New locations in Eventarc

Back in August, we announced more Eventarc locations (17 new regions, as well as 6 new dual-region and multi-region locations to be precise). This takes the total number of locations in Eventarc to more than 30. You can see the full list in the Eventarc locations page or by running gcloud eventarc locations list . 

What does location mean in Eventarc?

An Eventarc location usually refers to the single region that the Eventarc trigger gets created in. However, depending on the trigger type, the location can be more than a single region:

• Pub/Sub triggers only support single-region locations.
• Cloud Storage triggers support single-region, dual-region, and multi-region locations.
• Cloud Audit Logs triggers support single-region locations and the special global region.

Before looking into trigger location in more detail, let’s look at other locations relevant in Eventarc.

What other locations are relevant in Eventarc?

Triggers connect event sources to event targets:

Each event source, event target, and trigger has its own location. Sometimes, these locations have to match and sometimes they can be different.  

Here’s an example of a trigger connecting Cloud Storage events from a bucket in the europe-west1 region to a Cloud Run service in the us-central1 region with a trigger located in the europe-west1 region:

  gcloud eventarc triggers create trigger-storage \
  --destination-run-service=hello \
  --destination-run-region=us-central1 \
  --location=europe-west1 \
  --event-filters="type=google.cloud.storage.object.v1.finalized" \
  --event-filters="bucket=my-bucket-in-europe-west1-region" \
  --service-account=$PROJECT_NUMBER-compute@developer.gserviceaccount.com

In many cases, you don’t have control over the location of the event source. In the example above, the Cloud Storage bucket is in the europe-west1 region. That’s the location that you need to work with and it has implications for the trigger location (which I’ll get to later). 

The location of the event target is the region of the service where you want the events to go. You get to choose this from one of the supported regions when you deploy your Cloud Run service. You typically want this to be in the same region as your event source for latency and data locality reasons (but this is not strictly a requirement). In the example above, the event source (bucket) is in europe-west1 but the event target (Cloud Run service) is in  us-central1 as specified by the --destination-run-region flag. 

The location of the trigger is dictated by the event source location, but the trigger type also comes into play. It is specified by the –location flag. Let’s take a look at the trigger location for each trigger type in more detail.

Location in Pub/Sub triggers

In a Pub/Sub trigger, you connect a Pub/Sub topic to an event target. Pub/Sub topics are global and not tied to a single region. However, when you create a Pub/Sub trigger, you need to specify a region for it (because Eventarc triggers need to live in a region) with the --location flag as follows:

  gcloud eventarc triggers create trigger-pubsub \
  --destination-run-service=hello \
  --destination-run-region=us-central1 \
  --location=us-central1 \
  --event-filters="type=google.cloud.pubsub.topic.v1.messagePublished" \
  --transport-topic=projects/your-projectid/topics/your-topic

By specifying a location, Eventarc automatically configures the geofencing feature in Pub/Sub such that events only persist in the specified location. As I noted above, you typically want to (but are not required to) choose the same region for the trigger and the Cloud Run service for lower latency and data locality. You can also use regional Pub/Sub service endpoints to publish to the topic to ensure that all of the data stays in a single region. 

Location in Cloud Storage triggers

In a Cloud Storage trigger, you connect a Cloud Storage bucket to an event target. A Cloud Storage bucket can be in a single-region (e.g. europe-west1), dual-region (e.g. eur4), or multi-region (e.g. eu) location. The location of the bucket dictates the location of the trigger and they have to match. The earlier trigger example was for a bucket in the  europe-west1 single-region location. Here’s another trigger connecting Cloud Storage events from a bucket in the eu multi-region location. Notice how the location flag matches the bucket region:

  gcloud eventarc triggers create trigger-storage \
  --destination-run-service=hello \
  --destination-run-region=us-central1 \
  --location=eu \
  --event-filters="type=google.cloud.storage.object.v1.finalized" \
  --event-filters="bucket=my-bucket-in-eu-multi-region" \
  --service-account=$PROJECT_NUMBER-compute@developer.gserviceaccount.com

If the bucket region and the trigger region do not match, you’ll see an error:

  ERROR: (gcloud.eventarc.triggers.create) INVALID_ARGUMENT: The request was invalid: Bucket "my-bucket-in-eu-multi-region" location "eu" does not match trigger location "europe-west1". Try again by creating the trigger in "eu".

