Efficient, Safe and Dynamic Gaming Experience: Aristocrat's Digital Journey on Google Cloud - Build What's Next
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Efficient, Safe and Dynamic Gaming Experience: Aristocrat’s Digital Journey on Google Cloud

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Gaming company and its subsidiaries tapped into new markets and new users which required centralized platform to monitor data and application security across systems. Google Cloud and Splunk addressed this requirement and ups the gaming experiences!

Since Aristocrat’s founding in 1953, technology has constantly transformed gaming and the digital demands on our gaming business are a far cry from challenges we faced when we started. As we continue to expand globally, security and compliance are top priorities.

Managing IT security for several gaming subsidiaries and our core business became more complex as we entered into new markets and scaled up our number of users. We needed a centralized platform that could give us full visibility into all of our systems and efficient monitoring capabilities to keep data and applications secure. We also needed the ability to secure our systems without compromising user experiences.

We turned to Google Cloud and Splunk to better manage complexity and support highly efficient, secure, and more dynamic gaming experiences for everyone. We are committed to using today’s modern technologies to give players more optimal experiences.

Bringing our digital footprint into the cloud


When we set out on our digital transformation, we looked to address many business requirements.

These requirements included:

  • Regulation: We wanted a platform that could efficiently address our industry’s stringent and global regulatory compliance requirements.
  • Player experience: Our IT environment must support smooth gaming experiences to keep users engaged and satisfied.
  • Scalability: As we grow and diversify, meeting the changing demands of an increasingly global gaming community, we need an easily scalable platform to align with our current and future needs.

Google Cloud offered us the perfect foundation through solutions such as Compute Engine, Google Kubernetes Engine, BigQuery, and Google Cloud Storage. These acted as the right infrastructure components for us for the following reasons:

  • Google Cloud is globally accessible and supports compliance, helping to streamline security and regulatory processes for our team.
  • With Google Cloud, we can manage our entire development and delivery processes globally with fast and efficient reconciliation of regional compliance requirements.
  • When we need to adjust existing infrastructure or deliver new capabilities, Google Cloud accelerates the process and takes the heavy lifting off of our team.
  • Google Cloud allows us to support tens of thousands of players on each of our apps while experiencing minimal downtime and low latency. The importance of this support can’t be underestimated in an industry where players have little to no patience if lags in games occur.

We migrated our back-office IT stack alongside our consumer-facing production applications to Google Cloud given our positive experiences with compliance, security, scalability, and process management. This migration has significantly accelerated our digital transformation while streamlining our infrastructure for faster and more cost-effective performance.

In many ways, Google Cloud has been, with maybe a pun intended, a game-changer for us. For instance, when we suddenly had to support a lot of remote work during the COVID-19 pandemic, native identity and access management tools in Google Cloud allowed us to retire costly VPNs used for backend access and quickly adopt a more easily managed, cost-effective zero-trust security posture.

Accessing vital third-party partners and managed services


Aristocrat has many IT needs best addressed in a multi-cloud environment. Google Cloud is particularly attractive given its strong cloud interoperability, as well as the many products and services available on Google Cloud Marketplace. The marketplace accelerated our deployment of key third-party apps including Splunk and Qualys.

Given the personal information we store and the global regulatory compliance statutes we must oblige, security lies at the heart of our business. Splunk is a critical component of our digital transformation because it offers solutions that provide the enhanced monitoring capabilities and visibility we need. The integration between Splunk and Google Cloud gives us confidence that our data is secure. We know our data can be secure in Google Cloud, while simplified billing through Google Cloud Marketplace makes payments and license tracking easier for our procurement team.

As part of our protected environment, we use the Splunk platform as our security information and event management system, leveraging the InfoSec app for Splunk that provides continuous monitoring and advanced threat detection to significantly improve our security.

We can manipulate and present data in Splunk in a way that provides us with a single pane-of-glass for our hybrid, multi-cloud environment and our third-party apps and systems. Splunk observability tools have likewise helped us to track browser-based applications like our online gaming apps to monitor details related to security and performance.

Splunk and Google Cloud have transformed how we operate. We can now quickly ingest and analyze data at scale within our refined approach to security management by offloading software management to Splunk and Google Cloud. This ability enables us to approach security more strategically, and positions us to integrate more AI/ML capabilities into our products for even greater governance and performance.

