Oden Technologies is using the Internet of Things (IoT) to improve the factories of today. The giant network of “things” (including people) connected to each other via the Internet has the potential to reduce waste, increase efficiency, and improve safety across all walks of life. Oden is leading IoT innovation in manufacturing by combining wireless connectivity, big data, and cloud computing.

The use of data to improve manufacturing is practically as old as manufacturing itself. But the computerization of manufacturing has resulted in broad and rapid changes to the way data is collected and processed, as well as the sheer volume of data available.

Oden’s goal is to help manufacturers tap into this data to quickly identify process trends and even warning signs of machine breakdown. Such visibility can reveal opportunities to improve manufacturing and maintenance processes that reduce waste and increase profit margins.

Oden designs and develops data collection devices that can plug into almost any kind of machine and can wirelessly transmit data with minimal complexity and setup time.

Once devices are installed, the Oden technology platform processes data to give manufacturers cutting-edge analytics that are easy to comprehend. Analysis produced by the platform provides factory engineers with data points such as detailed root-cause analysis down to the second, factory-wide performance in real-time, and trend analysis.

Improving cloud delivery

Oden’s previous cloud platform performed satisfactorily, but the company evaluated alternatives in search of potential reductions in cost and complexity and increases in performance.

When evaluating Google Cloud Platform, Oden discovered it would require fewer virtual machine (VM) instances for equivalent performance, which would cut costs. Furthermore, Oden could gain more sophisticated data analytics and machine learning capabilities compared with its existing cloud provider.

Today, Oden runs its entire platform on Google Cloud Platform including Google Compute Engine, Google Cloud Pub/Sub, Google Cloud Bigtable, Google Stackdriver, and Google Kubernetes Engine.

“In order to serve our customers, we need a cloud platform that can scale reliably while keeping costs low, perform under heavy loads, and consistently deliver sophisticated features such as machine learning,” says Willem Sundblad, CEO and Founder at Oden Technologies. “Google Cloud Platform is way ahead in all of these areas compared to our previous cloud provider.”

Capturing tens of millions of metrics a day

Using Google Cloud Platform, Oden can help an average factory capture and store approximately 10 million metrics on a single manufacturing line every day.

Metrics can include extremely granular detail, such as the amount of electricity going to machines, the amount of raw material consumed, and the volume of material produced. Sensors can also capture and transmit environmental information such as temperature, humidity, and dew point so that manufacturers can identify weather-related and seasonal impacts on production.

The updated Oden Cloud Platform uses Kubernetes Engine—powered by the open source Kubernetes system—to run application program interfaces (APIs) that capture data from Oden’s wireless devices on the factory floor.

Google Cloud Pub/Sub then sends the data in real time to Google Cloud Bigtable, where data is processed using Oden’s proprietary analytics tools. Google Stackdriver supports Google Cloud Platform monitoring, logging, and diagnostics, which help Oden deliver its cloud platform with confidence.

Oden Technologies builds dashboards powered by Kubernetes Engine, which pull analyzed data from Google Cloud Bigtable. The dashboards provide customers with real-time visibility into their manufacturing lines. Oden Factory Cloud dashboards allow customers to delve deeper into their data to fine-tune production processes or discover the root causes of production issues.

With the previous cloud provider, Oden required 80 VM instances to run the dashboards. With Google Cloud Platform that number has been cut to 45, which dramatically reduces costs and complexity.

“We migrated from our previous cloud provider to Google Cloud Platform in just one month,” says Willem. “Further, our storage and data analytics costs have decreased by 30%. Cost savings like these allow us to protect customers from rising expenses, keeping us focused on bringing the best products possible to market.”

Faster data access; more efficient factories

With Google Cloud Platform, Oden can now deliver a complete factory analytics picture to manufacturers. In environments where thousands of variables affect the bottom line, businesses can now automatically and perpetually record machine and performance measurement. Oden Factory Cloud gives customers access to comprehensive data insights and can eliminate reliance on onsite infrastructure investments to run their own analytics.

Because manufacturers have access to live data and can analyze production data quickly, they can troubleshoot and resolve problems in minutes rather than months. Such information helps improve product quality, minimize unplanned downtime, cut costs, and improve profitability.

“With the help of Google Cloud Platform, we are helping our customers to be data-driven, which wasn’t possible before,” adds Willem. “They now understand that data is their most important asset. That allows them to be more innovative and continually improve their production processes.”

Accelerating digital transformation

Digital transformation is what propels businesses and industries forward. Organizations of all sizes—from startups to global enterprises—focus on digital transformation not only to make scaled improvements, but also to drive significant change and fully embrace the digital age. The pandemic has jump started and pushed many organizations into full gear to digitize their business models and transform with increased business agility, resiliency, and velocity, while driving new innovation and business values for the customers.

