waste issues while providing more affordable renewable energy, the Bio-CHP also creates new economic opportunities and improved outcomes where it is installed. This includes using its inexpensive power to expand local services and offerings, and empowering local community clean up efforts by incentivizing waste collection via blockchain-enabled digital currencies and services such as PayGo. Additionally, the Bio-CHP is an ideal solution for businesses who desire to maximize their own sustainability efforts, gain greater energy resiliency, and save money on their current energy and waste costs.

Engaging in Google for Startups Accelerator: Climate Change

When developing the Bio-CHP, we realized we needed a reliable and experienced partner to help us incorporate the best in class machine learning and artificial intelligence into our technology. That’s why we joined the Google for Startups Accelerator and participated in the Google for Startups Accelerator: Climate Change.

The accelerator introduced us to other companies working to create a sustainable future and opened new opportunities for collaboration and partnerships. The accelerator also continues to give our small team access to the best of Google Cloud’s people, programs, and solutions. We especially want to highlight Google Cloud’s dedicated startup experts and the incredible technical support they provide, as well as the Google Cloud research credits we used to explore new solutions.

As an example, Enexor is developing a predictive maintenance tool that automatically adjusts Bio-CHP operations to match fuel composition. Another tool in development proactively identifies and flags potential Bio-CHP system and component failures—before they occur.

Google Cloud’s dedicated startup experts work closely with Enexor to develop predictive models for these tools and Enexor also used the Google Cloud research credits that were provided to build these advanced models on TensorFlow, Vertex AI, Cloud CDN and AutoML. Since each system is remotely monitored from Enexor’s global headquarters in Tennessee, predictive maintenance tools also increase the safety, reliability, and efficiency of Bio-CHP in off-grid locations.

Generating 13 billion kWh of clean power by 2040

In the future, Enexor plans to explore additional Google Cloud solutions such as BigQuery to crunch larger datasets, Google Data Studio to build dashboards, and perhaps even Google Cloud Tensor Processing Units (TPUs) to more efficiently process machine learning (ML) workloads.

These solutions will help Enexor to achieve three primary goals by 2040: to generate 13 billion kWh of clean power, reduce 120 million tons of CO₂, and provide one million people with access to clean and sustainable energy. With each Bio-CHP system, Enexor annually reduces up to 2,000 metric tons of CO₂ equivalent emissions by decreasing methane emissions released from landfills, offsetting fossil fuel-based power generation with carbon credits and minimizing waste disposal transportation emissions.

Enexor is now preparing to deploy the Bio-CHP in Accra, Ghana where it will convert organic and plastic manufacturing waste into sustainable energy. Enexor is also looking forward to working with the local Accra community and NGOs to collect discarded plastics and organic waste diverting it from ending in the rivers and oceans and instead using them as renewable fuel sources. We can’t wait to see what we accomplish next as we celebrate Earth Day 2022 and think about the sustainable future Enexor is helping to empower.

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.

CIOs are again evaluating their mainframe investments, balancing rising operational costs and difficulty finding talent with the perceived costs and risks of moving critical applications to the cloud. Increased business agility, technical innovation, computing elasticity, customer insights, and a growing talent pool all encourage CIOs to migrate and modernize from “Big Iron” onto public cloud platforms. 

Google Cloud recently announced Dual Run, a new mainframe modernization solution, to help customers mitigate the risk involved in mainframe migrations and accelerate their migration to the cloud. Leaders can leverage Dual Run in their quest to ensure their mainframe modernization projects will succeed and pay off so let’s dive a little deeper into what Dual Run is, how it works, and how it can help you. 

Mainframe modernization with a proven technology

Since so many businesses still run mainframes, we decided to partner with Banco Santander—one of the largest banks in the world—to bring Dual Run to our enterprise customers, since they had already built a solution. In fact, Dual Run was built on top of Banco Santander’s unique technology which has already demonstrated proven results in the regulated financial services industry. Now that Dual Run is available, Banco Santander has been using it to bring their data and workloads onto Google Cloud’s trusted infrastructure.

The concept is not new, but the solution is unique

Dual Run enables you to run a parallel production system, allowing you to simultaneously run workloads on your mainframes and on Google Cloud. While many enterprises running mainframes have thought about parallel production concept and a few even tried before, Google Cloud is unique among the hyperscalers to provide such a solution as an offering to its customers. 

With a parallel production run, you can perform real-time testing of your applications on Google Cloud and quickly gather data on performance and stability with no disruption to your business. Once you’re satisfied with the functional and performance equivalence of the two systems, you can make the new Google Cloud environment your system of record, while existing mainframe systems can be used as a backup or decommissioned. 

In addition to the transformative benefits you get from moving to Google Cloud–such as AI-based scalability, speed, and security–migrating mainframes with Dual Run offers you even more benefits:

Mitigate migration risk: Dual Run reduces risk during the migration by running your business critical systems in parallel with powerful reporting to track the difference between your current and target systems. This ensures there is no impact or risk to your existing mainframes while migrating to Google Cloud. 