This is just the beginning of our journey with Splunk and Google Cloud. We’re excited to see the innovation we can continue bringing to the gaming community worldwide.

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Unlocking Economic Potential: Cloud FinOps

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Companies like OpenX help firms derive transformational benefits of the cloud. Experts at Google have imbibed their learning into Cloud FinOps operational framework that gives organizations the financial governance and accountability they need!

Built for a CapEx world, most organizations’ finance systems aren’t set up to take advantage of cloud’s dynamic, OpEx-driven consumption patterns.

Practicing Cloud FinOps can unlock the business value latent in adopting public cloud. 
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It may not be a household name yet, but chances are you’ve crossed paths with OpenX today. OpenX, a leader in programmatic advertising, operates one of the world’s largest ad exchanges, serving over 250 billion ad requests per day, connecting more than 30,000 brands and reaching nearly one billion consumers. To make it happen, in 2019, OpenX migrated entirely out of its data centers and became the first major ad-exchange platform to move completely to the cloud.

The OpenX CTO, Paul Ryan, knew that this cloud transformation initiative had the potential to increase costs faster than its revenues. To be successful, he needed his engineering, finance, and business teams to forge a new “cost-aware” culture, complete with effective cost visibility and controls. In other words, he needed Cloud FinOps — an operational framework and cultural shift that brings technology, finance, and business together to drive financial accountability and realize business benefits through cloud transformation.

Ryan laid out a cloud migration roadmap that included cost governance and controls around project ownership, established cost responsibility with engineering teams to accurately forecast cloud consumption, and challenged developers to lower per-unit costs — while at the same time improving performance, scalability, speed and global reach.

It worked! In just 9 months, OpenX reduced their per-unit cost by over 60%. The framework allowed OpenX to launch new regions in a matter of days, reduce their time to market for new features by over 50%, and complete their migration in record time — seven months! “We are now able to stop worrying about legacy infrastructure and focus more on our growth categories,” said Ryan. “Our tech stack is getting smarter and more sophisticated by the day, and we have the flexibility to scale our infrastructure in real-time as the business scales and evolves.”

Unblocking Cloud’s Potential

Cloud holds the key to a successful digital transformation. In fact, McKinsey forecasts that by 2030, the Fortune 500 alone may realize over $1 trillion of EBITDA value drivers associated with public cloud enablement. But unlike OpenX, many companies struggle to achieve near-term value objectives from their cloud investments. Surveys reflect that more than 30% of cloud spend in 2021 was wasted or inefficient, while upwards of 80% of CIOs have yet to achieve the business benefits of migrating to the cloud.

Traditional IT finance processes are ill-suited for cloud infrastructure: Traditional planning and budgeting processes are challenged to address dynamic consumption patterns and complex migrations. Centralized IT budgets using traditional allocations fail to provide the necessary visibility into sources of cost overruns. CapEx-focused cost controls have little ability to manage largely OpEx-driven spend. Trend-based forecasting often inaccurately predicts cloud costs. And developer teams lack access to cost-aware architecture patterns to deploy the applications more efficiently.

Enter Cloud FinOps

At Google we’ve worked with many companies, like OpenX, to help organizations realize the transformational benefits of the cloud by cultivating a culture of transparency and embedding agile processes to manage costs. We’ve distilled these learnings into a Cloud FinOps operational framework that gives organizations the financial governance and accountability they need to grow their business sustainably.

Building Blocks of FinOps
GOOGLE CLOUD

At a high level, a Cloud FinOps approach depends on five key areas:

  1. Accountability and Enablement

Accountability and enablement aim at instilling a cost-conscious culture across the organization. Oftentimes, this means standing up a cross-functional and dedicated team with members from technology, finance and engineering to establish cloud financial best practices and governance. In various organizations, we’ve seen this through an extension of a Cloud Center of Excellence, a Cloud Business Office or simply a Cloud FinOps team. Enablement focuses on empowering IT, finance and business leaders through training to help them better understand the economics of cloud services and the strategies to efficiently deploy and manage them. Cloud financial training guides teams on how to design cost-effective cloud environments, for example, embracing ”cloud-native” design principles such as auto-scaling/elasticity and Infrastructure as a Code.

