Cloud KMS with Cloud Storage: Better Performance for High-intensity Workloads - Build What's Next
Blog

Cloud KMS with Cloud Storage: Better Performance for High-intensity Workloads

3280

Of your peers have already read this article.

2:30 Minutes

The most insightful time you'll spend today!

Organizations have been securing data on Cloud Storage with Cloud KMS to take advantage of its encryption. Read the post to find out the latest developments in encryption offerings to boost performance, security and workload scalability!

Encryption is critical for securing sensitive data while it is stored and transits the cloud. Today, Cloud Storage encrypts data server-side with standard Google-managed encryption keys by default, and can also encrypt data with customer-managed encryption keys that are stored and managed by Cloud Key Management Service (Cloud KMS).

While customers have been able to secure their data on Cloud Storage with Cloud KMS keys for some time, we are always updating our encryption offerings to deliver better performance, lower costs and more capabilities that support critical business workloads. In this post, we’ll discuss some of our latest developments in this space—in particular, performance improvements for high-intensity workloads and support for customer-managed encryption keys (CMEK) for object composition

Why use Cloud KMS with Cloud Storage?

Cloud KMS enables you to centrally manage your keys in a fast and scalable way that helps to meet your security and compliance needs. Cloud KMS generates customer-managed encryption keys (CMEK) which act as an additional layer of protection on top of Google’s default encryption keys. You can set these keys on a Cloud Storage bucket as a default key, and can easily manage key rotation, replacement or disabling right within Cloud KMS.  

In addition to software-based CMEKs, Cloud Storage also supports hardware-based CMEKs hosted in hardware security modules that are FIPS 140-2 Level 3 validated as part of our Cloud HSM service. These enable you to protect your most sensitive workloads without needing to manage HSM cluster operations yourself. 

Improving KMS performance for high-intensity workloads

While Cloud HSM is often used to protect the most sensitive data for a customer, especially for those in healthcare and financial services industries, the default quota limits for cryptographic operations on Cloud HSM keys may cause performance bottlenecks for customers aiming to run high-intensity workloads when using Cloud Storage, such as analytics workloads on Hadoop.

We are making improvements to the Cloud KMS request behaviour on Cloud Storage that more effectively batches requests to Cloud KMS to reduce request bandwidth and drive down KMS billing. Identical Cloud KMS requests from Cloud Storage will be batched together for newly written objects and across all supported encryption modes in Cloud KMS, including software-backed customer-managed encryption keys. As a result of these changes, when you are using Cloud KMS you may notice faster encrypt, read and write operations for new data, deduplicated Cloud KMS audit logs and lower overall Cloud KMS charges. Customers running high-intensity workloads should see a significant reduction in throughput to KMS, leading to a reduction in KMS cryptographic operation billing costs for all types of KMS keys, as well as enabling customers to scale the throughput of their HSM-encrypted workloads.

Newly written objects encrypted with Cloud KMS will leverage these changes, whether they are encrypted using software-backed or HSM-backed CMEKs, and no configuration change is needed. If you are looking to use Cloud KMS with Cloud Storage, check out the Cloud KMS page to learn more, especially for setting up a hardware-backed HSM.

Supporting Cloud KMS for object composition

Object composition in Cloud Storage is widely used today for different types of applications, from stitching video segments together for a replay to uploading large datasets for analytics workloads. As more and more customers are leveraging Cloud Storage for these applications, we are expanding object composition capabilities to be flexible across different encryption modes.

Object composition is now supported for customer-managed encryption keys in addition to Google-managed encryption keys and customer-supplied encryption keys. This allows you to manage your own encryption keys while performing object composition for business-critical needs such as compiling sensitive financial datasets.

To compose objects that are encrypted with customer-managed encryption keys, specify the resource name of the Cloud KMS key for encrypting the composed object as a query parameter in the compose request. For the JSON API, construct the following HTTP request, while specifying the Cloud KMS key resource name for the query parameter kmsKeyName.

  POST https://storage.googleapis.com/storage/v1/b/bucket/o/destinationObject/compose

For the XML API, specify the Cloud KMS key resource name for the request header x-goog-encryption-kms-key-nameYou can also specify a Cloud KMS key when using gsutil to perform object composition. Check out our documentation to try out object composition, or to start composing objects encrypted with customer-managed encryption keys.

Get started with better encryption

Being deliberate about encryption is critical for securing your sensitive data on Cloud Storage. Whether you are composing objects or running analytics workloads, leveraging the latest encryption offerings will deliver faster performance, better security and improved workload scalability. We’re always evolving our encryption products to meet your needs and help you achieve your business goals. To get started with encryption on Cloud Storage, check out our documentation to learn more.