Location in Cloud Audit Logs triggers

In a Cloud Audit Logs trigger, you connect any event source that emits Audit Logs to an event target. The location of the event source will dictate the trigger location. This is typically a single region but there is a special global region that’s necessary in some cases. 

For example, if you want to read Cloud Storage events from a bucket in the europe-west1 region with an Audit Logs trigger, you will create the trigger with the same location. Note that this will match all buckets in the europe-west1 region as there’s no filter by bucket in Audit Logs:

  gcloud eventarc triggers create trigger-auditlog \
  --destination-run-service=hello \
  --destination-run-region=us-central1 \
  --location=europe-west1 \
  --event-filters="type=google.cloud.audit.log.v1.written" \
  --event-filters="serviceName=storage.googleapis.com" \
  --event-filters="methodName=storage.objects.create" \
  --service-account=$PROJECT_NUMBER-compute@developer.gserviceaccount.com

On the other hand, if you want to match a dual-region or a multi-region bucket such as eu, you will create the trigger with the global location as Audit Logs triggers only support a single or global region. Note that this will match all buckets in all regions globally:

  gcloud eventarc triggers create trigger-storage \
  --destination-run-service=hello \
  --destination-run-region=us-central1 \
  --location=global \
  --event-filters="type=google.cloud.storage.object.v1.finalized" \
  --event-filters="bucket=my-bucket-in-europe-west1-region" \
  --service-account=$PROJECT_NUMBER-compute@developer.gserviceaccount.com

As you can see from this example, if you want to read Cloud Storage events, the native Cloud Storage trigger is a much better option, but this example illustrates a typical case in which a global Audit Log trigger is necessary. 

That wraps up this closer look at locations in Eventarc. Feel free to reach out to me on Twitter @meteatamel for any questions or feedback.

EyecareLive transforms the healthcare ecosystem with Enhanced Support, a support service from the Google Cloud Customer Care portfolio.

Telemedicine is now mainstream. It exploded during the COVID-19 pandemic. A 2022 survey by Jones Lang Lasalle (registration required) found that 38% of U.S. patients were using some form of telemedicine. This number is expected to grow as consumers are demanding more convenient and immediate access to care, and doctors are seeking efficiencies, cost savings, and to forge closer relationships with patients.

But because the eye-care field is so heavily regulated, optometrists and ophthalmologists face more technical hurdles to perform telemedicine than their peers in other medical practices.

To join the telemedicine revolution, a generic technology solution wouldn’t do. Eye-care professionals need a more carefully architected and rigorously secure platform – one that ensures a very high degree of compliance and privacy.

EyecareLive provides exactly that. Their comprehensive cloud-based solution was built specifically for eye-care telemedicine practices. They not only facilitate telemedicine visits with patients via video, but help providers stay in compliance with complex industry regulations.

What’s more, EyecareLive is the only platform in the industry that conducts vision screening using Food and Drug Administration (FDA)-registered tests to check a patient’s vision before connecting them to a doctor through a video call. The doctor can thus triage any issues immediately and quickly determine the right next steps for proper care. In addition, their platform digitally connects optometrists and ophthalmologists to the entire eye-care ecosystem, including other doctors for referrals, insurance companies, hospitals, pharmaceutical firms, pharmacies, and, of course, patients.

On top of all of this, the automated back office for their eye-care practices processes electronic health records (EHRs), clinical workflow, billing, coding, and more into one platform. EyecareLive streamlines operations and frees up doctors to focus on delivering the highest possible eye healthcare and on building stronger relationships with patients.