  1. Measurement and Business Value Realization

Effective measurements not only create awareness and enable agile processes, but also support a culture that celebrates success and rewards teams for achieving business objectives. As such, measurement in the service of business value realization is about developing a comprehensive set of long-term benefits and cost KPIs to quantify the total net value of the return on digital transformation. Organizations often start with cost-related KPIs and eventually evolve those KPIs into business value metrics that are mapped to targeted business outcomes.

  1. Cloud Cost Optimization

Cloud cost optimization is an iterative and continuous process that provides a consistent methodology to manage cloud consumption cost-effectively. There are three key areas of optimization:

Resource optimization – Model cost-effective cloud usage based on utilization and consumption patterns.
Pricing optimization – Manage cloud spend through a continuous analysis of various pricing models. In a Google Cloud context, that might mean Committed Use Discounts, BigQuery flat rate reservations, etc.
Architecture optimization – Build applications with a cost-aware architecture by leveraging newer generation compute instances (like Tau VMs, which offer an industry-leading 42% better price-performance versus comparable offerings), or using managed services and serverless technology to offload operational overhead.
For example, video hosting, sharing and services platform provider Vimeo built transcoding pipelines by using Google Cloud Spot VMs to optimize their infrastructure spend. To do so, they created fault-tolerant workloads that could withstand preemptions, and in exchange, got up to a 91% discount compared to using regular on-demand instances.

  1. Planning and Forecasting

In the cloud, accurately forecasting your finances requires rethinking of traditional approaches to depreciation and trend-based forecasting of maintenance and licensing costs. One way to improve the accuracy of your dynamic cloud needs is to use 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. In other words, you can define cloud budgets and forecasts by monitoring cloud consumption trends, allocating cloud cost pools with a proper tagging strategy that’s mapped to a chart of accounts in a general ledger, and conducting a cost-benefit analysis based on cloud infrastructure, implementation, and support costs.

  1. Tools and Accelerators

Without the proper tools and processes in place, understanding and managing cloud costs can be complex — and this especially true as organizations scale their business in the cloud. By deploying proper cloud cost management tools and accelerators such as Looker Cloud Cost Management and automation scripts to set guardrails and enforce cost control policies, organizations can effectively manage and track cloud spend with access to near-real-time billing and cost data to make better informed business decisions.

The key objectives of Google Cloud Cost Management tools are to make it as simple as possible for organizations to get visibility into their current and forecasted costs with built-in reporting and customizable dashboards; help drive greater accountability for cloud spending across the organization by providing flexible ways to organize cloud resources and allocate costs; provide strong financial governance controls to reduce the risk of overspending; and offer intelligent recommendations for optimizing cloud costs and usage.

Start Saving with Cloud

Businesses are continuously seeking to better operate and manage their cloud environments and the need is ever increasing to transparently manage cloud spend, optimize costs, and obtain their desired business agility. By enhancing your Cloud FinOps capabilities and adopting principles of continuous cost optimization, you too can accelerate the business value of cloud computing.

Special thanks to Bruce WarnerDaniel PetiboneNihar Jhawar and FinOps Foundation community for their contributions and sharing their domain expertise to this important Cloud FinOps topic.

Whitepaper

Analyze and Evaluate Migration Strategies with Google

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In this whitepaper, we outline migration frameworks that we built based on conversations we’ve had with CIOs, CTOs, and their technical staff. The goal of these frameworks is to help you devise a migration strategy that empowers both IT and the business.

Learn how to analyze migration strategies for your business, including:

  • Moving up the stack before you migrate
  • Migrating workloads into the cloud (mostly) as is
  • Optimizing and modernizing workloads once you’ve migrated
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Google Cloud Garners Highest Score in Forrester New Wave for Computer Vision Platforms

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In Forrester’s evaluation of the emerging market for computer vision platforms, it identified the 11 most significant providers in the category — Amazon Web Services, Chooch AI, Clarifai, Deepomatic, EdgeVerve, Google, Hive, IBM, Microsoft, Neurala, and SAS — and evaluated them.

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Its report details its findings about how well each vendor scored against 10 criteria and where they stand in relation to each other.

Google Cloud was classified as “differentiated” (the highest class) across all 10 criteria.

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Find out more. Download The Forrester New Wave™: Computer Vision Platforms, Q4 2019.