Blog

Taking Maps Further: New Website Experience for Product Discovery, Budgeting and Access to Dev Documentation

6653

Of your peers have already read this article.

1:30 Minutes

The most insightful time you'll spend today!

As new technologies emerge and customer preferences evolve, businesses and users of Google Maps Platform can leverage its brand new 'website experience' to explore products and solution that meet their objectives! Learn More.

For more than 15 years, developers have used Google Maps Platform to deliver location-based experiences to their end users and used location intelligence to optimize their businesses. Along this journey, we’ve made a variety of changes to better support our community as needs have changed and new industries and technologies have emerged. We started rolling out a new website experience, at https://mapsplatform.google.com, to help you better understand the products and solutions best suited to address your objectives. Plus, now you can directly connect to the developer documentation for each product to get started quickly, and you can visualize usage and associated costs to have a better idea of what to expect before getting started. 

Getting to your solution faster 

Maps, Routes, Places are building blocks that let you develop implementations for any use case. Building for specific use cases, however, typically requires using a combination of APIs and SDKs. To help you quickly understand what’s possible and what you need to build for your use case, you can now visit the solutions tab to select from a list of popular use cases or industries. Once you’ve selected a use case or industry, you’re taken to a page where you can explore relevant products, read helpful blog posts, see how other customers have deployed for similar use cases, and more.  

Find the ideal location

Direct access to developer documentation

Did you know there are more than a thousand pages of developer documentation created to help you get started, unblock you when you’re stuck, and share best practices? Now when you explore a product or solution from the Google Maps Platform website, you can easily navigate back and forth between our website and documentation. Just tap on JS, iOS, Android or API under the product name to get to the documentation you need. 

Link to documentation

Budgeting for your project

To help you calculate pricing for your project, we’ve introduced a new pricing calculator. Once you find the product and API or SDK you plan to use, pull the slider to reflect your estimated number of monthly requests. This will automatically update the “monthly cost” column for each product and API or SDK you plan to use. If your estimated monthly requests exceed the slider limit, contact our sales team to ​​learn about volume discounts that start at 20% off. 

Pricing calculator

We hope our new website makes it easier to discover our products and solutions, estimate your budget, and start building with our documentation so you can deliver helpful experiences to your users and optimize your business. 

For more information on Google Maps Platform, visit https://mapsplatform.google.com.

Blog

Cloud on Europe’s Terms: How Google Sets to Deliver Cloud Services for Driving Digital Sovereignty

5179

Of your peers have already read this article.

1:30 Minutes

The most insightful time you'll spend today!

Google Cloud's overarching goal of delivering sustainable, digital transformation for European organization will be met as per Europe's terms! After a discussion with the policy makers and customers, Google unveils ways to make it happen.

Cloud computing is globally recognized as the single most effective, agile and scalable path to digitally transform and drive value creation. It has been a critical catalyst for growth, allowing private organizations and governments to support consumers and citizens alike, delivering services quickly without prohibitive capital investment. European organizations—in both the public and private sectors—want a provider to deliver a cloud on their terms, one that meets their requirements for security, privacy, and digital sovereignty, without compromising on functionality or innovation.

Last year, we set out an ambitious vision of sovereignty along three distinct pillars: data sovereignty (including control over encryption and data access), operational sovereignty (visibility and control over provider operations), and software sovereignty (providing the ability to run and move cloud workloads without being locked-in to a particular provider, including in extraordinary situations such as stressed exits). After extensive dialogue with customers and policymakers, we are today unveiling ‘Cloud. On Europe’s Terms’. As part of  this initiative, we will continue to demonstrate our commitment to deliver cloud services that provide the highest levels of digital sovereignty, all while enabling the next wave of growth and transformation for Europe’s businesses and organizations.

Google Cloud’s baseline controls and security features offer strong protections, meet current robust security and privacy requirements, and address many customer needs. Yet each country in Europe has its own characteristics and expectations. Certain customers in Europe may require more flexibility than current public and private cloud offerings may provide. We want to deliver a platform that allows customers to deploy workloads with the desired local control, without losing the transformational benefits of the public cloud.

We are now delivering on this new vision collaboratively with trusted local technology providers in Europe, starting with T-Systems in Germany. Today, together with T-Systems, we announced a partnership to build a Sovereign Cloud offering in Germany for private and public sector organizations. The offering will become available in mid 2022 with additional features being added over time.  

