In an industry as highly regulated as healthcare, building a single secure and compliant application that tracks patient care and appointments at a clinic requires a great deal of planning from development and security teams. So, imagine what it would be like to build a solution that includes almost everything related to a patient’s healthcare, including insurance and billing. That’s what Highmark Health (Highmark)—a U.S. health and wellness organization that provides millions of customers with health insurance plans, a physician and hospital network, and a diverse portfolio of businesses–decided to do. 

Highmark is developing a solution called Living Health to re-imagine healthcare delivery, and it is using Google Cloud and the Google Cloud Professional Services Organization (PSO) to build and maintain the innovation platform supporting this forward thinking experience. Considering all the personal information that different parties like insurers, specialists, billers and coders, clinics, and hospitals share, Highmark must build security and compliance into every part of the solution. 

In this blog, we look at how Highmark Health and Google are using a technique called “secure-by-design” to address the security, privacy, and compliance aspects of bringing Living Health to life.

Secure-by-design: Preventive care for development

In healthcare, preventing an illness or condition is the ideal outcome. Preventive care often involves early intervention—a course of ideas and actions to ward off illness, permanent injury, and so on. Interestingly, when developing a groundbreaking delivery model like Living Health, it’s a good idea to take the same approach to security, privacy, and compliance. 

That’s why Highmark’s security and technology teams worked with their Google Cloud PSO team to implement secure-by-design for every step of design, development, and operations. Security is built into the entire development process rather than waiting until after implementation to reactively secure the platform or remediate security gaps. 

It’s analogous to choosing the right brakes for a car before it rolls off the assembly line instead of having an inspector shut down production because the car failed its safety tests. The key aspect of secure-by-design is an underlying application architecture created from foundational building blocks that sit on top of a secure cloud infrastructure. Secure-by-design works to ensure that these building blocks are secure and compliant before moving on to development.

The entire approach requires security, development, and cloud teams to work together with other stakeholders. Most importantly, it requires a cloud partner, cloud services, and a cloud infrastructure that can support it. 

Finding the right cloud and services for secure-by-design 

Highmark chose Google Cloud because of its leadership in analytics, infrastructure services, and platform as a service. In addition, Google Cloud has made strategic investments in healthcare interoperability and innovation, which was another key reason Highmark decided to work with Google. As a result, Highmark felt that Google Cloud and the Google Cloud PSO were best suited for delivering on the vision of Living Health—its security and its outcomes. 

“Google takes security more seriously than the other providers we considered, which is very important to an organization like us. Cloud applications and infrastructure for healthcare must be secure and compliant,” explains Highmark Vice President and Chief Information Security Officer, Omar Khawaja. 

Forming a foundation for security and compliance

How does security-by-design with services work? It starts with the creation and securing of the foundational platform, allowing teams to harden and enforce specified security controls. It’s a collaborative process that starts with input from cross-functional teams—not just technology teams—using terms they understand, so that everyone has a stake in the design. 

A strong data governance and protection program classifies and segments workloads based on risk and sensitivity. Teams build multiple layers of defense into the foundational layers to mitigate against key industry risks. Google managed services such as VPC Service Controls help prevent unauthorized access. Automated controls such as those in Data Loss Prevention help teams quickly classify data and identify and respond to potential sources of data risk. Automation capabilities help ensure that security policies are enforced.

After the foundational work is done, it’s time to assess and apply security controls to the different building blocks, which are Google Cloud services such as Google Kubernetes Engine, Google Compute Engine, and Google Cloud Storage. The goal is to make sure that these and similar building blocks, or any combination of them, do not introduce additional risks and to ensure any identified risks are remediated or mitigated. 

Enabling use cases, step by step

After the foundational security is established, the security-by-design program enables the Google Cloud services that developers then use to build use cases that form Living Health. The service enablement approach allows Highmark to address complexity by providing the controls most relevant for each individual service. 

