Today, we are putting the power of Google’s insights and intelligence in the hands of risk, fraud, and security teams everywhere. We are pleased to announce the general availability of reCAPTCHA Enterprise Fraud Prevention, a new product that uses Google’s own fraud models, machine learning, and intelligence from protecting more than 6 million websites to help stop payment fraud.

reCAPTCHA Enterprise Fraud Prevention can help protect payment transactions by identifying targeted manual attacks and large-scale fraud attempts. It automatically trains fraud models based on behavior and transaction data to identify events that are likely fraudulent and could cause a dispute or chargeback if accepted. 

When threat actors are identified and blocked on any site in the reCAPTCHA network, the intelligence is made available to help protect other organizations from those same attackers. Organizations can then use the scores to send the transaction for manual review or directly block suspicious transactions, drive increased trust in their legitimate transactions, reduce the amount of friction for good users, and reduce erroneous rejection rates.

“Being a safe and trusted place to give and receive help is our top priority. We are constantly innovating, refining and enhancing our fraud defenses and Google’s reCAPTCHA Enterprise Fraud Prevention adds another layer of industry-leading protection for our users. Combining Google’s rich security expertise with GoFundMe’s focus on fraud prevention is already showing promising results as we strive to keep our platform the safest place to give online,” said Matthew Murray, director of risk, GoFundMe.

According to data obtained from our customers using reCAPTCHA Enterprise Fraud Prevention in private Preview, the new solution can help drive comprehensive value for organizations by:

• Reducing fraud losses: Get behavior modeling (not just mouse movements), stop financial damage created by account takeovers (ATOs), and connect fraud and abuse intelligence across your site and application.
• Increasing legitimate sales: Fraud Prevention can help businesses increase their revenue by providing insights to understand who good users are, who may otherwise be caught in an overly aggressive, customer restrictive fraud model.*

These benefits  are enabled for organizations by:

• Preventing advanced attacks: Stopping sophisticated attacks in an environment where attackers use cloud fraud infrastructure, and data leaks, virtual cards and VPN usage are on the rise
• Increasing trust in good transactions: Focus on good approval rates through a unique combination of supervised and unsupervised models
• Improving customer experience: By preventing fraudulent transactions with zero user friction, Fraud Prevention can help businesses protect legitimate users and increase customer retention

Our customers have used these new capabilities in preview in customer experiences that include online checkouts and payment transactions. Fraud Prevention has been used by merchants and payment processors to block millions of dollars in fraudulent transactions in a frictionless way. 

reCAPTCHA Enterprise provides a comprehensive online fraud detection platform that helps prevent fraudulent, spammy, and abusive digital client activity across your web and application footprint. This platform includes Account Defender, which protects users from account takeovers (ATO), frictionless bot management capabilities, and password leak detection to identify compromised accounts. With an additional API call for Fraud Prevention, organizations can leverage a comprehensive solution to secure financial transactions along with core reCAPTCHA Enterprise capabilities. 

To get started, organizations can install a score-based site key on each part of the payment user flow front end and send transaction data when a purchase occurs. This site key helps train site-specific fraud models and start returning fraud scores for each transaction. 

Ready to put reCAPTCHA Enterprise Fraud Prevention to work? Contact our fraud specialists or your customer success CSM team and sign up with the free tier. You learn more about these new capabilities in reCAPTCHA Enterprise in our product documentation. You can also register for our webinar where our experts will be discussing this capability in great detail on June 1, 2023. 

Coming up at our Security Summit on June 13-14, you can hear how reCAPTCHA Enterprise helped GoFundMe secure their donors from fraud. Sign up here for free Security Summit registration.

As the way people work continues to evolve, keeping security policies in place that protect organizations but give workers the ability to get things done is more important than ever. IT and security teams must aim to stay a step ahead of web-based security threats that come their organization’s way. To help, the Center for Internet Security (CIS) team has released the latest CIS Benchmark 2.1 for Google Chrome. This Benchmark offers independent recommendations on which Chrome policies to configure to help support organizations’ security and compliance needs. Thanks to Chrome being built with security at its core, in many cases, Chrome default settings are aligned with CIS recommendations.

Chrome is secure by default, but we also pride ourselves on providing customizations for enterprises to allow Chrome to better fit the needs of their business. And with hundreds of policies available through Chrome Browser Cloud Management and Group Policy Objects (Note: The CIS Benchmark is also available as a GPO), organizations can do just that. 