In this new joint offering, T-Systems will manage sovereignty controls and measures, including encryption and identity management of the Google Cloud Platform. In addition, as part of their offering, T-Systems will operate and independently control key parts of the Google Cloud infrastructure for T-Systems Sovereign Cloud customers in Germany.

We are committed to building trust with European governments and enterprises with a cloud that meets their digital sovereignty, sustainability and economic objectives. We are starting with T-Systems today and will continue by partnering with trusted technology providers in selected markets across the region. 

Customers in other markets across Europe will be able to use these trusted partner offerings or use Google Cloud’s controls to exercise autonomous control over data access and use; exercise choice over the infrastructure that is used to process that data; and avoid cloud vendor lock-in. 

With Google Cloud, our customers also automatically benefit from sustainable business transformation on the cleanest cloud in the industry. Today, we are the largest annual corporate purchaser of renewable energy globally, and by 2030, we aim to operate entirely on 24/7 carbon-free energy in all of our cloud regions worldwide. 

We’ll continue to listen to our customers and key stakeholders across Europe who are setting policy and helping shape requirements for customer control of data. Our goal is to make Google Cloud the best possible place for sustainable, digital transformation for European organizations on their terms—and there is much more to come.

Case Study

DueDil Chooses Apigee to Leverage APIs for Customers’ Risk Monitoring with Better Insights

4845

Of your peers have already read this article.

1:30 Minutes

The most insightful time you'll spend today!

DueDil, a due diligence service provider with over 3,000 enterprise users perform risk evaluations, built a platform to map hundred millions of connections by companies. Read how Apigee's resilient and agile platform helped the company build APIs.

As their name reflects, DueDil provides due diligence services ranging from customer-specific risk evaluations and selections to customer onboarding and real-time risk monitoring for leading financial services, high-growth tech and insurance companies. Founded in 2009, the company helps more than 3,000 enterprise users from over 400 clients to not only understand with whom they’re doing business, but to do so with increased efficiency and in compliance with regulatory requirements. 

Due diligence services have evolved in recent years, both because of new regulations and new technologies supplanting legacy systems and processes, many of which relied until recently on pen-and-paper workflows or exhaustive spreadsheet work. DueDil knew this technology transformation represented an opportunity to replace manual processes with automation–but it also recognized a second opportunity: to not merely process data but also activate it by connecting information in disparate IT systems and generating data-driven insights delivered at scale.  

To capitalize on this opportunity, the company built its Business Information Graph, or B.I.G., a platform that maps approximately 300 million connections among companies. B.I.G. ingests billions of data points, and is refreshed multiple times per day, to surface unique insights about business’s relationships, such as fraud risks. The results that B.I.G. drives often speak for themselves: some DueDil customers onboard partners up to 80% faster, perform risk verification up to 18 times faster, and reduce time spent on manual portfolio checks by up to 80%. 

What powers all of this transformation? Application Programming Interfaces (APIs). 

“From a go-to-market standpoint, our product is an API,” said Denis Dorval, DueDil COO, in a recent webcast, explaining that customers can directly tap B.I.G.’s resources for themselves, and build atop them for their own needs, via DueDil’s API. 

Choosing an API management platform to deliver fast, secure, and scalable APIs

To execute on their vision of connecting B2B ecosystems for better insights and efficiency, DueDil looked for a cloud provider that could fulfill several specific criteria. They needed robust management for the APIs with which their internal developers leverage different systems for new use cases and process automations, as well as for the productized API they offer to customers. They needed sophisticated analytics and abundant processing power to crunch through billions of data points. And, they needed enterprise-grade security, scalability, and agility to underpin it all. Last but not least, the company prioritized a smooth transition; DueDil did not want the user experience to suffer as it switched providers.

“The stability of Google Cloud’s Apigee API management platform and the strength of its services stood out”, said DueDil’s Engineering Manager, Robert Cicero. 

“Apigee is a resilient and agile platform, fulfilling our need to build APIs quickly, safely, and at scale,” he remarked, noting that he appreciated that many of Apigee’s API security defense tools and policies work out-of-the-box. For instance, Apigee’s JSON threat detection policies, custom policies, and authentication and authorization processes can be deployed instantly and add minimal latency, meaning DueDil can stop security threats before they enter its network while still avoiding the risk of service lags.