“Considering the number of plug-and-play services that Google has built into the Google Cloud Healthcare solutions, Google is basically supporting the entire healthcare industry from an infrastructure provider point of view.” — Raj Ramchandani, CEO, EyecareLive

Seeking greater agility, EyecareLive migrated to Google Cloud

EyecareLive is truly cloud first. They had operated entirely in the AWS cloud since opening their doors in 2017. Several years in, they decided to look for an additional cloud provider with broader support for digital health platforms. They specifically wanted to migrate to one they could rely on to deliver plug-and-play services, which would accelerate innovation of their platform. Rather than re-architecting for a new cloud, EyecareLive wanted a cloud platform that would offer compatible services they could use to meet their needs for reliability and availability.

“If we want to deploy a new conversational bot or build AI models that assist doctors to diagnose based on a retina image, Google Cloud provides these services which are reliable and tested by Google Cloud Healthcare solutions in many cases.” — Raj Ramchandani, CEO, EyecareLive

Versatility was another requirement. The EyecareLive platform must fulfill the demands of a variety of organizations — doctors, pharmaceutical companies, clinics, and others. EyecareLive also has an international deployment strategy that goes far beyond offering a domestic telehealth solution. Therefore EyecareLive needed a cloud functionality that extended into the broader global eye-care ecosystem.

EyecareLive chose Google Cloud. The most compelling reason was the deep industry expertise found in Google Cloud for healthcare and life sciences. This distinguished Google Cloud from all other possible cloud providers considered by EyecareLive. “We like Google Cloud because of the differentiations such as Google Cloud Healthcare solutions, computer vision, and AI models that can be used out of the box,” says Raj Ramchandani, CEO of EyecareLive. “We found these features more robust for our use cases on Google Cloud than any other.”

“Google is heavily into its Healthcare Cloud. That’s what differentiates it. We love that part because we can tap into innovative healthcare cloud functionality quickly.” — Raj Ramchandani, CEO, EyecareLive

Key to production deployment (and beyond): Google Cloud Enhanced Support

As a cloud-born company, EyecareLive had an exceedingly tech-savvy team. But the migration was a complex one that involved migrating third-party software and networking products that were tightly integrated into EyecareLive’s own code. The team knew it needed expert help with the migration. What’s more, doctors, patients, and other users required 24/7 access to the platform, and any interruptions to availability or infrastructure hiccups during the migration would disrupt their online experiences. However, the EyecareLive team was already stretched by continuing to grow and innovate the business, so they asked Google Cloud for help.

EyecareLive purchased Enhanced Support, a support service offered by the Google Cloud Customer Care portfolio. Specifically designed for small and midsized businesses (SMBs). Enhanced Support gave EyecareLive unlimited, fast access to expert support from a team of experienced Google Cloud engineers during the intricate, multifaceted migration.

“It was my top priority to engage Google Cloud Customer Care to help us keep the platform always available for our doctors and users,” says Ramchandani. “The level of detail to the answers, the clarifications of having the Enhanced Support experts tell us to do it a certain way has been enormously helpful.”

For example, one of the valuable features delivered by Enhanced Support is Third-Party Technology Support, which gives EyecareLive access to experts with specialized knowledge of third-party technologies, such as networking, MongoDB, and infrastructure. This meant all components in EyecareLive’s infrastructure could be seamlessly migrated to Google Cloud, and afterward EyecareLive could lean on Enhanced Support experts to continue to troubleshoot and mitigate issues as necessary.

“The response times to the questions and issues we had when going live was fantastic. It was the best experience with a tech vendor we’ve had in a long time.” — Raj Ramchandani, CEO, EyecareLive

With Enhanced Support at their side, EyecareLive was able to get up and running quickly in preparation for their international expansion by using Google Cloud’s prebuilt AI models, load balancers, and networking technologies that were designed to be easily deployed across multiple regions throughout the globe. “We know exactly how to implement data locality to scale our deployment into different regions and into different countries, because we’ve learned that from the Google Cloud support team.” — Raj Ramchandani, CEO, EyecareLive

EyecareLive then proceeded to rapidly scale their business, knowing that Google Cloud would ensure they could meet compliance standards in whatever country or region they expanded into.