However, according to the Boston Consulting Group, only about 30% of companies navigate a digital transformation successfully. Many large scale digital transformation programs failed because of lack of clear business priorities, top-down executive sponsorship, or dedicated resources and commitment to see it through.

Laying the foundation for digital transformation success

Digital transformation drives foundational change in how an organization operates, optimizes internal resources, and delivers value to customers; however, this doesn’t just happen overnight. Digital transformation requires a programmatic approach through an incremental yet agile, cost-effective, value-driven, and sustainable strategy to drive successful transformation across the organization.

One of the critical factors foundational to success is Cloud FinOps (Cloud Financial Operations). Cloud FinOps is an operational framework and cultural shift that brings technology, finance, and business together to drive financial accountability and accelerate business value realization through cloud transformation. In the context of Digital Transformation, it requires new ways of working and operating models to drive behaviors and cultural change that foster cross-functional collaboration, drive accountability, provide greater cost transparency, and promote a blameless culture.

Most importantly, Cloud FinOps serves as an enabling function to drive successful digital transformation programs and enable business agility by breaking down the boundaries between technology, finance, and business teams. Through this cross-functional team collaboration, technology leaders partner with finance and business leaders to better understand the technology investments to create sustainable business outcomes. By doing so, business priorities become more clear and the focus shifts to value creation, customer-centricity, and innovation.

As such, companies are reinventing their business models to fund value streams and connect cloud technology investments to strategic business outcomes. With the increased visibility of the cloud costs, finance teams are also gaining greater accuracy in tracking cloud spend against budgets. Organizations can align the TCO of the technology services to the value metrics to make better informed future investment decisions and forecast demand.

Cloud FinOps to accelerate business value realization

The successful deployment and implementation of Cloud FinOps building blocks will enable organizations to accelerate digital transformation beyond cost savings, including the ability to:

• Accelerate business value realization and innovation
• Drive financial accountability and visibility
• Optimize cloud usage and cost efficiency
• Enable cross organizational trust and collaboration
• Prevent cloud spend sprawl
• Break down of departmental silos

Organizations that are successful in digital transformation most often have established processes to measure and track business value. One of the key building blocks of Cloud FinOps is “Measurement & Realization.” By establishing a robust value measurement approach to track and monitor the business value metrics toward business goals, we are bringing technology, finance, and business leaders together through the discipline of Cloud FinOps to show how digital transformation is enabling the organization to create new innovative capabilities and generate top-line revenue.

Business value metrics fall across several factors: cost efficiency, resiliency, velocity, innovation, and sustainability. We suggest assigning KPIs to the following metric categories:

Cost efficiency: Measure cost efficiency through infrastructure savings, migration, and support costs. Customers will commonly start with metrics such as cost of compute and storage per day-week-month, and evolve to unit metrics such as cost per customer served or cost per transaction, where the cost of an application stack is aligned to customer drivers.

Resiliency: Enhance operational resiliency with improvement in service quality and security risk posture. Traditional measures such as system service level and the frequency and duration of critical downtime events are effective measures of IT durability. Customers can also augment these metrics by associating a cost per minute of downtime events, reflecting not only the direct impact of these events but opportunity costs as well.

Velocity: Decrease time to market by accelerating fluidity in product and service delivery. By moving to a cloud-based microservices architecture, customers commonly achieve benefits of increasing software release frequency, as well as being able to run many more test scenarios prior to release, resulting in higher quality code. As an example, our recent Google’s State of DevOps Report 2021, shows that elite performers have 973x more frequent code deployment and release frequency than the low performers.

Innovation: Enable a culture of rapid experimentation to drive innovation and cloud transformation. With cloud technology, companies can avoid the financial constraints of fixed cost investments and lengthy procurement lead times. As a result, the marginal cost of experimentation and time from ideation to experimentation can drop significantly while the number of experiments per unit of time can grow dramatically.

Sustainability: Embed true environmental and social sustainability metrics across the organization by adopting a circular economy strategy and building sustainability into everything we do – from running applications on zero net emissions virtual machines to reducing carbon footprint with enhanced productivity and collaboration services. According to Accenture, companies with average on-premise to cloud migrations can drive 65% energy reduction and carbon emission reduction of 84%1.

Getting started

The Cloud FinOps journey starts with defining or updating your metrics. Since business goals and strategic imperatives will likely change over time, it is important to review the Cloud FinOps metrics whenever the goals change. The review of metrics should include the changes in business goals when there are changes in the internal priorities of the team. Executive leaders need to identify dependency relationships between technology and business outcomes to improve the impact of metrics on decision making and to better prioritize and invest in evolving business and technology capabilities. Defining good metrics is not just about aligning to business goals and demonstrating value. It is also important to help prioritize strategic initiatives, guide effective resource allocation, and generate awareness across the organization to drive a shift in mindset with the new way of operating in the cloud.

