IT leaders today are being asked to simultaneously support their company’s infrastructure, find opportunities for growth, and meet their goals with fewer resources and smaller budgets than before. Recently we highlighted three customers who are leveraging Google Cloud VMware Engine to achieve these goals while lowering their TCO and transforming their organization. 

It’s because of these successful customer outcomes that we have been awarded the 2023 VMware Cloud Innovation and SaaS Transformation partner achievement award for delivering solutions that accelerate customers’ digital transformation journey. We’re honored to receive this award and continue to stay focused on delivering tremendous value to our customers.

In the past few months, we’ve also made several updates to Google Cloud VMware Engine. Today’s post provides a recap of the latest milestones that make it easier for you to migrate and run your vSphere workloads in a cloud-first, enterprise-class VMware environment in Google Cloud. 

Back in September 2022, we announced a number of updates including the preview of API/CLI support (which is now available). In February 2023, we also talked about how to use NetApp CVS as datastores for VMware Engine.

Key updates this time around include:

Availability of VMware Engine in Delhi, Santiago and Milan regions: This brings the availability of VMware Engine to 17 regions worldwide, each supporting 4 9’s of uptime SLA for clusters 5 or more, serving the needs of our regional and multi-national customers. In addition, we have also added a second zone in the London region.

Filestore datastore support for VMware Engine: Generally Available in all VMware Engine regions, you can use Filestore High Scale and Enterprise tier instances as external NFS datastores for VMware Engine nodes. Filestore is VMware certified as an NFS datastore with VMware Engine. You can size compute and storage capacity independently to meet your workload requirements for your storage-intensive VMs. You can also leverage vSAN for low-latency VM requirements and scale Filestore from TBs to PBs for the capacity hungry VMs. If interested in this feature, please contact your Google account team.

Stretched private clouds: These private clouds stretch across two data zones and a witness zone all within the same Google Cloud region. Stretched private clouds use vSphere and vSAN stretched clusters to provide compute and storage high availability against zone-level failures. This capability is now available in Frankfurt and Sydney regions. Learn more here.

Zerto solution version 9.5u1 support: This recovery solution allows critical infrastructure and application virtual machines (VMs) to be replicated continuously from your on-premises vCenter to your private cloud. Learn more about setting up Zerto here.

Google Cloud Backup and Disaster Recovery (GCBDR): GCBDR is available to protect applications running in VMware Engine, and can be managed within the Google Cloud Console. We recently launched GCBDR under Google Cloud Platform Terms of Service simplifying customers’ purchasing and support experience. 

vTPM support: Google Cloud VMware Engine private clouds now support the addition of a Trusted Platform Module (TPM) 2.0 virtual cryptoprocessor to a virtual machine. You can add vTPMs to VMs by following VMware instructions or upgrading your existing VMs to include a vTPM. You can read more about this in the VMware blog.

This brings us to the end of our updates this time. For the latest updates to the service, please bookmark our release notes.

🎧 Prefer to listen? Check out this episode on the Google Cloud Reader podcast

If you’re anything like me, you love reading, but also appreciate that sometimes your eyes need to be doing other things; whether it’s finding your exit off the highway, or keeping your puppy from destroying the couch.

And sometimes the thought of sitting down to read something just feels like it’s going to take valuable multi-tasking time away from my day. I know, I know, multitasking can be frowned upon, but it’s the way I live a good chunk of my life, and it’s working out so far. And while I’m not alone in my multitasking, I’m also not alone in my desire for a non-visual way to get this content, or any content.

*Google Cloud Reader enters the chat*

Google Cloud Reader is a podcast that lets you listen to the Google Cloud Blog posts that aren’t as dependent on visuals. This means they’re articles that are, or are adapted to be, less focused on graphs, or code samples, and instead describe the meaning behind those visual aids. 

It’s an easy, audible way to absorb content around all things new in Cloud, while still being able to make sure Ruthie doesn’t eat my work from home equipment. 

So by now you’re probably thinking “OK, so you started a podcast during the pandemic, even though you definitely seemed like the type to start making sourdough”—and you’re right. My 53 plants agree with you. But rest assured, one can listen to an episode of this podcast *while* creating a macramé plant hanger, or waiting for bread to rise—multitasking, am I right?

We’re a little over 50 episodes/macrame plant hangers in, so you should check it out (Ruth and I would appreciate it).