Today, DueDil has five internal services that facilitate business due diligence, all exposed via Apigee. They also use Apigee’s monetization feature to drive API consumption. This said, because DueDil’s go-to-market strategy is fast-paced and client-oriented, they most often use Apigee to rapidly prototype APIs for their clients, so they can understand what a specific API would look like and how it would behave. This allows DueDil, its partners, and its customers to spend more time delivering value from insights rather than getting bogged down in building backend systems. 

Moreover, Apigee made it simpler to also connect to other Google Cloud services, such as BigQuery, Google Data Studio, and Google Cloud Storage. Apigee acts as a central nervous system among systems, giving DueDil not only the ability to connect systems and automate processes but also insight and visibility into how its B.I.G. services are being used by partners and customers. 

Plus, added Cicero, “the migration to Apigee was seamless, with arguably our biggest win being that no one knew that we had switched API management providers to Apigee.”  

Leveraging APIs to provide self-service while enforcing security and governance policies

Moving forward, DueDil plans to leverage Apigee to give staff members and clients more privileges, visibility, and opportunity to create and edit apps in a self-service manner, without needing to rely on an IT department or endure long approvals processes. Harnessing APIs to open up B.I.G. and other capabilities to more teams across the company will also allow DueDil to move faster and include more people in the innovation process. Leveraging Apigee API management capabilities, DueDil also intends to dive deeper and experiment with other Google Cloud products and services, including Cloud Function, Cloud Pub/Sub, and more.

“At the end of the day, every company goes about due diligence a little differently. The only way that we at DueDil are able to provide something that is configurable and dynamic to diverse businesses is if we use platforms that can adapt, too,” said Cicero. “Apigee gives us the agility required to create and deliver for a wide variety of businesses.”

Google Cloud, today, works across banking, capitalmarkets, insurance, and payments worldwide to solve their most challenging problems. Click here to learn more about how Google Cloud Apigee API management can help you design, secure, analyze, and scale APIs anywhere with visibility and control. To try Apigee API management for free, click here.

Blog

Announcing reCAPTCHA Enterprise’s Mobile SDK to Help Protect iOS, Android apps

4215

Of your peers have already read this article.

2:30 Minutes

The most insightful time you'll spend today!

reCAPTCHA Enterprise is Google’s online fraud detection service that leverages more than a decade of experience defending the internet. reCAPTCHA Enterprise can be used to prevent fraud and attacks perpetrated by scripts, bot software, and humans. When installed inside a mobile app at the point of action, such as login, purchase, or account creation, reCAPTCHA Enterprise can block fake users and bots while allowing legitimate users to proceed.

To provide more complete coverage for native mobile iOS and Android applications, we’re announcing the general availability of the reCAPTCHA Enterprise Mobile SDK. Designed with digital-first and mobile-first organizations in mind, the new Mobile SDK fully integrates reCAPTCHA Enterprise’s frictionless experience on end-users’ mobile devices.

Why should I use the Mobile SDK?

Unlike most web applications, iOS and Android apps run on physical devices that can provide a wealth of device telemetry to help identify fraud and bot activity. By combining both device and network signals, the new mobile SDK can better protect native mobile applications from bot attacks while unlocking the full potential of reCAPTCHA Enterprise. It provides:

  • Frictionless customer experience — no picking fire hydrants from a grid
  • Easy integration to your native mobile app with support for popular frameworks like Cocoa Pods and Swift Package Manager
  • A regularly-updated device threat model to help stay ahead of attack evolution

Protecting against fraud across all your channels

Customers will be able to leverage the new mobile SDK to implement native iOS and Android protection against the OWASP Top 10 automated attacks common on the internet, which include fraudulent account creation, financial hijacking, and credential stuffing. This is particularly important for mobile workforces and end users who use a mobile app to access products and services. Since mobile traffic surpasses web traffic in many industries, it’s even more important to implement a comprehensive mobile app protection strategy to protect against the most prevalent attacks.

Integrating the new Mobile SDK

If you’re interested in learning more about how to integrate the new Mobile SDK, check out the documentation for iOS and Android. Mobile and Web integrations leverage the same easy to understand pricing for Assessments, found here.

Blog

A Look Back on Google Cloud’s Data Analytics Development Efforts from June

5978

Of your peers have already read this article.

4:00 Minutes

The most insightful time you'll spend today!

Experts at Google Cloud delivered a slew of new features across their data analytics products, BigQuery, Dataflow, Data Fusion, and more to enhance scalability, security, speed and user-friendliness.

June is the month that holds the summer solstice, and some of us in the northern hemisphere get to enjoy the longest days of sunshine out of the entire year. We used all the hours we could in June to deliver a flurry of new features across BigQuery, Dataflow, Data Fusion, and more.  Let’s take a look!