For each service, the teams begin by determining the risks and the controls that can reduce them. The next step is enforcing preventive and detective controls across various tools. After validation, technical teams can be granted an authorization to operate, also called an ATO. An ATO authorizes the service for development in a use case.

For use cases with greater data sensitivity, the Highmark teams validate the recommended security controls with an external trust assessor, who uses the HITRUST Common Security Framework, which maps to certifications and compliance such as HIPAA, NIST, GDPR, and more. A certification process follows that can take anywhere from a few weeks to a few months. In addition to certification, there is ongoing monitoring of the environment for events, behavior, control effectiveness, and control lapses or any deviation from the controls.

The approach simplifies compliance for developers by abstracting compliance requirements away. The process provides developers a set of security requirements written in the language of the cloud, rather than in the language of compliance, providing more prescriptive guidance as they build solutions. Through the secure-by-design program, the Highmark technology and security teams, Google, the business, and the third-party trust assessor all contribute to a secure foundation for any architectural design with enabled Google Cloud services as building blocks. 

Beating the learning curve 

Thanks to the Living Health project, the Highmark technology and security teams are trying new methods. They are exploring new tools for building secure applications in the cloud. They are paying close attention to processes and the use case steps and, when necessary, aligning different teams to execute. Because everyone is working together collaboratively toward a shared goal, teams are delivering more things on time and with predictability, which has reduced volatility and surprises. 

The secrets to success: Bringing everyone to the table early and with humility

Together, Highmark and Google Cloud PSO have created over 24 secure-by-design building blocks by bringing everyone to the table early and relying on thoughtful, honest communication. Input for the architecture design produced for Highmark came from privacy teams, legal teams, security teams, and the teams that are building the applications. And that degree of collaboration ultimately leads to a much better product because everyone has a shared sense of responsibility and ownership of what was built. 

Delivering a highly complex solution like Living Health takes significant, more purposeful communication and execution. It is also important to be honest and humble. The security, technology, and Google teams have learned to admit when something isn’t working and to ask for help or ideas for a solution. The teams are also able to accept that they don’t have all the answers, and that they need to figure out solutions by experimenting. Khawaja puts it simply, “That level of humility has been really important and enabled us to have the successes that we’ve had. And hopefully that’ll be something that we continue to retain in our DNA.”

When you choose to run your business on Google Cloud you benefit from the same planet-scale infrastructure that powers Google’s products such as Maps, YouTube, and Workspace. 

We have picked 10 ways in which Google Cloud Infrastructure services outshine alternatives in the market in how they simplify your operations, save money, and secure your data. 

1. Custom Machine Types means no wasted resources

Compute Engine offers predefined machine types that you can use when you create a VM instance. A predefined machine type has a preset number of vCPUs and a preset amount of memory; each type is billed at a set price as described on the Compute Engine pricing page. 

If predefined machine types don’t meet your needs, you can create a VM instance with a custom number of vCPUs and custom amount of memory, effectively building a custom machine type. Custom machine types are available only for general-purpose machine families. When you create a custom machine type, you are deploying a custom machine type from the E2, N2, N2D, or N1 machine family on GCP.  No other leading cloud vendor offers custom machine types so extensively.

Custom machine types are a good idea for workloads that aren’t a good fit for the predefined machine types and for workloads that require more processing power or memory but don’t need all of the upgrades provided by the next machine type level. This translates into lower operating costs.   They are also useful for controlling software licensing costs that are based on the number of underlying compute cores. 

Jeremy Lloyd, Infrastructure and Application Modernization Lead at Appsbroker, a Google partner: 

“Custom machine types coupled with Google’s StratoZone data center discovery tool provides Appsbroker with the flexibility we need to provide cost efficient virtual machines matched to a virtual machine’s actual utilization. As a result, we are able to keep our customers’ operating costs low while still providing the ability to scale as needed.”

