Today, we’re pleased to announce the general availability of Ubuntu Pro images on Google Cloud, providing customers with an improved Ubuntu experience, expanded security coverage, and integration with critical Google Cloud features. In partnership with Canonical, we’re making it even easier for customers that have fully embraced open source to ensure security and compliance for their most mission-critical and enterprise workloads.

With Ubuntu Pro on Google Cloud, you  now have access to features like:

• 10-year lifetime security updates – Canonical backs Ubuntu Pro for 10 years with security updates and a guaranteed upgrade path.
• FIPS & CC-EAL2 certification – Ubuntu Pro includes components that meet requirements from entities like FedRAMP, HIPAA, ISO, and PCI.
• Open-source security coverage – Protect your most important open-source workloads including MongoDB, Apache Kafka, Redis, NGINX, and PostgreSQL.
• Multi-version availability – Pro images are available for the three most popular Ubuntu Server distributions: 16.04 LTS, 18.04 LTS, and 20.04 LTS.
• Kernel Livepatch – Kernel patches are delivered immediately without having to reboot your VMs.
• Optional CIS and DISA STIG profiles – Choose from two leading profiles to harden your environment according to industry benchmarks.
• Cloud-based pricing – Ubuntu Pro does not require a contract, and pricing tracks with the underlying compute cost depending on the instance type.

Extended Security Maintenance (ESM) for Ubuntu 16.04 LTS with Ubuntu Pro

Availability of Ubuntu Pro images is especially important if you’re an Ubuntu 16.04 LTS customer and want extended security maintenance (ESM) for your virtual machines but don’t want to upgrade to Ubuntu 18.04 LTS or Ubuntu 20.04 LTS versions immediately. ESM is included with Ubuntu Pro 16.04. You can move your workloads from Ubuntu 16.04 LTS VM instances to Ubuntu Pro 16.04 instances to continue receiving ESM and all the above-mentioned benefits, without having to test your applications on a new version of the OS.

Gojek has evolved from offering just ride-hailing to a suite of more than 20 services today, serving everyday solutions for millions of users across Southeast Asia.

“We needed more time to comprehensively test and migrate our Ubuntu 16.04 LTS workloads to Ubuntu 20.04 LTS, which would mean stretching beyond the standard maintenance timelines for Ubuntu 16.04 LTS. With Ubuntu Pro on Google Cloud, we now have the ability to postpone this, and in moving our 16.04 workloads to Ubuntu Pro, we benefit from its live kernel patching and improved security coverage for our key open source components.”—Kartik Gupta, Engineering Manager for CI/CD & FinOps at Gojek

“With the launch of Ubuntu Pro on Google Cloud, we build on our joint investments with Google to optimize Ubuntu performance on Google Cloud, and add comprehensive security patching and Long Term Support for another 30,000 open source packages—the widest range of security-maintained open source on the planet,” said Mark Shuttleworth, CEO of Canonical. “As the world moves to open source for everything, Canonical offers the safety net of security maintenance that enterprises count on to unleash their developers.”

Getting started

Getting started with Ubuntu Pro on Google Cloud is simple. You can now purchase these premium images directly from Google Cloud by selecting Ubuntu Pro as the operating system straight from the Google Cloud Console.

To learn more about Ubuntu Pro on Google Cloud, please visit the documentation page and read the announcement from Canonical.

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

At AirAsia, we operate a fleet of more than 270 aircraft across 23 markets, fly to more than 150 destinations and carry 100m guests each year. We’ve also been named the world’s best low-cost carrier for 11 years running. To accomplish all of this, we rely heavily on our 22,000 Allstars (employees). As AirAsia co-founder Tony Fernandes likes to say, “it has always been about the people.” 

In my role as CIO, it’s critical that I give our Allstars the tools and technology they need to get their jobs done, while at the same time ensuring that our company’s data is protected and secure. While this is challenging enough in normal circumstances, we’re also in the midst of rapidly moving from legacy on-premises technologies to the cloud. Google Cloud has been a critical partner for us on this journey.

Identity challenges
AirAsia, like many other enterprises, has relied on a legacy on-premises directory for many years. As our company has quickly grown and expanded to new markets and regions, we’ve had to manage multiple servers across a number of on-premises data centers and the public cloud, which has proved costly and time-consuming.

Our Allstars, located all across Asia, need to easily access a number of legacy on-premises apps in addition to a growing number of SaaS apps. As a business, we also needed a more seamless integration between our HR system of record and our identity solution for user provisioning and lifecycle management. Solving these challenges with our existing on-premises directory was simply not feasible for us.