Simple, Sophisticated, and Secure

Usability is a key tenant of our data analytics development efforts. Our new user-friendly BigQuery improvements this month include:

  • Flexible data type casting
  • Formatting to change column descriptions 
  • GRANT/REVOKE access control commands using SQL

We hope this will delight data analysts, data scientists, DBAs, and SQL-enthusiasts who can find out more details in our blog here.

Beyond simplifying commands, we also recognize that it’s equally important to have more sophistication when dealing with transactions. That’s why we introduced multi-statement transactions in BigQuery.

As you probably know, BigQuery has long supported single-statement transactions through DML statements, such as INSERT, UPDATE, DELETE, MERGE and TRUNCATE, applied to one table per transaction. With multi-statement transactions, you can now use multiple SQL statements, including DML, spanning multiple tables in a single transaction. 

This means that any data changes across multiple tables associated with all statements in a given transaction are committed atomically (all at once) if successful—or all rolled back atomically in the event of a failure. 

Multi-statement transactions for BigQuery

We also know that organizations need to control access to data, down to the granular level and that, with the complexity of data platforms increasing day by day, it’s become even more critical to identify and monitor who has access to sensitive data. 

To help address these needs,  we announced the general availability of BigQuery row-level security. This capability gives customers a way to control access to subsets of data in the same table for different groups of users. Row-level security in BigQuery enables different user personas access to subsets of data in the same table and can easily be created, updated, and dropped using DDL statements. To learn more, check out the documentation and best practices.

Row Level Security with BigQuery

Simple, Safe, and Smart

Beyond building a simpler, more sophisticated and more secure data platform for customers, our team has been focused on providing solutions powered by built-in intelligence. One of our core beliefs is that for machine learning to be adopted and useful at scale, it must be easy to use and deploy.  

BigQuery ML, our embedded machine learning capabilities, have been adopted by 80% of our top customers around the globe and it has become a cornerstone of their data to value journey.  

As part of our efforts, we announced the general availability of AutoML tables in BigQuery ML.  This no-code solution lets customers automatically build and deploy state-of-the-art machine learning models on structured data. With easy integration with Vertex AI, AutoML in BQML makes it simple to achieve machine learning magic in the background. From preprocessing data to feature engineering and model tuning all the way to cross validation, AutoML will “automagically” select and ensemble models so everyone—even non-data scientists—can use it.   

Want to take this feature for a test drive? Try it today on BigQuery’s NYC Taxi public dataset following the instructions in this blog! 

Speaking of public datasets, we also introduced the availability of Google Trends data in BigQuery to enable customers to measure interest in a topic or search term across Google Search.  This new dataset will soon be available in Analytics Hub and will be anonymized, indexed, normalized, and aggregated prior to publication. 

Want to ensure your end-cap displays are relevant to your local audience?  You can take signals from what people are looking for in your market area to inform what items to place. Want to understand what new features could be incorporated into an existing product based on what people are searching for?  Terms that appear in these datasets could be an indicator of what you should be paying attention to.

All this data and technology can be put to use to deploy critical solutions to grow and protect your business. For example,  it can be difficult to know how to define anomalies during detection. If you have labeled data with known anomalies, then you can choose from a variety of supervised machine learning model types that are already supported in BigQuery ML. 

But what if you don’t know what kind of anomaly to expect, and you don’t have labeled data? Unlike typical predictive techniques that leverage supervised learning, organizations may need to be able to detect anomalies in the absence of labeled data. 

That’s why, we were particularly excited to announce the public preview of new anomaly detection capabilities in BigQuery ML that leverage unsupervised machine learning to help you detect anomalies without needing labeled data.  

Our team has been working with a large number of enterprises who leverage machine learning for better anomaly detection. In financial services for example, customers have used our technology to detect machine-learned anomalies in real-time foreign exchange data.  

To make it easier for you to take advantage of their best practices, we teamed up with Kasna to develop sample code, architecture guidance, and a data synthesizer that generates data so you can test these innovations right away. 

Simple, Scalable, and Speedy

Capturing, processing and analyzing data in motion has become an important component of our customer architecture choices. Along with batch processing, many of you need the flexibility to stream records into BigQuery so they can become available for query as they are written.  

Our new BigQuery Storage Write API combines the functionality of streaming ingestion and batch loading into a single API. You can use it to stream records into BigQuery or even batch process an arbitrarily large number of records and commit them in a single atomic operation.