“Since we’ve moved to Google Cloud and chose Enhanced Support, we’ve had 100% availability. That’s zero downtime, which is incredible.” — Raj Ramchandani, CEO, EyecareLive

Enhanced Support also provided the capabilities for EyecareLive to:

• Resolve issues and minimize any unplanned downtime to maintain a high-quality, secure experience for doctors and patients during and after migration
• Acquire fast responses to questions from technical support experts
• Learn from guidance from the Enhanced Support team beyond immediate technical issues

EyecareLive builds momentum toward their vision for eye-care telemedicine

By working closely with the Google Cloud Enhanced Support team, EyecareLive was able to successfully migrate their platform.

“If you ask any of my engineers which cloud provider they prefer, they’d all respond ‘Google Cloud,’” says Ramchandani. “The documentation is there, the sample code is there, everything that we need to get started is available.”

EyecareLive was then able to go on to grow and scale their business in the cloud in the following ways:

• Successfully managed a complex migration with minimal disruption and maximum availability, ensuring a consistent, secure, and compliant-ready experience for doctors and patients
• Gained the trust of both doctors and patients – they know that EyecareLive protects their sensitive medical data
• Kept EyecareLive agile and focused on innovating forward rather than building new features from scratch by supporting the team as they took advantage of Google’s tailored, plug-and-play technologies
• Analyzed performance over time to plan for future growth by partnering with Enhanced Support for the long term

“We know we can rely on Google Cloud from a security point of view. We love the fact that Google Cloud Healthcare solution is HIPAA compliant. Those are the things that make us trust Google to do the right thing.” — Raj Ramchandani, CEO, EyecareLive

With Enhanced Support, EyecareLive sees a bright future in the cloud

With the help of Enhanced Support, EyecareLive brings digital transformation to the eye-care in the healthcare industry by integrating the entire ecosystem of eye-care partners onto one platform making EyecareLive a leader in their industry.

Learn more about Google Cloud Customer Care services and sign up today.

Value of Establishing a Baseline for Metrics

As organizations continue to leverage cloud investments to drive their business growth and top line revenue, business, finance, and technology executives need to become increasingly connected in their efforts to deliver strong business outcomes.  More than ever before, executives need to quantify the value of their investments in business and technology capabilities.  As such, business and IT leaders need a set of value metrics that cover both operational and strategic outcomes, as well as risks and opportunities.  Nevertheless, operational IT metrics are often disconnected from business outcomes, and executives need to establish the connection between technology and business outcomes to facilitate a meaningful dialogue between IT and business leaders.

Like many aspects of IT operations, metrics and KPIs are commonly a journey.  Organizations typically start this journey with unit metrics focusing on cloud costs and eventually progress toward a set of clearly defined business value metrics.

As we define the set of metrics across the five key building blocks of Cloud FinOps, which include Accountability & Enablement, Measurement & Realization, Cost Optimization, Planning & Forecasting, and Tools & Accelerators, we ensure that these metrics are easily measurable and commonly attainable across the organizations that are on the journey of digital transformation. 

Accountability and Enablement Metric

The Accountability and Enablement pillar is foundational to building a culture of cost and value awareness and charts the course for both the process and cultural transformation journey in cloud FinOps.  The primary goal is to help drive financial accountability and accelerate business value realization by streamlining IT financial processes and enabling frictionless cloud governance.  Enablement empowers IT, finance, and business teams with training to better understand cloud resources and strategies to efficiently deploy and manage them.  Driving accountability and enablement starts with a charter and core governance policies, and then guides the transformation of processes that link finance, IT, and business owners. 

We recommend adopting Cloud Enablement % as the standard metric for the accountability and enablement pillar, measured by the # of business leaders trained and certified / total # of business leaders in the organization.