2. Compute Engine Virtual Machines are optimized for scale-out workloads 

For scale-out workloads, T2D, the first instance type in the Tau VM family, is based on 3rd Gen AMD EPYC processors and leapfrogs VMs for scale-out workloads of any leading public cloud provider today, both in terms of performance and price-performance. Tau VMs offer 56% higher absolute performance and 42% higher price-performance compared to general-purpose VMs from any leading public cloud vendor (source). The x86 compatibility provided by these AMD EPYC processor-based VMs gives you market-leading performance improvements and cost savings, without having to port your applications to a new processor architecture. Sign up here  if you are interested in trying out T2D instances in Preview. 

For SAP HANA, Google Cloud has demonstrated with SAP how we can run the world’s largest scale-out HANA system in the public cloud (96TB).   With such innovation, you are covered as your business grows exponentially.

3. Largest single node GPU-enabled VM

Google is the only public cloud provider to offer up to 16 NVIDIA A100 GPUs in a single VM, making it possible to train very large AI models. Users can start with one NVIDIA A100 GPU and scale to 16 GPUs without configuring multiple VMs for single-node ML training, without crossing the VM layer. 

Additionally, customers can choose smaller GPU configurations—1, 2, 4 and 8 GPUs per VM—providing the flexibility to scale their workload as needed. 

The A2 VM family was designed to meet today’s most demanding applications—workloads like CUDA-enabled machine learning (ML) training and inference, for example. This family is built on the A100 GPU which offers up to 20x the compute performance compared to the previous generation GPU and comes with 40 GB of high-performance HBM2 GPU memory. To speed up multi-GPU workloads, the A2 VMs use NVIDIA’s HGX A100 systems to offer high-speed NVLink GPU-to-GPU bandwidth that delivers up to 600 GB/s. A2 VMs come with up to 96 Intel Cascade Lake vCPUs, optional Local SSD for workloads requiring faster data feeds into the GPUs and up to 100 Gbps of networking. A2 VMs provide full vNUMA transparency into the architecture of underlying GPU server platforms, enabling advanced performance tuning. Google Cloud offers these GPUs globally. 

4. ​​Non-disruptive maintenance means you worry less about planned downtime

Compute Engine offers live migration (non-disruptive maintenance) to keep your virtual machine instances running even when a host system event, such as a software or hardware update, occurs. Google’s Compute Engine live migrates your running instances to another host in the same zone without requiring your VMs to be rebooted. Live migration enables Google to perform maintenance that is integral to keeping infrastructure protected and reliable without interrupting any of your VMs. When a VM is scheduled to be live-migrated, Google provides a notification to the guest that a migration is imminent. 

Live migration keeps your instances running during:

• Regular infrastructure maintenance and upgrades
• Network and power grid maintenance in the data centers
• Failed hardware such as memory, CPU, network interface cards, disks, power, and so on. This is done on a best-effort basis; if a hardware component fails completely or otherwise prevents live migration, the VM crashes and restarts automatically and a hostError is logged.
• Host OS and BIOS upgrades
• Security-related updates
• System configuration changes, including changing the size of the host root partition, for storage of the host image and packages

Live migration does not change any attributes or properties of the VM itself. The live migration process transfers a running VM from one host machine to another host machine within the same zone. All VM properties and attributes remain unchanged, including internal and external IP addresses, instance metadata, block storage data and volumes, OS and application state, network settings, network connections, and so on. This has the benefit of reducing operational and maintenance overhead, helps you build a more robust security posture where infrastructure can be consciously revamped from a known good state and minimizes risks for advanced persistent threats. 

Refer to Lessons learned from a year of using live migration in production on Google Cloud from the Google engineering team.

5. Trusted Computing: Shielded VMs guard you against advanced, persistent attacks

Establishing trust in your environment is multifaceted, involving hardware and firmware, as well as host and guest operating systems. Unfortunately, threats like boot malware or firmware rootkits can stay undetected for a long time, and an infected virtual machine can continue to boot in a compromised state even after you’ve installed legitimate software. 