Some of my personal favorites 

• Beginners Guide to Painless Machine Learning – Learn how to get started with Google Cloud AI tools
• Introducing GKE Autopilot: A Revolution in Managed Kubernetes – Learn more about GKE Autopilot, a revolutionary mode of operations for managed Kubernetes that lets you focus on your software, while GKE Autopilot manages the infrastructure.
• Cook up your own ML recipes with AI Platform – ​​Learn about Mars Wrigley’s new ML-inspired recipe experiment on Google Cloud and how you can get started with your own.
• Recovering Global Wildlife Populations using ML – Review Google’s Wildlife Insight’s ML project and help users create an image classification model for motion-sensor cameras (called camera traps) used to help protect wildlife in an non-invasive way by collecting and tagging species via pictures.

Let me know your favorite episodes, and what other articles you’d like to hear on Twitter @jbrojbrojbro!

No matter why you prefer an audio format, we’ve got you covered; Google Cloud Reader, where we read the tech blog for you, and to you.

Get all the Google Cloud Reader on your favorite podcast platform, including Google Podcasts, Apple Podcasts, and Spotify.

When Google announced our plan to go beyond purchasing renewable power for 100% of our energy usage and operate on 24/7 carbon-free energy by 2030, we noted that achieving this goal will require new transaction structures, advancements in clean energy policy, and innovative new technologies. Today, we’re pleased to announce that one of these new technologies—a first-of-its-kind, next-generation geothermal project—will soon begin adding carbon-free energy to the electric grid that serves our data centers and infrastructure throughout Nevada, including our Cloud region in Las Vegas.  

Google and clean-energy startup Fervo have just signed the world’s first corporate agreement to develop a next-generation geothermal power project, which will provide an “always-on” carbon-free resource that can reduce our hourly reliance on fossil fuels. In 2022, Fervo will begin adding “firm” geothermal energy to the state’s electric grid system, where Google’s commitments already include one of the world’s largest corporate solar-plus-storage power purchase agreements. 

Importantly, this collaboration also sets the stage for next-generation geothermal to play a role as a firm and flexible carbon-free energy source that can increasingly replace carbon-emitting fossil fuels—especially when aided by policies that expand and improve electricity markets; incentivize deployment of innovative technologies; and increase investments in clean energy research, development, and demonstration (RD&D). 

Next-generation geothermal technology

Traditional geothermal already provides carbon-free baseload energy to a number of power grids. But because of cost and location constraints, it accounts for a very small percentage of global clean energy production. 

That’s one reason this new approach is so exciting; by using advanced drilling, fiber-optic sensing, and analytics techniques, next-generation geothermal can unlock an entirely new class of resource. And the US Department of Energy has found that with advancements in policy, technology, and procurement, geothermal energy could provide up to 120 GW of firm, flexible generation capacity in the US by 2050. 

As part of our agreement, Google is partnering with Fervo to develop AI and machine learning that could boost the productivity of next-generation geothermal and make it more effective at responding to demand, while also filling in the gaps left by variable renewable energy sources. Although this project is still in the early stages, it shows promise.

Using fiber-optic cables inside wells, Fervo can gather real-time data on flow, temperature, and performance of the geothermal resource. This data allows Fervo to identify precisely where the best resources exist, making it possible to control flow at various depths. Coupled with the AI and machine learning development outlined above, these capabilities can increase productivity and unlock flexible geothermal power in a range of new places. 

This won’t be the first time that Google is applying software solutions to clean energy applications: we’ve just announced an update to our carbon-intelligent computing program that helps us reduce emissions associated with running applications at Google data centers. And other forms of AI and machine learning are currently being used to increase the value of wind energy. 

Already this year, Google has taken significant strides toward sourcing 24/7 carbon-free energy for all our data centers, office campuses, and Cloud regions. On Earth Day, our CEO Sundar Pichai announced that for the first time, five of our global data center sites operated near or at 90% carbon-free energy in 2020. 

Not only does this Fervo project bring our data centers in Nevada closer to round-the-clock clean energy, but it also acts as a proof-of-concept to show how firm clean energy sources such as next-generation geothermal could eventually help replace carbon-emitting power sources around the world.

Thirteen years’ experience in e-commerce has given Teddy Chan, Chief Executive Officer and Chief Technology Officer, AfterShip, a deep understanding of the challenges of shipping and tracking packages to customers worldwide.