Throughout the CIS guide you’ll notice that there are different designations for configuration profiles. Any labeled Level 1, are considered to be a good baseline for an organization. Level 2 profiles are recommended for deployments that require the highest level of security, but note that these settings could have a trade off on user productivity. We recommend looking at each setting and determining if it’s a good fit for your business. 

The benchmark is made up of five sections:

• Enforced Defaults — Notes policies that are configured by default when you install Chrome. Enforcing these settings at an enterprise level can prevent these settings from being changed by business users to less secure options.
• Attack Surface Reduction — Details how to disable web features that may not be necessary in your enterprise environment and could reduce your overall attack surface.
• Privacy — Surfaces settings that improve user privacy.
• Data Loss Prevention — Contains settings that can help prevent data loss and protect your organization’s data. (Note: These recommendations cover additional capabilities that can be added to Chrome through BeyondCorp Enterprise). 
• Forensics (Post Incident) — Shares recommendations on policies that give insights into post incident forensics and analysis. 

Organizations can use these benchmarks to optimize the best way to secure Chrome in their environment. Download the CIS Benchmark here and check out our team’s configuration guide for additional recommendations on how to configure Chrome.

Note: This benchmark was created using a consensus review process composed of subject matter experts. Consensus participants provide perspective from a diverse set of backgrounds such as consulting, software development, audit and compliance, security  research, operations, government, and legal. While these recommendations come from a trusted source, it’s important for each organization to weigh which policies make the most sense for their business.

Enterprises are increasingly seeking out technologies that help them create unique experiences for customers with speed and at scale. At the same time, customers want flexibility when deciding where to manage their enterprise data, particularly when it comes to business-critical applications.

That’s why I’m thrilled that Sprinklr, the unified customer experience management (Unified-CXM) platform for modern enterprises, has partnered with Google Cloud to accelerate its go-to-market strategy and grow awareness among our joint customers. Sprinklr will work closely with our global salesforce, benefitting from our deep relationships with enterprises that have chosen to build on Google Cloud. 

Akin to Google Cloud’s mission to accelerate every organization’s ability to digitally transform their business through data-powered innovation, Sprinklr’s primary objective is to empower the world’s largest and most loved brands to make their customers happier by listening, learning, and taking action through insights. With this strategic partnership now in place, Sprinklr and Google Cloud will go-to-market together with the end-customer as our sole focus.

Traditionally, brands have adopted point solutions to manage segments of the customer journey. In isolation, these may work — but they rarely work collaboratively, even when vendors build “Frankenstacks” of disconnected products. These solutions can’t deliver a 360° view of the customer, and often reinforce departmental silos. All of which creates point-solution chaos.

Sprinklr’s approach is fundamentally different and is the way out of the aforementioned point-solution chaos. As the first platform purpose-built for unified customer experience management (Unified-CXM) and trusted by the enterprise, Sprinklr’s industry-leading AI and powerful Care, Marketing, Research, and Engagement solutions enable the world’s top brands to learn about their customers, understand the marketplace, and reach, engage, and serve customers on all channels to drive business growth. 

Sprinklr was built from the ground up as a platform-first solution, designed to evolve and grow with the rapid expansion of digital channels and applications. The results? Faster innovation. Stronger performance. And a future-proof strategy for customer engagement on an enterprise scale.

“Sprinklr works with large, global companies that want flexibility when deciding where to manage their enterprise data and consider our platform a business-critical application,” said Doug Balut, Senior Vice President of Global Alliances, Sprinklr. “Giving our customers the opportunity to manage Sprinklr on Google Cloud empowers them to create engaging customer experiences while maintaining the high security, scalability, and performance they need to run their business.”

To learn more about this exciting partnership and the challenges we jointly solve for customers, check out the recent conversation between Google Cloud’s VP of Marketing, Sarah Kennedy, and Sprinklr’s Chief Experience Officer, Grad Conn. Or read the press release on the partnership.

When customers migrate to Google Cloud Platform (GCP), their first step is often to adopt Compute Engine, which makes it easy to procure and set up virtual machines (VMs) in the cloud that provide large amounts of computing power. Launched in 2012, Compute Engine offers multiple machine types, many innovative features, and is available in 20 regions and 61 zones! 

Compute Engine’s predefined and custom machine types make it easy to choose VMs closest to your on-premises infrastructure, accelerating the workload migration process cost effectively. Cloud allows you the pricing advantage of ‘pay as you go’ and also provides significant savings as you use more compute with Sustained Use Discounts. 

As Technical Account Managers, we work with large enterprise customers to analyze their monthly spend and recommend optimization opportunities. In this blog, we will share the top recommendations that we’ve developed based on our collective experience working with GCP customers. 