Shielded VMs can help you protect your system from attack vectors like:

• Malicious guest OS firmware, including malicious UEFI extensions
• Boot and kernel vulnerabilities in the guest OS
• Malicious insiders within your organization

To guard against these kinds of advanced persistent attacks, Shielded VMs use:

• Unified Extensible Firmware Interface (UEFI) BIOS: Helps ensure that firmware is signed and verified
• Secure and Measured Boot: Helps ensure that a VM boots an expected, healthy kernel
• Virtual Trusted Platform Module (vTPM): Establishes root-of-trust, underpins Measured Boot, and prevents exfiltration of vTPM-sealed secrets
• Integrity Monitoring: Provides tamper-evident logging, integrated with Stackdriver, to help you quickly identify and remediate changes to a known integrity state

The Google approach allows customers to deploy Shielded VMs with only a simple click, thereby easing implementation. 

6. Confidential Computing encrypts data while in use

Google Cloud was a founding member of the Confidential Computing Consortium. Along with encryption of data in transit and at rest using customer-managed encryption keys (CMEK) and customer-supplied encryption keys (CSEK), Confidential VM adds a “third pillar” to the end-to-end encryption story by encrypting data while in use. Confidential Computing uses processor-based technology that allows data to be encrypted in use while it is being processed in the public cloud. Confidential VM allows you to to encrypt memory in use on a Google Compute Engine VM by checking a single checkbox. 

All Confidential VMs support the previously mentioned Shielded VM features under the covers—you can think of Shielded VM as helping to address VM integrity, while Confidential VM addresses the memory encryption aspect which relies on CPU features. With the confidential execution environments provided by Confidential VM and AMD Secure Encrypted Virtualization (SEV), Google Cloud keeps customers’ sensitive code and other data encrypted in memory during processing. Google does not have access to the encryption keys. In addition, Confidential VM can help alleviate concerns about risk related to either dependency on Google infrastructure or Google insiders’ access to customer data in the clear. 

See what Google Cloud partners say about Confidential Computing here. 

7. Advanced networking delivers full-stack networking and security services with fast, consistent, and scalable performance

Google Cloud’s network delivers low latency, reduces operational costs and ensures business continuity, enabling organizations to seamlessly scale up or down in any region to meet business needs. Our planet-scale network uses advanced software-defined networking and security with edge caching services to deliver fast, consistent, and scalable performance. With 28 regions, 85 zones, and 146 PoPs connected by 16 subsea fiber cables around the world, Google Cloud’s network offers a full stack of layer 1 to layer 7 services for enterprises to run their workloads anywhere. Enterprises can be assured that they have best-in-class networking and security services connecting their VMs, containers, and bare metal resources in hybrid and multi-cloud environments with simplicity, visibility, and control. 

Google Cloud’s network has protected customers from one of the world’s largest DDoS attacks at 2.54 Tbps. With our multi-layer security architecture and products such as Cloud Armor, our customers ran their business with no disruptions. Furthermore, our recent integration of Cloud Armor with reCAPTCHA Enterprise adds best-in-class bot and fraud management to prevent volumetric attacks. Cloud Armor is deployed with our Cloud Load Balancer and Cloud CDN, extending the secure benefits at the network edge for traffic coming into Google Cloud so customers have security, performance, and reliability all built in. Furthermore, we are excited to offer Cloud IDS in preview, which was co-developed with security industry leader, Palo Alto Networks, to run natively in Google Cloud. 

Our advanced networking capabilities also extends to GKE and Anthos networking. With the GKE Gateway controller, customers can manage internal and external HTTPS load balancing for a GKE cluster or a fleet of GKE clusters with multi-tenancy while maintaining centralized admin policy and control. Unlike other Kubernetes offerings, we offer eBPF dataplane which brings powerful tooling such as Kubernetes network policy and logging to GKE. eBPF is known to kernel engineers as a “superpower” for its unique architecture to load and unload modules in kernel space, and now this capability is built in with Google Cloud networking. 