In recent years, we partnered with Google Cloud to help drive our digital transformation, including moving dozens of workloads and apps to Google Cloud Platform (GCP), deploying G Suite as our collaboration and productivity solution for all of our employees, and replacing thousands of Windows laptops with fast and secure Chromebooks.

We brought up our identity concerns with the Google Cloud team, and after a number of conversations, we decided to deploy Cloud Identity, Google’s cloud-based identity, and access management solution, to help address the identity challenges we were facing. 

Why Cloud Identity for AirAsia?
We ended up choosing Cloud Identity for a few key reasons. Here at AirAsia, we are eager to move to the cloud as quickly as possible, and moving identity management to the cloud is a key enabler of this and our broader digital transformation. Managing identities from the cloud also enables us to have a single identity and set of credentials for each employee, which they can use to access all of the applications they need to be productive, both in the cloud and on-premises. 

In addition, deploying Cloud Identity is a key step towards enabling the BeyondCorp (or zero trust) security model, which we feel is the best approach to strengthen our security posture and fight modern threats. Cloud Identity also integrates seamlessly with our existing technologies, which includes not only Google Cloud products like GCP, G Suite, and Chrome OS, but also third-party tools like Citrix, Papercut, and others.

And finally, Cloud Identity offered us significant cost and resource savings. With Cloud Identity in place, our IT department can spend less time worrying about managing multiple on-premises directory servers and can instead focus on delivering value to our Allstar employees.

Google Cloud provides multiple layers of security to help customers stay ahead of evolving threats and keep their cloud workloads safe. Today at our annual Security Summit, we are excited to announce the general availability of Secure Web Proxy, a new cloud-first network security offering that provides web egress traffic inspection, protection, and control. Secure Web Proxy (Cloud SWP) can help networking and security teams implement Zero Trust networking principles, discover malicious activity, and support forensic investigations

How Secure Web Proxy works

You configure workloads to use Secure Web Proxy as a gateway. Web requests can originate from virtual machine (VM) instances, containers, serverless environments, and workloads outside of Google Cloud connected by Cloud VPN or Cloud Interconnect. Policies and rules in Cloud SWP will be applied to traffic sent from these workloads to the internet.

Cloud SWP helps enable organizations to enforce granular access policies, limiting egress web traffic based on source, identities, destination, or request types. With Cloud SWP you can create policies with Google Cloud Identity Access Management (IAM) context using service accounts and secure tags to block egress. For example, you can set a policy to limit a service account to sending traffic to a specific outbound destination. 

Secure Web Proxy offers a scalable TLS inspection service that lets you intercept TLS traffic, inspect the encrypted request, and enforce your policies. Cloud SWP integrates with Cloud Logging to record metrics and transaction logs for requests handled by the proxy.

Common use cases for Secure Web Proxy

Many organizations employ a proxy like Cloud SWP to programmatically restrict workload access to only trusted external web services. 

You can also use Cloud SWP to monitor outbound access. The proxy identifies traffic that doesn’t conform to policy and logs it to Cloud Logging. This allows you to monitor internet usage, discover and disrupt threats on your network by spotting command and control traffic or anomalous data transfers. Logs can be also used in forensics to investigate security events and incidents involving egress web traffic. 

Operational benefits

Secure Web Proxy is another example of how Google Cloud continues to deliver built-in, cloud-first security capabilities that offer operational efficiencies for our customers.

Cloud SWP is easy to deploy and manage because it is a managed service. Unlike frequently deployed proxy solutions, it does not require users to configure virtual machines (VMs) to run and scale the proxy. Security patching is handled automatically. As your business and outbound traffic grows, Cloud SWP takes care of growing your proxy infrastructure for you. 

Secure Web Proxy can also help make cloud migrations more seamless. If you are using an on-premises proxy, you can easily port the existing proxy’s policies to Cloud SWP when you migrate the app, maintaining the same egress protection in the cloud as you had on-premises.                       

Customer testimonials

Preview customers validated the operational and security value of implementing Cloud SWP:

“Google’s Secure Web Proxy is a powerful tool that can help businesses of all sizes protect their cloud workloads from online threats. By using the granular policy controls and TLS inspection, we are ensuring that our cloud applications only access approved external destinations. Additionally we are able to comply with data security regulations,” said David Saleh, director, Cloud Architecture and Application Security, ATB Financial.

“Secure Web Proxy has helped us to improve our security in Google Cloud. We are now able to filter outbound HTTP and HTTPS traffic from our applications. In addition, having a native solution will allow us to replace the VM-based solution we currently have, providing us with cost savings and continuing to deliver on our strategy of replacing products with cloud native services,” said Roberto Vega, cloud analyst, Carrefour.

