
Evernote Ditches Private Cloud for Google Cloud and Improves Performance and Uptime
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7 Fantastic Ways Google Cloud VMWare Engine Stands Out from the Rest for Running VMWare Workloads in the Cloud!

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Google Cloud VMware Engine delivers an enterprise-grade, cloud-native VMware experience that is built on Google Cloud’s highly performant and scalable infrastructure. By enabling a consistent VMware experience, the service allows customers to adopt Google Cloud rapidly, easily, and with minimal modifications to their vSphere workloads, bringing the best of VMware and Google Cloud together on one platform for a variety of use-cases. These include rapid data center exit, application lift and shift, disaster recovery, virtual desktop infrastructure, or modernization at your own pace.
Here are seven ways VMware Engine outshines alternatives for running your VMware workloads in the cloud, simplify your operations, and help you innovate faster:
- Dedicated 100Gbps east-west networking
Google Cloud VMware Engine nodes come with redundant switching and dedicated 100Gbps east-west networking with no oversubscription of bandwidth, unlike other options where there is generally oversubscription. This is especially important when it comes to running latency-sensitive workloads. - Four 9’s of availability in a single zone
The service offers 99.99% uptime SLA for a cluster in a single Zone with five to 16 nodes and FTT=2 or more without the need for stretched clusters, which is higher than the alternatives. Further, dedicated connectivity for core service functions such as vSAN and vMotion enables better solution stability and availability. This enables the service to support the needs of enterprise workloads that require high availability.
Note: “Cluster” means a deployment of three or more dedicated bare metal nodes running VMware ESXi and associated networking managed via management interfaces.
- Global networking without complex routing
Google Cloud VMware Engine networking is built based on Google Cloud’s powerful networking architecture. With simplified regional and global routing modes—which allow a VPC’s subnets to be deployed in any region where our service is available—you can architect global networks without the need or overhead of creating and connecting regional network designs. You get instant, direct Layer 3 access between them. In alternative cloud environments, you may have to configure special networking between regions, often requiring VPN-based tunnels over the WAN to enable global uniform network communication. This adds to the deployment and operational complexity, in addition to cost. - Integrated multi-VPC networking
Users often have application deployments in different VPC networks, such as separate dev/test and production environments or multiple administrative domains across business units. The service supports “many-to-many” access from VPC networks to Google Cloud VMware Engine networks with multi-VPC networking, allowing you to retain existing deployed architectures and extend them flexibly to your VMware environments. In addition, by providing multi-VPC networking, you can pool their VMware needs—say for QA and dev—to a smaller set of clusters, effectively reducing their costs.
For more information about the end-to-end networking capabilities and services available in Google Cloud VMware Engine, please refer to the Private Cloud Networking for Google Cloud VMware Engine whitepaper. Here, you’ll find details about network flows, configuration options, and the differentiated benefits of running your VMware workloads in Google Cloud.
- Unified, cloud-integrated model
Google Cloud VMware Engine is a fully managed Google first-party service, operated and supported by Google and its world-class team. With fully integrated identities, billing, and access control, you have a simpler end-to-end experience that is different from other services. You access Google Cloud VMware Engine service via the Google Cloud console, like any other Google Cloud service. You can also access other native Google Cloud services privately from your VMware private cloud running in Google Cloud VMware Engine over local connections. - Flexibility in third-party ecosystem compatibility
With Google Cloud VMware Engine, you can set up existing VMware on-premises third-party tools or products that require additional privileges by using a solution user account. This uniquely enables operational consistency, ensuring that the tools you have invested in and used over the years work on Google Cloud VMware Engine. Furthermore, in key areas such as vSAN data encryption, you have the choice of not only using Google Cloud Key Management Service (KMS)—which is turned on by default on vSAN datastores—but also external KMS providers such as HyTrust, Thales, and Fortanix. - Dense nodes with high storage:core and memory:core ratios and fast provisioning
Google Cloud VMware Engine nodes are dense. Each node is powered by Intel® Xeon® Scalable Processors and comes with 36 cores, 72 hyperthreaded cores, 768 GB memory, 19.2 TB NVMe data and 3.2 TB NVMe cache storage. This, along with oversubscription, leads to high consolidation ratios and compelling storage:core per dollar and memory:core per dollar. In addition, you can rapidly spin up these nodes in a VMware private cloud often in under an hour, enabling on-demand, VMware-consistent capacity in Google Cloud for your needs.
These are just a few examples of customer-centric innovation that set Google Cloud VMware Engine infrastructure apart. In addition, migrating to Google cloud can save you up to 38% in TCO. Get started by learning about Google Cloud VMware Engine and your options for migration, or talk to our sales team to join the customers who have embarked upon this journey.
The authors would like to thank the Google Cloud VMware Engine product team for their contributions on this blog.
You Can Now ‘Listen’ to Over 50 Tech Blogs on Google Cloud Reader

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🎧 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.
Google’s Research and Data Insights Solutions to Power Drug Development and Clinical Research