For observability and monitoring, our customers deploy Network Intelligence Center, Google Cloud’s comprehensive network monitoring, verification and optimization platform. With four key modules in Network Intelligence Center, and several more to come, we are working towards realizing our vision of proactive network operations that can predict and heal network failures, driven by AI/ML recommendations and remediation. Network Intelligence Center provides unmatched visibility into your network in the cloud along with proactive network verification. Centralized monitoring cuts down troubleshooting time and effort, increases network security and improves the overall user experience.  

8. Regional Persistent Disk for High Availability

Regional Persistent Disk is a storage option that provides synchronous replication of data between two zones in a region. Regional Persistent Disks can be a great building block if you need to ensure high availability of your critical applications as they offer cost-effective durable storage and replication of data between two zones in the same region. 

Regional Persistent Disks are also easy to set up within the Google Cloud Console. If you are designing robust systems or high availability services on Compute Engine, Regional Persistent Disks combined with other best practices such as backing up your data using snapshots enable you to build an infrastructure that is highly available and recoverable in a disaster. Regional Persistent Disks are also designed to work with regional managed instance groups. In the unlikely event of a zonal outage, Regional Persistent Disks allow continued I/O through failover of your workloads to another zone. Regional Persistent Disks can help meet zero RPO and near-zero RTO requirements and other stringent SLAs that your critical applications might require by maximizing application availability and protection of data during events such as host/VM failures and zonal outages. 

9. Cloud Storage’s single namespace for dual-region and multi-region means managing regional replication is incredibly simple

Similar to how Persistent Disk makes data more available by replicating data across zones, Cloud Storage provides similar benefits for object storage. Cloud Storage within a region is cross-zone by definition, reducing the risk that a zonal outage would take down your application. Cloud Storage adds to this by also providing a cross-region option that can protect against a regional outage and gets your data closer to distributed users. This comes in the form of Dual-region or Multi-region settings for a bucket. These are the simplest to implement cross-region replication offerings in the industry—just a simple button or API call to enable them. In addition to being simple to implement, they offer an added advantage of using a single bucket name that spans regions. 

This is unique in the industry. Competitive offerings currently require setting up and managing two distinct buckets, one in each region and they don’t offer the strong consistency properties Cloud Storage offers across regions. Operations and app development are burdened by this design. Google’s single namespace approach dramatically simplifies application development (the app runs on single region or dual/multi-region without any changes), and provides simpler application restarts and testing for DR.

10. Predictive autoscaling 

Customers use predictive autoscaling to improve response times for applications with long initialization times or for applications with workloads that vary predictably with daily or weekly cycles. When you enable predictive autoscaling, Compute Engine forecasts future load based on your Managed Instance Group’s history and scales out the MIG’s in advance of predicted load, so that new instances are ready to serve when the load arrives. Without predictive autoscaling, an autoscaler can only scale a group reactively, based on observed changes in load in real time. 

With predictive autoscaling enabled, the autoscaler works with real-time data as well as with historical data to cover both the current and forecasted load. Forecasts are refreshed every few minutes (faster than competing clouds) and consider daily and weekly seasonality, leading to more accurate forecasts of load patterns.

For more information, see How predictive autoscaling works and Checking if predictive autoscaling is suitable for your workload.

These are just a few examples of customer-centric innovation that set Google Cloud infrastructure apart.  Bring your applications and let the platform work for you.   

Get started by learning about your options for migration, or talk to our sales team to join the thousands of customers who have embarked upon this journey.

Acknowledgement

Special thanks to Dheeraj Konidena (Google) for contributing to this article.

As enterprises accelerate adoption of cloud-based services and products, they face a common challenge: How can they effectively secure and govern rapidly expanding volumes of their most sensitive data in new environments? 