This is an important metric as many organizations fail to adopt Cloud FinOps because of lack of awareness and training. This cloud enablement metric will help business leaders better understand the value of cloud and how it can be an enabler to drive sustainable business outcomes. 

The cloud enablement metric can easily be implemented through a set goal based on the number of identified business leaders across the organization. With that said, it is important to utilize the Pareto principle of 80/20 rule here and identifying the key business leaders who are extensively consuming services on the cloud should be the primary focus. Google Cloud recently published a new Cloud Digital Leader certification that is aimed for business leaders and executives. By obtaining the Cloud Digital Leader certification, it ensures the individual is well-versed in basic cloud concepts and can demonstrate a broad application of cloud computing knowledge in a variety of applications and how Google Cloud services can help achieve desired business goals. In addition, the FinOps Foundation also provides training and certification to practitioners in a large variety of cloud, finance and technology roles to validate their FinOps knowledge and enhance their professional credibility.

Ultimately, we see that a target goal of over 70% of business leaders achieving the Cloud Digital Leader certification can significantly drive alignment and adoption of Cloud FinOps across the organization and leverage cloud technologies as an enabler to create sustainable business outcomes.

Measurement and Realization Metric 

Foundational to any good process is accurate data and effective metrics, which starts with the notion of cloud costs visibility and traceability. This is driven by proper resource hierarchy and project structure standards and supported by a labeling and tagging data architecture behind your organization’s use of cloud resources.  While many common tags include IT-driven designators such as application, environment, and project, it is important to design a direct connection to your P&L into your labeling and tagging architecture, by including cost centers or the chart of accounts as tags.  Furthermore, automation of tagging ensures that all taggable resources are deployed with consistent and accurate labels and feed FinOps metrics with reliable data.

Establishing consistent and detailed tagging is essential to attributing cloud resources not only to specific products and projects, but also to detailed cost centers aligned with lines of business and associated P&Ls.  In order to establish a full chargeback of typical cloud services, customers will need to attribute costs associated with 3 types of cloud resources.  The first and most straightforward will be attributing taggable resources (compute instances, databases, and storage buckets) that are aligned to a specific P&L, such as where a given application is solely consumed by one line of business.  

The second situation is where taggable resources are shared across multiple lines of business.  Many customers will resort to using traditional P&L allocation models, such as using business revenue or headcount of the associated business units to divy up the costs.  In order to more accurately allocate shared application costs, leading-edge customers use elements in their cloud microservices architecture, such as API calls, to specifically measure the relative consumption of shared applications.  

The third type of cloud resources are those that cannot be tagged.  Common examples include support, networking costs, and third party Marketplace costs.  Here, traditional P&L allocation models as described above (using headcount or revenue) are commonly used.  Some customers will use the relative distribution of their taggable resource allocations to appropriate non-taggable costs to their business units, while some types of costs, such as networking, are allocated based on API calls.

To measure the effectiveness of the Measurement & Realization pillar of cloud FinOps across these three types of cloud resources, we recommend adopting Cloud Allocation % as the lead metric.  This metric is measured as the percentage of total cloud costs (taggable resources consumed by individual business units, taggable resources shared across multiple business units, and non-taggable resources) allocated to responsible business owners.

This metric can be used to support both Showback (cloud costs held in a central IT P&L but reported to business units) and Chargeback models (cloud costs fully charged to business unit P&Ls), and reflects the underlying effectiveness and accuracy of resource tagging and cost attribution to business units.  Cloud Allocation % can be implemented in two ways.  The basic implementation would qualify costs apportioned by any P&L metric (either by consumption or by traditional P&L allocation such as by revenue or headcount).  The more advanced implementation of this metric would only qualify those resources (both specific and shared) that use either tagging or API calls to measure consumption and attribute associated costs to business units.

Customers evolving from a Crawl to a Walk stage of implementation will seek to allocate 70% or more of their total cloud costs, while those moving to a Run state will achieve 90% or greater cost attribution based on direct consumption measures.