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In order to be successful, research needs to be replicable, so scientists can build on past work and insights. However, an article in Nature warned that as much as 50% of published drug development research could not be reproduced in subsequent trials. As a result, promising drug candidates sometimes led to disappointment, as well as wasted time and money, when key findings could not be replicated.
The shift to cloud computing helps solve this problem because it allows researchers to use open-source tools that work across platforms. As demand for cloud computing rises, our customers have asked us for more ready-made solutions to assure reproducibility of results by their collaborators, regardless of the platform they are using. They asked for secure and effective collaboration tools as well as faster time-to-insight from any type of data.
We listened. Google’s new research and data insights solution includes three sets of functionalities to address these key challenges. Each can be activated on demand and may be eligible for subscription pricing. “HPC in a box” offers abstract complexity to run high performance computing (HPC) workloads by automatically managing your cluster in the most effective manner. It integrates seamlessly with some of the industry’s most-used schedulers like Slurm and PBS. It makes it easier than ever to answer bigger questions faster by accessing Google’s fast, powerful hardware like TPUs and GPUs, all for one predictable flat fee for eligible workloads. Healthcare Innovation Hub provides healthcare-specific functionality to help ingest, aggregate, and de-identify any type of healthcare data in its original format. It unlocks cross-modality analysis and collaboration and empowers researchers with harmonization tools to overcome healthcare interoperability issues. Google Cloud Real-World Insights (formerly FDA MyStudies) accelerates and streamlines drug development and clinical trials to address urgent medical challenges with reproducible results.
The solution enables researchers to ask new questions, get answers more quickly, and work more collaboratively–with no wait times or down times. Institutions can scale to more ambitious projects and generate actionable, real-time insights from any data source–all while staying within budget.
Many top research centers have already found it faster and more cost effective to shift from downloading and storing data on their own servers to storing and analyzing data on Google Cloud. Here are some of the real-world projects already yielding breakthroughs:
- Clemson analyzed 8,500 hours of traffic camera feeds with 2.1M vCPUs in three hours to improve evacuation routes for disaster planning.
- The Colorado Center for Personalized Medicine saved $2.9M by building their Compass data warehouse on Google Cloud rather than on on-prem.
- The Broad Institute slashed costs of genomic sequencing by 90% with Google Cloud.
Our partners, such as Atos, Burwood, Omnibond, Mavenwave, Quantiphi, and Deloitte, can help you first design and develop, then install and implement your own solution, including training. To assess your institution’s needs and develop a customized plan for your next-generation research solution with research and insights, contact our sales team.
Google Cloud’s Metric Scope Makes Multi-project Monitoring Simple

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Customers need scale and flexibility from their cloud and this extends into supporting services such as monitoring and logging. Google Cloud’s Monitoring and Logging observability services are built on the same platforms used by all of Google that handle over 16 million metrics queries per second, 2.5 exabytes of logs per month, and over 14 quadrillion metric points on disk, as of 2020. However, you let us know through consistent feedback that the previous construct of Workspaces for Cloud Monitoring was not providing the flexibility needed for your larger scale projects.
Cloud Operation’s New Approach to Multi-Project Monitoring
We’re happy to announce a new model for multi-project monitoring, which replaces the concept of Workspaces. This overhaul is geared toward maximizing the flexibility you have to manage your monitoring environments by introducing Metrics Scopes. Starting today you can associate your Google Cloud projects with multiple Metrics Scopes! Like Workspaces, Metrics Scopes will still be used to store all of the configuration content for dashboards, alerting policies, uptime checks, notification channels, and group definitions. However there is no limit to the number of Metrics Scopes to which you can associate a project. Prior to this change, a project could only be scoped with a single Workspace. Now, there are virtually unlimited possibilities for how you can set up multi-project monitoring. This unlocks a large variety of options, from more granular permissions to mission-focused configurations. At its most simple implementation though: operators/SREs can now create org-wide Metrics Scopes with monitoring configurations focused on infrastructure health. And developers can leverage Metrics Scopes built on a subset of their organization’s projects that allow them to focus on their application’s performance.
How it works
- When you have a collection of projects, Metrics Scopes enable you to view each project’s metrics in isolation as well as in combination with metrics stored by other projects.
- The Metrics Scope is hosted by a scoping project. This scoping project is the Cloud project that is selected in the Cloud Console project picker.
Example
- In this example, Project-SRE is the name of a scoping project to monitor your fleet. You added two developer teams’ projects: Project-Dev-1 and Project-Dev-2, to Project-SRE’s Metrics Scope. If you select Project-SRE with the Cloud Console project picker and then go to the Monitoring page, you view the metrics for all three projects:

- If you select Project-Dev-1 with the Cloud Console project picker and then go to the Monitoring page, you view the Metrics Scope for Project-Dev-1 and you can only see the metrics for that project:

What else is new?
- Metrics Scopes can now monitor up to 375 projects (up from 100).
- New projects automatically start working in Cloud Monitoring without the previous 60-second Workspace creation process.
- If you want to monitor more than one project simply add it to your Metrics Scope:

Navigation
- Mentioned earlier, the Project Picker in the Cloud Console can be used to navigate between Metrics Scopes in Cloud Monitoring:

- This is now consistent with many other services across Google Cloud. Specifically, you can see how the project picker stays consistent when navigating from Cloud Monitoring to Cloud Logging:

- Additionally, to make your navigation between Metrics Scopes easy we’ve added the new Metrics Scope Tab and Panel in the UI:

Coming Soon
- The Metrics Scope API is coming within the next quarter! This API will enable you to programmatically manage your monitoring configurations and Metrics Scopes.
Current Workspaces users
If you are already using Workspaces in Cloud Monitoring you may have noticed that they converted to Metrics Scopes weeks ago. There is no additional action required and you can start taking advantage of the additional features of Metrics Scopes today.
Get Started
Companies that are digitally native or in the process of digital transformation have placed an increased operational role on developers and this often creates overlapping sets of responsibilities with Operations and SRE teams. Now multiple developer teams can focus on optimizing the performance of their applications while operators can take a fleet-wide view when maintaining and improving the performance of all of the infrastructure under their purview.For information on configuring a Metrics Scope to include metrics for multiple projects, see Viewing metrics for multiple projects.
Google Cloud Region in Columbus to Accelerate Ohioan Businesses and Tech Transformation

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Digital tools such as cloud computing are fueling economic transformation across the US, including Ohio. Google continues to invest across cities and communities in Ohio, bringing over 200 jobs to the state, and helping provide $12.85 billion of economic activity for tens of thousands of Ohio businesses, nonprofits, publishers, creators and developers. To further accelerate the transformation of all Ohioan businesses and technologists, we’re thrilled to announce our newest Google Cloud region in Columbus, Ohio is open. The Columbus cloud region brings a second region to the Midwest, the 10th region to North America, and grows our global cloud region count to 33.

A region for the Buckeye State
Now open to Google Cloud customers, the Columbus region (us-east5) provides you with the speed and availability you need to innovate faster, build high-performing applications, and serve local customers — all on the cleanest cloud in the industry. Additionally, the region gives you added flexibility to distribute your workloads across the central, midwest, and eastern US.
The Columbus region offers immediate access to three zones, for high availability workloads, and our standard set of products, including Compute Engine, Google Kubernetes Engine, Cloud Storage, Persistent Disk, CloudSQL, and Cloud Identity. Our private backbone connects Columbus to our global network more quickly and securely. In addition, you can integrate your on-premises workloads with our new region using Cloud Interconnect. This means that Columbus-based customers can expand globally from their front door, and those based outside the region can more easily reach their users in the Midwest.
What customers are saying
Industries including retail, financial services, and IT are investing in Columbus. Organizations across these verticals have turned to the Google Cloud to innovate faster and help solve their most complex challenges
“As Wendy’s continues to innovate in new ways to create fast, frictionless, and fun interactions that redefine the way customers visit and enjoy our restaurants, our partnership with Google Cloud is a key enabler to delivering on our AI/ML and data analytics strategies. The proximity of the new Google Cloud region to Wendy’s headquarters provides the ability for us to move and scale quickly as business needs evolve. Additionally, Google Cloud’s investment in Columbus positions central Ohio as a true technology hub, which further boosts Wendy’s and other regional employers’ ability to recruit innovative talent,” said Kevin Vasconi, Chief Information Officer, Wendy’s.
“Huntington National Bank’s API Architecture is a central component to our growth and technology strategy. As our business segments grow from an offering and geographic perspective, we must evolve our technology to provide the optimal experience for our customers and our partners. Collaborating directly with Google Cloud on the build out of their cloud region in Central Ohio, provides the access our technology teams need to innovatively scale our infrastructure to meet the demands of our business with increased availability, lower latency, and greater resiliency,” said Geoff Preston, Chief Architect, Huntington National Bank.
“Google Cloud has been instrumental in our ability to scale and optimize data management and compute resources. We prioritize scale, elasticity and resilience in cloud services and Google Cloud delivers all three globally and locally. With Google Cloud security, we can efficiently process the quantities of application data required to accelerate alert detection and reduce response times for the critical infrastructure our customers depend on to enable the continuity of their vital applications.” said Sheryl Haislet, Chief Information Officer at Vertiv, a global provider of critical digital infrastructure and continuity systems headquartered in Columbus, Ohio, that leverages Google Cloud solutions to provide resilience for its operations and to better support customers.
“The addition of the new cloud region in Ohio continues to demonstrate Google Cloud’s commitment to the enterprise space and their presence in the region,” said Chris Delong, Chief Technology Officer, Designer Brands Inc. / DSW
What’s next
We are thrilled to welcome you to our new cloud region in Columbus, and eagerly await to see what you build with our platform. Register here for our Cloud Study Jam in June – an event for local developers to get hands-on training with Google Cloud. Stay tuned for more region announcements and launches this year, including our next U.S. region in Dallas, TX. And for more information, contact sales to get started with Google Cloud today.
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