Getting ready to save

Before you get started, be sure to familiarize yourself with the VM instance pricing page—required reading for anyone who needs to understand the Compute Engine billing model and resource-based pricing. In addition to those topics, you’ll also find information about the various Compute Engine machine types, committed use discounts and how to view your usage, among other things. 

Another important step to gain visibility into your Compute Engine cost is using Billing reports in the Google Cloud Console and customizing your views based on filtering and grouping by projects, labels and more. From there you can export Compute Engine usage details to BigQuery for more granular analysis. This allows you to query the datastore to understand your project’s vCPU usage trends and how many vCPUs can be reclaimed. If you have defined thresholds for the number of cores per project, usage trends can help you spot anomalies and take proactive actions. These actions could be rightsizing the VMs or reclaiming idle VMs.

Now, with these things under your belt, let’s go over the five ways you can optimize your Compute Engine resources that we believe will give you the most immediate benefit. 

1. Apply Compute Engine rightsizing recommendations

Compute Engine’s rightsizing recommendations feature provides machine type recommendations that are generated automatically based on system metrics gathered by Stackdriver Monitoring over the past eight days. Use these recommendations to resize your instance’s machine type to more efficiently use the instance’s resources. It also recommends custom machine types when appropropriate. Compute Engine makes viewing, resizing and other actions easier right from the Cloud Console as shown below. 

Recently, we expanded Compute Engine rightsizing capabilities from just individual instances to managed instance groups as well. Check out the documentation for more details.

For more precise recommendations, you can install the Stackdriver Monitoring agent which collects additional disk, CPU, network, and process metrics from your VM instances to better estimate your resource requirements. You can also leverage the Recommender API for managing recommendations at scale.

2. Purchase Commitments

Our customers have diverse workloads running on Google Cloud with differing availability requirements. Many customers follow a 70/30 rule when it comes to managing their VM fleet—they have constant year-round usage of ~70%, and a seasonal burst of ~30% during holidays or special events. 

If this sounds like you, you are probably provisioning resources for peak capacity. However, after migrating to Google Cloud, you can baseline your usage and take advantage of deeper discounts for Compute workloads. Committed Use Discounts are ideal if you have a predictable steady-state workload as you can purchase a one or three year commitment in exchange for a substantial discount on your VM usage.

We recently released a Committed Use Discount analysis report in the Cloud Console that helps you understand and analyze the effectiveness of the commitments you’ve purchased. In addition to this, large enterprise customers can work with their Technical Account Managers who can help manage their commitment purchases and work proactively with them to increase Committed Use Discount coverage and utilization to maximize their savings.

3. Automate cost optimizations

The best way to make sure that your team is always following cost-optimization best practices is to automate them, reducing manual intervention.

Automation is greatly simplified using a label—a key-value pair applied to various Google Cloud services. For example, you could label instances that only developers use during business hours with “env: development.” You could then use Cloud Scheduler to schedule a serverless Cloud Function to shut them down over the weekend or after business hours and then restart them when needed. Here is an architecture diagram and code samples that you can use to do this yourself. 

Using Cloud Functions to automate the cleanup of other Compute Engine resources can also save you a lot of time and money. For example, customers often forget about unattached (orphaned) persistent disk, or unused IP addresses. These accrue costs, even if they are not attached to a virtual machine instance. VMs with the “deletion rule” option set to “keep disk” retain persistent disks even after the VM is deleted. That’s great if you need to save the data on that disk for a later time, but those orphaned persistent disks can add up quickly and are often forgotten! There is a Google Cloud Solutions article that describes the architecture and sample code for using Cloud Functions, Cloud Scheduler, and Stackdriver to automatically look for these orphaned disks, take a snapshot of them, and remove them. This solution can be used as a blueprint for other cost automations such as cleaning up unused IP addresses, or stopping idle VMs. 

4. Use preemptible VMs

If you have workloads that are fault tolerant, like HPC, big data, media transcoding, CI/CD pipelines or stateless web applications, using preemptible VMs to batch-process them can provide massive cost savings. In fact, customer Descartes Labs reduced their analysis costs by more than 70% by using preemptible VMs to process satellite imagery and help businesses and governments predict global food supplies.

Preemptible VMs are short lived— they can only run a maximum of 24 hours, and they may be shut down before the 24 hour mark as well. A 30-second preemption notice is sent to the instance when a VM needs to be reclaimed, and you can use a shutdown script to clean up in that 30-second period. Be sure to fully review the full list of stipulations when considering preemptible VMs for your workload. All machine types are available as preemptible VMs, and you can launch one simply by adding “-preemptible” to the gcloud command line or selecting the option from the Cloud Console. 