Cost Optimization Metric

Cloud cost optimization is not just about cutting costs—it’s about knowing where to spend your money to maximize the business value. It is an iterative and continuous process that provides a consistent methodology to visualize and manage cloud consumption in a most cost effective way.  Success in cost optimization can result not only in significant reductions of cloud spend, but sometimes also in improved application performance to manage higher traffic (user requests per seconds or transaction processed) within the same cost envelope. 

It is important for an organization to automate reports generated by ingesting billing usage and cost data as well as recommendations generated for optimizations. These optimizations reflect the potential savings (also known as unrealized savings) which allows the team to prioritize implementations to realize the cost savings. 

Typically potential savings contains adoption of:

• Pricing optimizations like Committed Use Discounts (resource-based and spend-based), BigQuery reservations, etc.
• Resource optimizations of wasteful resources (including aged snapshots, idle instances, and over-sized databases) that don’t provide any business value.

Capturing this metric is important as it allows the organization to keep a pulse on inefficiencies that exist in the organization and allows businesses to focus on achieving cost savings thereby capturing true value of running their workloads in the cloud.

The cost optimization metric can be implemented by integrating Recommendation Hub in your FinOps workflows. Recommendations Hub is part of Active Assist that contains a portfolio of intelligent tools and capabilities to help you optimize your workloads with minimal effort. It surfaces a summary of all recommendations across your projects along with potential cost savings ($) so you can prioritize your cost optimization effort. We have seen customers realize savings by taking action on recommendations generated by idle VM recommender, Committed Use Discount recommender, VM machine type recommender and many more.

Ultimately we see customers achieving realized savings of over 90% on total cloud service optimizable. We have seen customers reinvest these savings into creating differentiated products and offerings and improving their customer experience, thus accelerating business value realization from the cloud.

Planning and Forecasting Metric

Financial planning is a foundational capability within finance organizations that will directly influence each company’s capabilities of cloud computing forecast accuracy. Financial planning focuses on accurately forecasting financial metrics that are set on an annual basis to guide the company’s financial objectives. The annual plans are measured on a quarterly basis and adjusted based on performance throughout the year; the forecast performance is monitored on a monthly basis to help influence operational results.

Planning and forecasting cloud computing costs is typically the responsibility of the team responsible for cloud operations. Operational forecast planning is based on consumption workload plans, historical trajectory, seasonality and leading indicators. Transformational projects also create material risks to forecast accuracy. 

Establishing accurate financial forecasting in the cloud spend requires rethinking traditional approaches to asset depreciation run-outs and trend-based forecasting of maintenance and licensing costs. Using workload-specific forecasting models that leverage a combination of trend-based models for steady-state workloads, driver-based models for scaling applications, as well as monthly variance analysis can greatly improve the accuracy of dynamic cloud needs.

Capturing and measuring forecast accuracy enables companies to understand if they do what they plan. Companies get what they measure and so by measuring and discussing variances to forecast accuracy it enables better control of cloud spend allocations. 

Cloud computing forecast accuracy should be included as a topic that Finance and Cloud operations teams discuss at least monthly. The cloud operations team should monitor forecast trajectory during the month and evaluate adjustments when they identify unexpected shifts.

An effective forecast accuracy is one that avoids surprises to company executives and investors. Cloud computing often has more variability and seasonality than depreciation of capex from on prem environments. Coordinating project and sprint agile management can help avoid surprises. If a development change creates an unexpected jump in spending then change management processes should be reviewed to avoid future surprises.

Tools and Accelerators Metric

Employing proper tools and accelerators are important to fully benefiting from FinOps practices. In earlier stages, companies may have limited their ability to report detailed analysis of cloud spend. As practices mature and improve, labeling and tagging of resources proves valuable to understanding costs for specific projects/teams and for building unit cost metrics. 

These capabilities can become even more powerful through automated monitoring of resources that offers insights on spend, value, compliance and recommendations.  