Today, Google Cloud released an architectural whitepaper and accompanying source code for a solution which successfully completed an assessment facilitated by KPMG LLP and has been accredited by the Enterprise Data Management Council (EDM Council) as a Cloud Data Management Capabilities (CDMC) Certified Cloud Solution. The architecture, which includes Google Cloud’s BigQuery and Dataplex Data Catalog, has been validated against CDMC’s control framework and can be used by new or existing Google Cloud clients wanting to migrate their sensitive data to the cloud with greater confidence.

“This is an exciting milestone for Google Cloud and the CDMC framework,” said John Bottega, president of EDM Council. “Google is advancing cloud adoption across all industries. Now as a CDMC Certified Cloud Solution, their clients can have the added certainty that Google’s architecture has the key controls and accepted best practices in place to protect their data in the cloud.”  

Introducing CDMC

The CDMC framework, developed and published by EDM Council, provides a set of data management capabilities, standards, and best practices for securing their cloud implementations. Contributors to the framework include large global enterprises across regulated industries, major cloud service providers, technology service organizations, and advisory firms. 

The EDM Council also provides a data management assessment framework which includes a framework composed of 14 key controls and corresponding assessment procedures, which are used to validate that sensitive data is being managed effectively. To become a CDMC Certified Cloud Solution, the Google Cloud team designed, implemented, and documented a reference architecture which met the control requirements and was then assessed by KPMG LLP.

Using the solution, customer data assets are automatically classified and tagged with business metadata, their lifecycle is managed, and a reporting engine that proactively scans and publishes findings provides security administrators information about misconfigurations and security issues via a single dashboard.

Who should use this framework?

• CDOs and CISOs: The CDMC framework provides a systematic approach to handling sensitive data in the cloud and is a good starting point for chief digital officer-level discussions around what governance and security controls should be applied to different types of sensitive data. The Google Cloud CDMC assets can help with determining practical scope and efforts needed to implement the CDMC controls within your organization.
• Data platform architects and engineers: The Google Cloud reference architecture provides reusable patterns that can be adopted and customized to suit the particular needs of your organization, as well as your existing architecture and technology stack. 
• Data owners and data stewards: Once implemented, the resulting classification, automation, findings, and reports should reduce the manual burden of effectively governing sensitive data at scale.

Architecture

The architecture combines a number of Google Cloud’s services with built-in platform capabilities and data-protection services to protect data at scale. 

These services include:

• BigQuery, which can fully manage a serverless data warehouse that enables scalable analysis for petabytes of data.
• Dataplex’s Data Catalog, which can fully manage highly scalable data discovery and metadata management with built-in data lineage features.
• Cloud Data Loss Prevention, which provides tools to classify and mask sensitive data.
• VPC Service Controls, which defines a security perimeter around Google Cloud resources to mitigate data exfiltration risks.
• Looker Studio, which provides a sample dashboard to visualize the overall health of the environment.

Additionally, the architecture leverages: 

• Secure Data Warehouse Blueprint, which adheres to practices for data governance when creating, deploying, and operating a data warehouse in Google Cloud.
• Tag Engine, which automates the process of creating and populating metadata tags in Data Catalog.

The diagram below highlights the Google Cloud services used and how they mapped to the 14 CDMC key controls:

Further information

To get started, Google Cloud customers can: 

• Read our whitepaper that describes the architecture and controls
• Download and deploy the solution via our GitHub repository
• Read more about CDMC and its Key Controls Framework
• Read more about the EDM Council

In cybersecurity, speed matters. Whether a security analyst is trying to understand the details of an alert that was triggered by an indicator of compromise (IoC), or find additional context for a suspicious asset, speed is often the critical factor that will help thwart a cyberattack before threat actors are able to inflict damage.