The pandemic has accelerated the need for companies to modernize their digital capabilities. With technology-driven disruptions across all industries, it has never been more important for organizations to transform themselves, embrace an agile mindset, and make bold investments in cloud technology and capabilities to achieve sustainable business outcomes.

So, where are you now in your cloud FinOps journey, and how do you move beyond the challenges ahead? Google can help you start the conversation and accelerate your path to maximizing business value with the cloud.

No matter where you are on the cloud transformation journey, through an interactive session with Google, we can bring executives across the organization together to work toward a shared vision and a plan to accelerate and realize business value in the cloud. If you are interested in more information, please contact us.

Special thanks to Pathik Sharma, Bruce Warner, Jon Naseath, and Nihar Jhawar for their contributions and sharing their domain expertise to this important Cloud FinOps topic.

In fast-moving organizations, it’s not uncommon for cloud resources, including entire projects, to occasionally be forgotten about. Not only such unattended resources can be difficult to identify, but they also tend to create a lot of headaches for product teams down the road, including unnecessary waste and security risks. 

To help you prune your idle cloud resources, we’re excited to introduce Unattended Project Recommender. It’s a new feature of Active Assist that provides you with a one-stop shop for discovering, reclaiming, and shutting down unattended projects. With actionable and automatic recommendations, you no longer have to worry about wasting money or mitigating security risks presented by your idle resources. Unattended Project Recommender uses machine learning to identify, with a high degree of confidence, projects that are likely abandoned based on API and networking activity, billing, usage of cloud services, and other signals. This feature is available via the Recommender API today, making it easy for you to integrate with your company’s existing workflow management and communication tools, or export results to a BigQuery table for custom analysis.

Thousands of projects can be unattended in large organizations, presenting major security risks

Your cloud projects can go abandoned or unattended for a number of reasons — ranging from a test environment that’s no longer needed, to project cancellation, to project owner switching jobs, and more. Not only can such projects contribute to your cloud bill (waste) but they may contain security issues such as open firewalls or privileged service account keys that attackers can exploit to get a hold of your cloud resources for cryptocurrency mining or, worse, compromise your company’s sensitive data. These security risks tend to grow over time because the latest best practices and patches are usually not applied to unattended projects. 

We experience this issue here at Google, too… In fact, it has been on Google’s internal security team’s radar for some time now, so we joined forces and looked into this problem together, starting with our very own “google.com” organization cloud projects. We quickly found some projects that were unattended, but remediating this issue was easier said than done due to challenges in several areas:

• Detection: With lots of signals available to you via sources like Cloud Monitoring, what are the right ones you should look at (e.g. API, networking, user activity)? How can you tell the difference between an unattended project and a project that has a low level of activity by design (e.g. a “shell” project that holds an auth token)?
• Remediation: Once you have identified a project that seems abandoned, how do you go about ensuring that it’s indeed an unattended project? How do you reduce the risk of deleting something that might be essential to a production workload, causing irreversible data loss? How do you solve this at the scale of your entire organization, beyond a one-time cleanup? 

Over the course of 2021 we built and tested a Google-internal prototype first, cleaning up many of our internal unattended projects, and then worked with a number of Google Cloud customers to build and tune this feature based on real-life data (thank you to all of our early adopters for working with us and your generous feedback that helped us shape this feature!) It was not uncommon for us to come across organizations with thousands of unattended projects, and we’re very excited to bring Unattended Project Recommender to all customers, in public preview.

Discovering and acting on unattended project recommendations

Unattended Project Recommender analyzes usage activity across all projects under your organization, including the following data:

• API activity (e.g. service accounts with authentication activity, API calls consumed)
• Networking activity (ingress and egress)
• Billing activity (e.g. services with billable usage)
• User activity (e.g. active project owners)
• Cloud services usage (e.g. number of active VMs, BigQuery jobs, storage requests)

Based on these signals, it can generate recommendations to clean up projects that have low usage activity (where “low usage” is defined using a machine learning model that ranks projects in your organization by level of usage), or recommendations to reclaim projects that have high usage activity but no active project owners. Here’s what an example post-processed summary list of recommendations can look like for the “foobar” organization that has 3 projects:

  Project ID: demo-project-307815
Recommendation: CLEANUP_PROJECT

Project ID: new-project
Recommendation: N/A

Project ID: bobs-playground-project
Recommendation: RECLAIM_PROJECT

In addition to the recommendations, you can also examine the underlying project activity insights that the recommendations are based upon. The insights provide additional information that can be useful for integration with your organization’s existing workflows and automation (e.g. send an auto-generated email or chat message to project owners based on the list provided by the owners field). Here’s an example insight payload:

  content:
  activeAppengineInstanceDailyCount: 0
  activeCloudsqlInstanceDailyCount: 0
  activeGceInstanceDailyCount: 3
  activeServiceAccountDailyCount: 1
  apiClientDailyCount: 18922           // Daily average API calls produced
  bigqueryInflightJobDailyCount: 0
  bigqueryInflightQueryDailyCount: 0
  bigqueryStorageDailyBytes: 0
  bigqueryTableDailyCount: 0
  consumedApiDailyCount: 0             // Daily average API calls consumed
  datastoreApiDailyCount: 0
  gcsObjectDailyCount: 11
  gcsRequestDailyCount: 0
  gcsStorageDailyBytes: 2663548
  hasActiveOauthTokens: false          // OAuth tokens used in the last 180 days
  hasBillingAccount: true
  numActiveUserOwners: 1
  owners:                              // List of project owners
  - activeOnProject: false
    member: user:user1@example.com
  - activeOnProject: true
    member: user:user2@example.com
  serviceWithBillableUsage:
  – Cloud Storage
  - Compute Engine
  vpcEgressDailyBytes: 264456938       // Daily average VPC egress bytes
  vpcIngressDailyBytes: 392435047      // Daily average VPC ingress bytes
  usagePercentile: 20                  // Level of usage relative to other projects

GCP projects are used in many different ways and for many different purposes. In case you get a recommendation to delete a project that’s being used in a way that’s out of the scope for this feature, you can dismiss the recommendation and it will stop showing up for the given project. 

Restoring deleted projects

When you choose to shut down a project using the projects.delete() method, it gets marked for deletion. After a project is marked for deletion, it becomes unusable, all resources within that project are shut down, and a 30-day wait period for the project and all of its data to get fully deleted begins.

In case a useful project is accidentally shut down, you have the option to restore the project within that 30-day wait period. Since restoring allows you to recover most but not necessarily all of your project data and resources, we recommend carefully examining the utilization insights associated with a project and considering any additional utilization signals that may not be captured by the Unattended Project Recommender before taking the cleanup action.

Early customer success stories

A number of enterprise customers are already using Unattended Project Recommender to keep their organizations clean of unattended projects and resources.

Decathlon, a French sporting goods retailer, is excited for the insight Unattended Project Recommender will bring to their environment, and are already deploying it as a part of their latest cloud security initiatives.

“After a thorough test of this feature and the validation of our CISO, we ended up deleting our first 775 projects, and no one complained! A great help to improve our security. The next step for us will be to operationalize it at scale, and implement a company wide policy for unattended resource management.” —Adeline Villette, Cloud Security Officer

For Veolia, one of the world’s largest water, waste and energy management companies, not only does this feature reduce security risks and waste, but also helps drive cultural shift and alignment with its ecological transformation strategy.

“This feature allows us to reduce our costs and security debt on assets that are no longer in use, and is also fully in line with Veolia’s philosophy of limiting its carbon footprint. After having tested Unattended Project Recommender on more than 3,000 projects throughout our organization, we are looking to bring it as proactive alerts to our project owners at scale.”—Thomas Meriadec, Product Manager

Box, a secure cloud content management provider, views it as a foundation for building a repeatable process to remediate unused resources.

“Unattended Project Recommender is a great fit for us. It gives us a unified view of project usage across our entire organization and enables us to address security risks of legacy projects in a systematic and organized manner, ensuring an even safer environment.” —Matt Bowes, Staff Security Engineer

Getting started with the Unattended Project Recommender

To help you get started, we’ve prepared a Cloud Shell tutorial (source code) that you can use to find unattended project recommendations within your own Projects/Folders/Organization. Click this button to clone the tutorial from GitHub and run in your Cloud Shell environment:

As you can see, listing recommendations for your projects only takes a few clicks with the tutorial (special thanks to Lanre Ogunmola, Security & Compliance Specialist, for making this look so easy)! For additional detail on using the gcloud CLI or API to discover unattended project recommendations, please refer to the documentation page.

You can also automatically export all recommendations from your Organization to BigQuery and then investigate the recommendations with DataStudio or Looker, or use Connected Sheets that let you use Google Workspace Sheets to interact with the data stored in BigQuery without having to write SQL queries.

As with any other Recommender, you can choose to opt out of data processing at any time by disabling the appropriate data groups in the Transparency & control tab under Privacy & Security settings.

We hope that you can leverage Unattended Project Recommender to improve your cloud security posture and reduce cost, and can’t wait to hear your feedback and thoughts about this feature! Please feel free to reach us at active-assist-feedback@google.com and we also invite you to sign up for our Active Assist Trusted Tester Group if you would like to get early access to the newest features as they are developed.

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.