Using preemptible VMs in your architecture is a great way to scale compute at a discounted rate, but you need to be sure that the workload can handle the potential interruptions if the VM needs to be reclaimed. One way to handle this is to ensure your application is checkpointing as it processes data, i.e., that it’s writing to storage outside the VM itself, like Google Cloud Storage or a database. As an example, we have sample code for using a shutdown script to write a checkpoint file into a Cloud Storage bucket. For web applications behind a load balancer, consider using the 30-second preemption notice to drain connections to that VM so the traffic can be shifted to another VM. Some customers also choose to automate the shutdown of preemptible VMs on a rolling basis before the 24-hour period is over, to avoid having multiple VMs shut down at the same time if they were launched together. 

5. Try autoscaling 

Another great way to save on costs is to run only as much capacity as you need, when you need it. As we mentioned earlier, typically around 70% of capacity is needed for steady-state usage, but when you need extra capacity, it’s critical to have it available. In an on-prem environment, you need to purchase that extra capacity ahead of time. In the cloud, you can leverage autoscaling to automatically flex to increased capacity only when you need it. 

Compute Engine managed instance groups are what give you this autoscaling capability in Google Cloud. You can scale up gracefully to handle an increase in traffic, and then automatically scale down again when the need for instances is lowered (downscaling). You can scale based on CPU utilization, HTTP load balancing capacity, or Stackdriver Monitoring metrics. This gives you the flexibility to scale based on what matters most to your application. 

High costs do not compute

As we’ve shown above, there are many ways to optimize your Compute Engine costs. Monitoring your environment and understanding your usage patterns is key to understanding the best options to start with, taking the time to model your baseline costs up front. Then, there are a wide variety of strategies to implement depending on your workload and current operating model. 

For more on cost management, check out our cost management video playlist. And for more tips and tricks on saving money on other GCP services, check out our blog posts on Cloud Storage, Networking and BigQuery cost optimization strategies. We have additional blog posts coming soon, so stay tuned!

To help organizations confidently move their sensitive data to the cloud, Google Cloud works diligently to earn and maintain customer trust. Our Trusted Cloud is committed to giving you a secure foundation that you can verify and independently control. Discovery and protection of sensitive data are integral parts of Google Cloud’s strategy to safeguard customer data. With this as our longstanding approach to protecting customers, we are happy to share that Forrester Research has ranked Google Cloud a Leader in The Forrester Wave™ Data Security Platforms Q1 2023.

Relentless security innovation leveraging Google’s core strengths

Google keeps more people safe online than anyone else. The scale at which we operate allows us to pioneer approaches to cloud-native security and then bring them to commercial and public sector organizations everywhere they operate. Leveraging our data processing and novel analytics capabilities with artificial intelligence and machine learning (AI/ML) allows our technology to help protect enterprises and their end users. At the core of our data security capabilities is our data loss prevention (DLP) technology, which enables customers to discover, classify, and de-identify data in real-time, on-demand, continuously, and in event-driven workloads.

In their explanation for the ranking, Forrester noted in its report “Cloud-first, Google has notable areas of innovation focus, such as harnessing machine learning (ML) and artificial intelligence (AI), productizing internal innovations, and co-innovation with partners in areas like confidential computing, data sovereignty controls, and external cloud key management services.”

Embedded across multiple Google products

Our platform supports the discovery of corporate assets in Chrome Enterprise and Google Workspace applications including Gmail and Google Drive. We also provide support for discovering production and analytical assets such as object storage, relational databases, data warehouses, data lakes, production apps, and workloads such as migration/ETL. This technology identifies and detects various types of sensitive data using a comprehensive set of built-in infoType detectors that are ready to use out-of-the-box along with flexible custom detection options and rules. Types of sensitive data include personal identifiable information and personal health information (PII/PHI), financial identifiers, health context, multi-cloud credentials/secrets, and ML-based full document classification (including source code, SEC filings, and legal briefings).

Driven by Zero Trust principles

The Forrester Wave identified the 14 top significant data security platform providers. Forrester notes in the report that “[Google] also stands out for manageability and integrations for Zero Trust.” and “Google is a strong choice for organizations considering or currently using GCP as well as those using Google Workspace who are taking a Zero Trust approach to enabling bring your own device (BYOD) and remote work.”

Delivering value for our customers

We are honored to be a Leader in The Forrester Wave™: Data Security Platforms, Q1 2023 report. We look forward to continuing to innovate with you and make your digital transformation journey safer with our Trusted Cloud.

A copy of the full report can be viewed here.