With speed in mind, we are pleased to announce the general availability of our new investigative experience in Chronicle Security Operations. We are continuing to deliver on our mission to bring the power of Google to security operations and are raising the bar for search and the investigative experience in the SOC.

With this release, SecOps teams will be able to harness Chronicle’s lightning-fast search across any form of structured data. Additionally, the new investigation experience can provide greater flexibility to pivot and drill-down when conducting complex, open-ended threat investigations and surface insights quickly and easily.

Our Unified Data Model (UDM) schema, with its built-in flexibility that can effectively handle a wide variety of security related events, is at the heart of Chronicle’s powerful search. We have scaled this capability by optimizing query responses across structured data. Additionally, analysts can investigate large datasets and build complex queries with a new and intuitive user experience. With user personalization enhancements, analysts can quickly access saved searches and top queries in their environment to improve routine SOC workflows.

With the new investigative experience, security teams can:

• Drive faster threat understanding with an interactive event results timeline that helps eliminate unnecessary long wait times by streaming results as they are processed to quickly begin threat analysis
• Use enhanced context and operationalize relevant data for threat analysis with one-click filter-to-query conversion
• Personalize the analyst experience with saved search and search history functions for quicker analyst knowledge recall
• Power threat investigation and hunting with a new, improved, highly performant UDM search

Let’s look at an example of how to use the reimagined investigative experience and our new broader, faster search.

In our use-case, a security analyst is investigating a curated detection alert for potentially suspicious behavior on a Windows environment. Additionally, there is a low prevalence domain from host “win-dc-01” with ip “10.166.0.3”. To investigate further, let’s open the UDM Search page and construct a query containing the host and IP information along with destination information of the domain the host was contacting (edge.microsoft.com). Over 70,000 events stream into the investigation interface providing the analyst an immediate picture of data surrounding their alert.

The new interactive events timeline can provide a clear picture of event trends over time with key statistical data which can be easily filtered. Additionally, with the new quick filters, the analyst is able to easily filter out hosts that are known-good to get pertinent information about the domain.

Analyzing value aggregations present in the filter panel, automatically generated by Chronicle, enables analysts to domain values of highest interest, and quickly determine that approximately 800 events were present in the last week that related to edge.microsoft.com URL. Since Microsoft Edge is disallowed in the organization, there should not be any outbound traffic to this type of destination.

As a final step before orchestrating a response in Chronicle SOAR’s case management, the analyst can save their search to quickly recall the steps they took in the future for related investigations.

We have already seen our customers use these new capabilities in preview to build new use cases, accelerate existing threat hunting workflows, and drive faster threat response. We will continue our mission to bring Google speed, scale, and intelligence to the investigative experience, expediting “time to aha” for security analysts, and driving better, faster responses.

Ready to put Chronicle to work in your Security Operations Center? Contact Google Cloud sales or your customer success CSM team. You can also learn more about all these new capabilities in Google Chronicle in our product documentation.

Over the past two decades, Google has innovated to build some of the largest and most secure computing systems in the world. This scale requires us to deliver pioneering approaches to cloud security, which we pass on to our Google Cloud customers. We are committed to solving hard security problems like only Google can, as the tip of the spear of innovation and threat intelligence.

Today we’re excited to share the next step in this journey with the completion of our acquisition of Mandiant, a leader in dynamic cyber defense, threat intelligence and incident response services. Mandiant shares our cybersecurity vision and will join Google Cloud to help organizations improve their threat, incident and exposure management.

Combining Google Cloud’s existing security portfolio with Mandiant’s leading cyber threat intelligence will allow us to deliver a security operations suite to help enterprises globally stay protected at every stage of the security lifecycle. With the scale of Google’s data processing, novel analytics approaches with AI and machine learning, and a focus on eliminating entire classes of threats, Google Cloud and Mandiant will help organizations reinvent security to meet the requirements of our rapidly changing world.

We will retain the Mandiant brand and continue Mandiant’s mission to make every organization secure from cyber threats and confident in their readiness.