Secure migration investments: Avoid costly migration mistakes by basing your decisions and actions on empirical data acquired from your production system.

Reduce business testing effort: Compare the functional equivalence of outcomes in the current and target system with production data and drastically reduce the testing cycles of your migrated workload. 

Accelerate migration: Speed up the entire mainframe migration process with a well-defined framework, automation components, predefined dashboards, and a tested approach.  Empirical reporting available in Dual Run also enables customers in regulated industries to more readily respond to regulator reviews and requests for information.

Your migration journey with Dual Run

Dual Run is packaged with several automation components to aid your migration journey, from assessment all the way through to production. 

This chart shows how Dual Run plays a key role throughout your mainframe modernization journey:

Let’s explore this illustration in a bit more detail, phase by phase: 

Current state: This is your starting point, when your production workloads are still running in your mainframe. Dual Run helps you assess your mainframe workload for compatibility on Google Cloud. 

After this assessment, Dual Run’s conversion engine helps address the incompatibilities in your current application and then migrates the application and data to Google Cloud. At this stage, you have your current application executing on the mainframe and your migrated application is ready to be executed or tested on Google Cloud.

Dual Run state: In this state, the migrated workload will be executed in two stages.

Dual Run stage 1:

In the first stage of Dual Run, your mainframe will remain as the “primary” system — meaning the response and outputs to other systems are sent from your mainframe — while the migrated workload will be executed in parallel in Google Cloud as “secondary.”

Dual Run performs the following actions as a cyclical process, repeated until you reach your desired migrated application quality is achieved:

• All workloads — batch & transactions — executed in the mainframe are replicated in Google Cloud 
• The outcomes from both systems are validated to report any differences, enabling you to take corrective actions in migrated applications
• The functional and performance differences between the two systems will be observed, and the mainframe and Google Cloud data are periodically synchronized to bring both the systems in sync 

Typically, most of your migration time will be spent in the first stage of Dual Run until you are satisfied with the results. The key goal for this stage is that your primary, business-critical mainframe workload is not disturbed while your migrated application is tuned to provide the exact same results as your current application.

Dual Run stage 2:

When the Dual Run reporting and results confirm that the migrated application matches your mainframe system, Google Cloud then becomes the “primary” system, while your mainframe will still be executed in parallel as “secondary.” Dual Run will enable you to do a smooth switch between primary and secondary systems through a configuration management system.

Target state: In this final state, the mainframe can be decommissioned while the Dual Run components are removed, enabling an optimal and efficient business execution with Google Cloud.

Summary

For any business or organization that has to migrate or modernize their mainframes, Dual Run offers a unique solution to achieve this with reduced risk and time. In fact, what we’re seeing from our customers is that Dual Run offers the right combination of proven experience, engineering, and strategic partnership that is essential for mainframe migration success. If you would like to learn more, check out our mainframe modernization website.

As the saying goes, “it’s hard to make predictions, especially about the future.” Some organizations find it challenging to predict what cloud resources they’ll need in months or years ahead. Every organization is on its own unique cloud journey. To help, we’re developing new ways for customers to consume and pay for Google Cloud services. We’re doing this by removing barriers to entry, aligning cost to consumption and providing contractual and product flexibility. Read on to learn how we’re rolling out several new go-to-market programs across these key areas to help our customers purchase and consume Google Cloud services more easily.

Removing barriers to entry with Google Cloud Flex Agreements

Many customers choose multi-year commitments because they provide better line-of-sight into IT spend and budgeting. However, these commitments can create difficulty for those who don’t have clear visibility into their future cloud consumption needs. That’s why today we’re launching Flex Agreements, which enable customers to migrate their workloads to the cloud with no up-front commitments. As part of this new licensing option, Google Cloud customers still get access to unique incentives, such as monthly spend discounts¹, committed use discounts, cloud credits, and access to professional services, based on monthly spend and workloads migrated to Google Cloud.

Flex Agreements are just one example of how we are removing barriers to help customers start using Google Cloud. In 2022, we launched the Innovators Plus annual subscription, which gives developers a curated toolkit to accelerate their expertise, including access to live and on-demand training through Google Cloud Skills Boost, Google Cloud credits, and more. 

We also recently expanded trials for Google Cloud products. For example, the new Spanner free trial instance is good for 90 days, allowing developers to create Google Standard SQL or PostgreSQL databases, explore Spanner capabilities, and prototype applications—with no commitment or contract needed. 

Contractual and feature flexibility  

Contractual flexibility has always been one of our core principles. Committed Use Discounts (CUDs), for example, provide discounted prices in exchange for a commitment to use a minimum level of resources for a specified term. Last year, we introduced Flexible CUD, spend-based commitments that offer predictable and simple flat-rate discounts that apply across multiple virtual machine families and regions.