“The key problem many merchants face is customers asking ‘where is my order?’ and ‘when I will get the package?’” Chan says. “When I considered this issue, I came up with the idea of AfterShip.” Chan helped found AfterShip in 2011 to enable merchants to keep track of packages sent to customers via a web portal or an API. AfterShip also allows merchants to notify customers of anticipated delivery times.

“Using AfterShip, merchants can provide the same experience to buyers regardless of which couriers they use,” Chan says. “Merchants can also improve their customer engagement by including up-selling or marketing content with their delivery notifications.”

Hong Kong-headquartered AfterShip continues to grow quickly and now has a 40-person team. Thirty members of this team are based on the China special administrative region and 10 are based in India.

“Google Cloud Platform has a network of global datacentres with deep connectivity that enables us to put our infrastructure close to our customers. In addition, the ability to horizontally scale our global database using tools such as Google Cloud Spanner eliminates any limits on our geographic expansion.”

—Teddy Chan, Chief Executive Officer and Chief Technology Officer, AfterShip

By October 2017, the business was tracking about 30 million packages per month and had expanded its services to include label and rate calculation and self-service return. Revenue, package transaction numbers and team size have doubled every year for the past three years, while more than 300,000 merchants and 426 couriers are signed up to the service. Key customers include Wish, Etsy and Groupon.

Close to half AfterShip’s customers are based in the United States, about one third in Europe and the remainder are located in Asia. AfterShip had initially delivered its applications and services from an incumbent public cloud service. However, the company wanted to continue its growth trajectory while automating key infrastructure processes, implementing a continuous deployment model and controlling costs.

The business needed to achieve these objectives while maintaining a global presence and high-quality service. AfterShip started reviewing its options and decided to migrate to Google Cloud Platform (GCP). “Google Cloud Platform has a network of global datacentres with deep connectivity that enables us to place our infrastructure close to our customers,” Chan says.

“In addition, the ability to horizontally scale our global database using tools such as Google Cloud Spanner eliminates any limits to our geographic expansion. Furthermore, the managed services provided through GCP would allow us to focus on building better features for online merchants.” The reliability provided by GCP would also enable AfterShip to meet the stringent service level requirements of large digital marketplaces in the United States, Asia and elsewhere.

“Google Cloud Platform could manage the high volumes and enable us to deliver the service levels that would realise our ambition of becoming the number one tracking API platform in the world,” Chan says. “For example, with Google Cloud Platform, we can provide a 99.95% monthly uptime service level to our customers.” Finally, GCP provided managed solutions, including Google Kubernetes Engine powered by open source container orchestrator Kubernetes, that would enable AfterShip to automate processes such as scaling and enable its team to focus on developing applications.

AfterShip has moved its websites into GCP infrastructure in three datacentres around the world and anticipates completing the migration in Q4 2017. “Google provided a lot of assistance, particularly early in the project when we needed it,” Chan says. “They briefed us on several services we hadn’t known about that could replace the equivalents in the public cloud we were using previously.” The business then completed the migration using its own skilled team members. As well as Google Kubernetes Engine and Google Cloud Spanner, AfterShip is using Google BigQuery to store and analyse transaction information.

“Google Cloud Platform could manage the high volumes and enable us to deliver the service levels that would realise our ambition of becoming the number one tracking API platform in the world.”

—Teddy Chan, Chief Executive Officer and Chief Technology Officer, AfterShip

Deployment times down from one hour to two minutes

With deployment times falling from up to one hour in its previous cloud environment to about two minutes in GCP, AfterShip has been able to adopt a continuous deployment model. “This has improved our service levels,” Chan says. “If there are any issues we can fix them quickly, while we can iterate faster to create new features in response to customer requests or changes in the market. “This enables us to continue to lead our competitors.”

Targeting a 30 percent reduction in costs

AfterShip is now targeting a 30% reduction in costs by optimising its use of Docker containerisation technology on GCP.

“By using Docker with Kubernetes, we have been able to fine-tune our use of compute resources and better control our costs,” Chan says. “We’re extremely pleased with Google Cloud Platform as it really is built for engineers,” he adds. “In addition, its documentation is extremely clear, allowing us to troubleshoot or carry out activities on the platform ourselves. “We look forward to continuing to grow and extend our package tracking and associated services with Google Cloud Platform.”