Context and threat intelligence from the frontlines

Our goal is to democratize security operations with access to the best threat intelligence and built-in threat detections and responses. Ultimately, we hope to shift the industry to a more proactive approach focused on modernizing Security Operations workflows, personnel, and underlying technologies to achieve an autonomic state of existence – where threat management functions can scale as customers’ needs change and as threats evolve.

Today Google Cloud security customers use our cloud infrastructure to ingest, analyze and retain all their security telemetry across multicloud and on-premise environments. By leveraging our sub-second search across petabytes of information combined with security orchestration, automation and response capabilities, our customers can spend more time defending their organizations.

The addition of Mandiant Threat Intelligence—which is compiled by their team of security and intelligence individuals spread across 22 countries, who serve customers located in 80 countries—will give security practitioners greater visibility and expertise from the frontlines. Mandiant’s experience detecting and responding to sophisticated cyber threat actors will offer Google Cloud customers actionable insights into the threats that matter to their businesses right now. We will continue to share groundbreaking Mandiant threat research to help support organizations, even for those who don’t run on Google Cloud.

Advancing shared fate for security operations

Google Cloud operates in a shared fate model, taking an active stake in the security posture of our customers. For security operations that means helping organizations find and validate potential security issues before they become an incident.

Detecting, investigating and responding to threats is only part of better cyber risk management. It’s also crucial to understand what an organization looks like from an attacker’s perspective and if an organization’s cybersecurity controls are as effective as expected.

By adding Mandiant’s attack surface management capabilities to Google Cloud’s portfolio, organizations will be able to continually monitor assets for exposures, enabling intelligence and red teams to move security programs from reactive to proactive to understand what’s vulnerable, misconfigured and exposed.

Once an organization’s attack surface is understood, validating existing security controls is critical. With Mandiant Security Validation, organizations will be able to continuously validate and measure the effectiveness of their cybersecurity controls across cloud and on-premise environments.

Transforming security operations and incident response

Security leaders and their teams often lack the resources and expertise required to keep pace with today’s ever changing threats. Organizations already harness Google’s security tools, expert advice and rich partner ecosystem to evolve their security program. Google’s Autonomic Security Operations also serves as a prescriptive solution to guide our customers through this modernization journey.

With the addition of Mandiant to the Google Cloud family, we can now offer proven global expertise in comprehensive incident response, strategic readiness and technical assurance to help organizations mitigate threats and reduce business risk before, during and after an incident.

In addition, Google Cloud’s security operations suite will continue to provide a central point of intelligence, analysis and operations across on-premise environments, Google Cloud and other cloud providers. Google Cloud is also deeply committed to supporting our technology and solution partners, and this acquisition will enable system integrators, resellers and managed security service providers to offer broader solutions to customers.

Comments on the news

“The power of stronger partnerships across the cybersecurity ecosystem is critical to driving value for clients and protecting industries around the globe. The combination of Google Cloud and Mandiant and their commitment to multicloud will further support increased collaboration, driving innovation across the cybersecurity industry and augmenting threat research capabilities. We look forward to working with them on this mission.” – Paolo Dal Cin, Global Lead, Accenture Security

“Google’s acquisition of Mandiant, a leader in security advisory, consulting and incident response services will allow Google Cloud to deliver an end-to-end security operations suite with even greater capabilities and services to support customers in their security transformation across cloud and on-premise environments.” – Craig Robinson, Research VP, Security Services, IDC

“Bringing together Mandiant and Google Cloud, two long-time cybersecurity leaders, will advance how companies identify and defend against threats. We look forward to the impact of this acquisition, both for the security industry and the protection of our customers.” – Andy Schworer, Director, Cyber Defense Engineering, Uber

We welcome Mandiant to the Google Cloud team, and together we look forward to helping security teams achieve so much more in defense of their organizations. You can read our release and Kevin Mandia’s blog for more on this exciting news.