Therefore the recommended measure of Tools & Accelerators maturity is to evaluate the # of automated recommendations that have been implemented as a % of total list of automated recommendations generated that results in cost savings

This is an important metric because as the organization onboards newer workloads to the Cloud environment, lack of robust actionable recommendations and monitoring can lead to increased cloud waste. This has been a key component prohibiting organizations from realizing the total value of their cloud investment.

Customers starting on their tool maturity journey can leverage Google’s out of the box recommendations Hub to get started. The Recommendation Hub is a place in the Google Cloud Console where you can view, prioritize, and apply these recommendations.  Some examples include VM right sizing recommendations, BQ slot optimizations, Committed use Discount etc, Idle resource recommendations. This can further be integrated into any existing enterprise tooling using the recommendations API. As organizations mature, they can leverage Cloud Monitoring to create advanced recommendations based on custom business logic.

Ultimately, we see that a target goal of over 50% of automated recommendations implemented as the tooling for surfacing recommendations matures and this will ensure that the organization can minimize and eliminate cloud waste to maximize value from cloud investment. 

Bringing this together with a Cloud FinOps Dashboard

As technology and business goals continue to evolve over time, it is essential to establish a process where the Cloud FinOps metrics are continuously reviewed whenever the goals change. Furthermore, it is important to note that not all organizations need to achieve the “Run” state of the identified metrics target. The metrics are means to achieve the business outcomes based on the organization’s priorities. By collaborating with cross-functional teams to quantify and measure the impact of the Cloud FinOps metrics, executive leaders can quickly obtain buy-in, highlight common-shared goals, and move fast. 

At Google Cloud, we have developed solutions to help our customers build a Cloud FinOps Dashboard to capture these metrics to drive a culture of change and equip the transformation and business leaders with the tools to share and track the results of the key metrics. Successful adoption of the Cloud FinOps metrics enable organizations to focus on the business outcomes and the dashboard provides a meaningful feedback loop to report on the impact and drive visibility across the organization.

So, where are you now in your 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 Daniel Pettibone, Amitai Rottem, Bruce Warner, Jon Naseath, and Nihar Jhawar for co-authoring and contributing to this blog post and the members of the FinOps Foundation including J.R. Storment, Vas Markanastasakis, Anders Hagman, John McLoughlin, Mike Bradbury, and Rich Hoyer for providing their domain expertise and continuous support to this important cloud FinOps topic.}

There’s never been a better time to talk about multicloud, and the Google Cloud Multicloud Mindset series on Twitter Spaces was created to do just that! This series takes place once every two weeks and features live conversations with top experts about the latest multicloud topics. You can join the 15-minute Q&A to ask your top questions and listen to episodes later offline for up to 30 days after we chat.

If you happened to miss our last few episodes, we recommend checking out our introduction blog to the series for what you missed. Let’s dive into our latest episodes, discussing the impact of open source and novel security challenges in multicloud environments.

Episode #5: ‘The intersection of open source and multicloud’

Open source technology has been an integral part of computing since its earliest era, predating even the birth of technology hubs like Silicon Valley. Open source projects have been responsible for giving us some of the most popular software in the world, such as Mozilla Firefox and the operating system Linux.

In the fifth episode, we sat down with Mike Coleman, Cloud Developer Advocate at Google Cloud, and took a closer look into the history of open source technologies, the role they play in a multicloud world, and the developer perspective on using these technologies to do their work.

The concept of multicloud anchors on the ability to run workloads across clouds and being able to pick the providers that are best suited for specific parts of workloads. Adopting open source technologies and languages empower companies to use the tools they need, regardless of cloud provider, without the fear of getting locked into a specific provider.

“As you think about moving across different environments, whether that be cloud to cloud, or developer desktop to ultimate destination, whether that be your data center or the cloud. Open source software allows you to do that…and multicloud is just an extension of that. This idea that I need to run the same software wherever I go.” — Mike Coleman, Cloud Developer Advocate at Google Cloud

If you’ve ever wanted a developer’s take on the impact of multicloud and the influence of open source in software development and digital transformation trends, you’ll want to tune into this episode.

You can access the full conversation on Twitter Spaces.