In addition to contractual flexibility, our customers also need the flexibility to choose features and functionality based on their stages of cloud adoption and the complexity of their business requirements. Therefore, over the next few quarters, we will launch new product pricing editions—Standard, Enterprise, and Enterprise Plus—in parts of our cloud portfolio. This new commercial packaging model will help give customers more choice and flexibility to optimize their cloud spend.

For customers running workloads such as those in regulated industries like banking and public sector, the higher-end Enterprise Plus tier will offer compute, storage, networking and analytics services with high availability, multi-region support, regional failover and disaster recovery, advanced security, and a broad range of regulatory compliance support. The Enterprise pricing tier will include a broad range of features designed for customers with workloads that demand a high level of scalability, flexibility, and reliability. The Standard pricing tier will offer cost-efficient and easy-to-use managed services that include all essential capabilities such as autoscaling to meet the core workload requirements of customers.

Align costs to consumption with autoscaling

At Google Cloud, a core requirement for the products we build is providing customers industry-leading capabilities to automatically scale (autoscale) services up and down to match capacity with real-time demand. Autoscaling improves uptime, reduces infrastructure costs, and removes the operational burden of managing resources.  

Many Google Cloud products include autoscaling capabilities to help customers manage unplanned variations in demand. For example, Dataflow vertical and horizontal autoscaling, in combination with granular adaptive resource configuration (aka “right-fitting”), has resulted in up to 50% saving in infrastructure costs for streaming by automatically choosing the right number of instances required to run the jobs and dynamically re-allocating more or fewer instances during the runtime of jobs. Bigtable also provides native autoscaling capabilities, and Spanner’s autoscale is an open source tool that works across regional and multi-regional Spanner deployments. 

Similarly, we added multiple features such as Cluster Autoscaler, Horizontal Pod Autoscaling, Vertical Pod Autoscaling, and Node Auto-Provisioning to GKE for elasticity and cost efficiency. 

For L.L.Bean, the ability to quickly scale capacity to meet changing usage patterns (e.g., during the holidays), as well as to rapidly perform load tests to test capacity, are “night and day” with Google Cloud compared to L.L.Bean’s legacy on-premises IT system.

“We won’t have to pay for peak capacity to have it available during peak shopping times. We just scale capacity up or down as needed.” — Randy Dyer, Enterprise Architect, L.L.Bean

We are now taking these capabilities to the next level by enabling autoscaling in BigQuery at a more granular level so you never pay more than what you use. This allows you to provision additional capacity in smaller increments, so you never overprovision and overpay for underutilized capacity. BigQuery customers can now try the new BigQuery autoscaler (currently in public preview) in their Google Cloud console.

A commitment to flexibility and choice

At Google Cloud, we remain deeply committed to the success of our customers and partners, and we are uniquely positioned to help organizations transform their business. By providing you with more flexibility and choice in how to purchase our products, we are empowering you to be more efficient and resilient.

Join Google Data Cloud & AI Summit to hear the latest announcements around innovations in Google Data Cloud for databases, data analytics, business intelligence, and AI. Gain expert insights, new solutions, and strategies that can help you transform customer experiences with modern apps, boost revenue, and reduce costs.

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If you took one look at the title of this blog and thought, “just show me how, because I already know a million reasons why I’m stressed about billing things” then check out the interactive tutorial right here.

For everyone else, read on, because we’ll walk through some common sense tips, and a few step-by-step tutorials for all things billing related. If you’ve ever wished you could sit down with someone from Google Cloud, and walk through your bill, the console, and your options — you’re in the right place! Consider this Cloud Billing 101 – an intro level course that’ll get you started on the right foot.

6 simple tips to manage your Google Cloud billing accounts:

1. Get to know your billing statement and console: Knowledge is power, after all. Take a tour of the billing console so you can better understand your options, along with what’s included in your monthly bill and the different components.
2. Set up authorized users, alerts and budgets: Make sure anyone who needs to have access to payment settings is authorized. Allocate budgets for projects, and get notifications when your usage or spending exceeds a certain amount so you can take action as needed.
3. Use cost-saving tools: We’ve got  a range of tools and services to help you save money, like Committed Use Discounts, and even Recommenders for actionable, AI-powered intelligent recommendations around your cost trends and product usage.
4. Optimize your resources: Use the Google Cloud Resource Manager to see how your resources are being used and identify areas for optimization, temporarily suspend, or even shut down unused projects. 
5. Review your billing history with reporting and data visualization: Regularly check your billing history with reports to help track your spending, identify any trends or patterns, and even anticipate future costs. You can even export your data to BigQuery for detailed analysis, or use a tool like Google Data Studio to visualize your data.
6. Use the pricing calculator: Estimate your monthly costs and make informed decisions with the Google Cloud pricing calculator. It can help you get a ballpark figure for your usage, and determine if your use case fits within cost-free parameters.

I hope these common sense pointers and tutorials empower you to effectively manage your Google Cloud billing and stay on top of your spending. Get started right now by managing your billing methods and payment settings in this 5-minute tutorial, and then take a tour of the billing console to get familiar with your setup.