Flexible systems that can do batch and real-time in the same environment is in our DNA: Dataflow, our serverless, data processing service for streaming and batch data was built with flexibility in mind.  

This principle applies not just to what Dataflow does but also how you can leverage it—whether you prefer using Dataflow SQL right from the BigQuery web UI, Vertex AI notebooks from the Dataflow interface, or the vast collection of pre-built templates to develop streaming pipelines.

Dataflow has been in the news quite a bit recently. You might have noted the recent introduction of Dataflow Prime, a new no-ops, auto-tuning functionality that optimizes resource utilization and further simplifies big data processing. You might have also read that Google Dataflow is a Leader in The 2021 Forrester Wave™: Streaming Analytics, giving Dataflow a score of 5 out of 5 across 12 different criteria.  

We couldn’t be more excited about the support the community has provided to this platform. The scalability of Dataflow is unparalleled and as you set your company up for more scale, more speed, and “streaming that screams”, we suggest you take a look at what leaders at SkyRVU or Palo Alto Networks have already accomplished.

If you’re new to Dataflow, you’re in for a treat: this past month, Priyanka Vergadia (AKA CloudGirl) released a great set of resources to get you started. Read her blog here and watch her introduction video below!

https://youtube.com/watch?v=WRspZRG9e90%3Fenablejsapi%3D1%26

Simple structure that sticks together

We thrive to be the partner of choice for your transformation journey, regardless where your data comes from and how you choose to unify your data stack.  

Our partners at Tata Consultancy Services (TCS) recently released research that highlights the importance of a unifying digital fabric and how data integration services like Google Cloud Data Fusion can enable their clients to achieve this vision.

We also  announced SAP Integration with Cloud Data Fusion, Google Cloud’s native data integration platform, to seamlessly move data out of SAP Business Suite, SAP ERP and S4/HANA. To date, we provide more than 50 pipelines in Cloud Data Fusion to rapidly onboard SAP data.  

This past month, we introduced our SAP Accelerator for Order to Cash.  This accelerator is a sample implementation of the SAP Table Batch Source feature in Cloud Data Fusion and will help you get started with your end-to-end order to cash process and analytics. 

It includes sample Cloud Data Fusion pipelines that you can configure to connect to your SAP data source, perform transformations, store data in BigQuery, and set up analytics in Looker. It also comes with LookML dashboards which you can access on Github.

Countless great organizations have chosen to work with Google for their SAP data. In June, we wrote about ATB Financial’s journey and how the company uses data to better serve over 800,000 customers, save over CA$2.24 million in productivity, and realize more than CA$4 million in operating revenue through “D.E.E.P”, a data exposure enablement platform built around BigQuery.

Finally, if you are an application developer looking for a unified platform that brings together data from Firebase Crashlytics, Google Analytics, Cloud Firestore, and third party datasets, we have good news!  

This past month, we released a unified analytics platform that combines Firebase, BigQuery, Google Looker and FiveTran to easily integrate disparate data sources,  and infuse data into operational workflows for greater product development insights and increased customer experience. This resource comes with sample code, a reference guide and a great blog!  We hope you enjoy it. See you all next month!

https://youtube.com/watch?v=L25Vfzr2Ciw%3Fenablejsapi%3D1%26

More Relevant Stories for Your Company

Blog

Confidential Computing at Google Cloud

This blog includes content from Episode One "Confidentially Speaking” of our Cloud Security Podcast, hosted by Anton Chuvakin (Head of Solutions Strategy) and Timothy Peacock (Product Manager). You should listen to the whole conversation for more insights and deeper context.LEARN MORECloud Security Podcast - Confidentially SpeakingListen to the Cloud Security Podcast with

Case Study

AirAsia’s CIO Speaks Up: Why He Decided, What He Did

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

Blog

Building Effective Visibility into Technology Assets Used in Healthcare

When technology just works, it's easy to trust. But too often, we place our trust in technology that doesn’t deserve it. When we do this with technology to provide healthcare, we put the safety of patients and the security and reliability of our global healthcare system at risk. The institutions

Case Study

Groupe Dauphinoise Grows it Customer Base with G Suite and Google Cloud Platform

As a leading French agricultural cooperative, Groupe Dauphinoise places collaboration at the heart of its philosophy. Working with farmers in the Rhone-Alpes region, Groupe Dauphinoise takes on a diverse range of activities from agricultural production to research and development to running retail outlets. As its operations expanded and strained its

SHOW MORE STORIES