Episode #6: ‘Novel challenges in security with multicloud’

In the sixth episode of the series, we chatted with Dr. Anton Chuvakin, Security Advisor at Office of the CISO at Google Cloud, about how security leaders and architects are shifting away from traditional security models, which are increasingly insufficient for multicloud environments.

As more organizations adopt multicloud approaches, the question of how to maintain security in these complex environments and the increasing burden on SecOps teams is top of mind. As Dr. Chuvakin noted, the challenges in the cloud facing more traditional teams range from types of telemetry and logs to volumes and lack of clarity on detection use cases. However, these issues intensify when extended to include multiple clouds, where learning how to do something on one provider may be completely different on another.

“If you end up multicloud, you need to know public cloud and how it works at a better level than you would if you’re going to a single provider. Just like if you’re trying to repair three cars, you need to first learn how to repair cars. You need to have more cloud knowledge to do multicloud, not less. You need to have more powerful superpowers in the public cloud computing area because you can’t just learn one provider and call it a day.” — Dr. Anton Chuvakin, Security Advisor at Office of the CISO at Google Cloud

During the discussion, he offered three tips for tackling multicloud security:

1. Learn cloud more, not less if you’re going multicloud. Multicloud requires more cloud knowledge because you can’t learn a single provider and call it a day. You’ll need to understand the differences in order to be able to secure multiple cloud environments.
2. Focus on learning cloud identity management and how it compares to your traditional identity management service functions. Start with identifying the differences and similarities in what you see in one cloud and then continue with other clouds you use.
3. Explore where your threat areas change in cloud environments when you plan detection and response activities to understand if your detection is covered across clouds.

If your organization is embracing multicloud, this is a great episode to listen and learn more about cloud security, the primary considerations and challenges facing security teams, and some helpful best practices for thinking about security in multicloud environments.

We’ll be sharing the latest topics and episodes with you every month in this blog series. Until next time.

As retailers strive to meet the growing expectations of shoppers, they are turning to Google Cloud to transform their businesses and tackle opportunities in an increasingly challenging industry. From optimizing inventory management to increasing collaboration between employees across locations and roles, to helping build omnichannel experiences for their customers, we are working together with retailers to help make the shopping experience as seamless and personalized as possible.  

A standout Google Cloud customer is Macy’s, one of the world’s largest retailers. Founded in 1858, Macy’s operates approximately 680 Macy’s and Bloomingdale’s, and 190 specialty stores including Bloomingdale’s The Outlet, Bluemercury and Macy’s Backstage. And through macys.com, bloomingdales.com, and bluemercury.com, it also serves millions of customers across more than 100 countries. 

By moving its infrastructure to the cloud, and taking advantage of Google Cloud data warehousing and analytics solutions, Macy’s is streamlining retail operational functions across its network.

With the opening of its new approximately 675,000 square-foot distribution center in Columbus, Ohio, Macy’s is leveraging the scalability of Google Cloud to ensure that merchandise is accurately and efficiently received, sorted, ticketed, picked, packed and shipped from the distribution center to the stores—even during peak retail seasons like back to school and the holidays.

“Powered by software developed at Macy’s technology, this new distribution center is a fantastic first step in our cloud journey. Working with Google Cloud allows us to be more nimble, efficient and flexible in how we utilize our warehouses,” 

Naveen Krishna, CTO, Macy’s

Leveraging Google Cloud’s data management and analytics solutions, Macy’s new warehouse management system will initially service 200+ Macy’s Backstage off-price stores at launch. Macy’s will begin rolling out this software solution to additional distribution centers that service its nationwide fleet of Macy’s and Bloomingdale’s department stores, as well as Macys.com and Bloomingdales.com direct-to-customer orders. 

Our continued work with Macy’s reflects their investment in technology to improve digital and mobile experiences, site stability, store technology, fulfillment, and logistics, and integrate its front line and back office to reinvent retail. I look forward to deepening our partnership with Naveen and his team to help them achieve these goals.