Getting started with Secure Web Proxy

You can get started with Cloud SWP by visiting our documentation page to learn more about Cloud SWP prerequisite requirements and configuration options. If you want to quickly evaluate Cloud SWP for your cloud environment, use the SWP evaluation guide for step-by-step instructions. Be sure to check out all our sessions at this year’s Google Cloud Security Summit.

Many organizations require effective processes and techniques for removing or obfuscating certain sensitive information in the data they store. An important tool to achieve this goal is de-identification. Defined by NIST as a technique that “removes identifying information from a dataset so that individual data cannot be linked with specific individuals. De-identification can reduce the privacy risk associated with collecting, processing, archiving, distributing or publishing information.

Always striving to make data security easier, today we are happy to announce the availability of a de-identification action for our Cloud Storage inspection jobs. Now, you can de-identify Cloud Storage objects, folders, and buckets without needing to run your own pipeline or custom code. Additionally, we have enhanced our transforms by adding a new dictionary replacement method that can help you achieve stronger privacy protection – especially with unstructured data you might store like customer support chat logs.

The “De-identify findings” Action

The “de-identify findings” action for Cloud DLP inspection jobs is a fully managed feature that creates a de-identified copy of the data objects that are inspected. This means that you can inspect a Cloud Storage bucket for sensitive data like Personal Identifiable Information (PII) and then create a redacted copy of these objects all with a few clicks in the Console UI. No need to write custom code or manage complex pipelines and since it’s fully managed, it will auto-scale for you without you needing to manage quota.

This new action supports the following data types:

• Text files
• Comma- or tab-separated values
• Images (see regional limitations)

Once enabled, the DLP job will perform an inspection of the data and produce a de-identified copy of all supported files into the output bucket or folder.

You can also use the new de-identify action on Job Triggers to automatically de-identify new content as it appears on a recurring schedule. This is useful for creating a workflow with a safe drop zone for incoming files that need to be de-identified before being made accessible.

What can automatic De-identification do?

Cloud DLP provides a set of transformation techniques to de-identify sensitive data while attempting to make the data still useful for your business. These techniques include:

• Redaction: Deletes all or part of a detected sensitive value.
• Replacement: Replaces a detected sensitive value with a specified surrogate value.
• Masking: Replaces a number of characters of a sensitive value with a specified surrogate character, such as a hash (#) or asterisk (*).
• Crypto-based tokenization: Encrypts the original sensitive data value using a cryptographic key. Cloud DLP supports several types of tokenization, including transformations that can be reversed, or “re-identified.”
• Bucketing: “Generalizes” a sensitive value by replacing it with a range of values. (For example, replacing a specific age with an age range, or temperatures with ranges corresponding to “Hot,” “Medium,” and “Cold.”)
• Date shifting: Shifts sensitive date values by a random amount of time.
• Time extraction: Extracts or preserves specified portions of date and time values.

New Dictionary Replace method

When a sensitive data element is found, dictionary replacement replaces it with a randomly selected value from a list of words that you provide. This transformation method is especially useful if you want the redacted output to have more realistic surrogate values.

Consider the following example: You collect customer support chat logs as part of providing service to your customers. These support chat logs contain various types of Personal Identifiable Information (PII) including people’s names and email addresses. Cloud DLP can find and de-identify the sensitive elements with static replacements such as “[REDACTED]” to help prevent someone from seeing this sensitive data.

With the new dictionary replacement method you can instead replace these findings with a randomly selected value from a dictionary. This dictionary replacement provides two key benefits over static replacement:

1. The resulting output can look more realistic
2. Because the output looks more realistic, it can help conceal any residual names (a privacy de-identification technique sometimes referred to as “hiding in plain sight”)

An example of this:

Input:

[Agent] Hi, my name is Jason, can I have your name?

[Customer] My name is Valeria

[Agent] In case we need to contact you, what is your email address?

[Customer] My email is v.racer@example.org

[Agent] Thank you. How can I help you?

De-identified Output:

[Agent] Hi, my name is Gavaia, can I have your name?

[Customer] My name is Bijal

[Agent] In case we need to contact you, what is your email address?

[Customer] My email is happy.elephant44@example.org

[Agent] Thank you. How can I help you?

As you can see in the output, the names and email addresses have been replaced with a random value that both protects the original sensitive information but also makes the output look more realistic. This can make the data more useful and help “hide” any residual PII.

Next Steps:

To learn more about De-Identification check out our Technical Docs, try De-identification of Storage in the Cloud Console and Watch a recent Google I/O talk on De-identification of data.