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Google Cloud’s Metric Scope Makes Multi-project Monitoring Simple

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Metric Scopes, Google Cloud's new model for multi-project monitoring replaces the concept of Workspaces. It has no limit in ways it can be associated with a project. Read on to learn to leverage Metric Scopes for all your Google Cloud projects.

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: 
Metrics Scope explanation
Metrics from all the projects are visible by using the scoping project Project-SRE, a project that was created specifically to monitor the fleet. It has a Metrics Scope of 3.
  • 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:
Metrics Scopes 2
Only metrics from the Developer’s project are visible by using the scoping project Project-Dev-1. It has a Metrics Scope of 1.

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:
Metrics scopes gif1
Adding more than one project to a Metrics Scope

Navigation

  • Mentioned earlier, the Project Picker in the Cloud Console can be used to navigate between Metrics Scopes in Cloud Monitoring:
Project Picker for Metrics Scope
A view of the Project Picker in the Cloud Console which can be used to navigate between Metrics Scopes
  • 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:
Metrics scopes gif2
The Project Picker stays consistent as you are navigating multiple services
  • Additionally, to make your navigation between Metrics Scopes easy we’ve added the new Metrics Scope Tab and Panel in the UI:
Metrics scopes gif3
Metrics Scopes panel in the Cloud Console 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.

Case Study

What Swiggy and You Can Learn From This Company’s Use of ML to Engage Customers

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Just Eat, which is similar to Swiggy, uses Google Cloud's machine learning to power sophisticated consumer recommendations on both its app and website. It enables them to create an “Adventurous Index”, for instance, something we haven't seen in Indian ordering apps.

The app economy has enabled a huge range of unique business models to flourish. One such model is online food ordering and delivery services, in which apps leverage geo-location data to aggregate local food choices and offer personalized options to consumers.

A leading company in this space is Just Eat. Launched in the UK in 2001 with a vision of ‘serving the world’s greatest menu. Brilliantly.’ The company has capitalized on the popularity of online food delivery and grown its presence across 12 markets. 

Just Eat acts as an intermediary between take-out food outlets and hungry customers, giving local restaurants access to a broader base of potential diners, while providing consumers with an easy and secure way to order and pay for food from their favourite restaurants.

Today the company helps 27 million customers find food from more than 112,000 restaurants—everything from homemade Italian pasta, to Chinese noodle bowls, to fish-and-chips. 

Data is the fuel of Just Eat’s rapid growth, but it wasn’t always looked at that way. In its early days, Just Eat struggled with the deluge of information and faced fragmentation across its systems. In fact, the company realized its legacy data vendor wasn’t capable of ingesting 90 percent of the data produced by its food platform. This was incredibly frustrating for Just Eat’s analysts and data scientists, who had to waste time cleaning up sources instead of leveraging the data to create a better user experience. 

Just Eat turned to Google Cloud, and now uses machine learning (ML) to power sophisticated consumer recommendations on both its app and website. It also makes heavy use of features offered by Google Cloud Platform, including BigQuery for running analytics on its customer data set and Cloud Pub/Sub for messaging app users with relevant offers in real-time. 

Having all of Just Eat’s data in one platform has translated into real value for its customers. With Google Cloud tools, Just Eat has created its own proprietary Customer Ontology framework, which today contains 5.5 billion features that better understand consumers’ behavior and food habits, and provides insights into previous visits.

Just Eat recently created an “Adventurous Index” to map its customers according to their ordering habits, enabling them to tailor their marketing and user experiences. For example, mid-adventurous customers are shown a choice of restaurants that serve their most ordered cuisine, while adventurous customers can choose from restaurants that serve a wider variety. This not only has prompted consumers to be more adventurous with their choices, but also has led to more business at a more diverse set of restaurants.

Matt Cresswell, Director of Customer Platforms at Just Eat said that Google Cloud has become integral to its product delivery: “Consumer food choice is a hugely nuanced topic. We know that individuals have their own unique journeys when they use Just Eat. We’ve sought to create a truly one-to-one relationship with every customer. The changes we’ve made to the platform mean they can access the dishes they enjoy at the touch of a fingertip, and find inspiration to discover new dishes they’ll love. We’re grateful to Google Cloud for helping us support our customers on their culinary explorations.”

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