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Google Cloud Platform Blog 09/16/2019 10:45
For decades, organizations built and ran applications in their own on-premises data centers. Then, they started deploying and running applications in the cloud. But, for most enterprises, the thought of moving all-in to the cloud was too daunting. They worried they would need different developers and tools for each environment, and that they wouldn’t have a consistent management interface to ensure the environments were compliant with their security policies. To address these challenges, we introduced, a services platform that brings applications into the 21st century, with the flexibility to run in any environment—whether it’s cloud-native or based on virtual machines. Today, we’re announcing new Anthos capabilities to further simplify you.
Google Cloud Platform Blog 09/13/2019 14:00
Editor’s note: Today we hear from Zohaib Ali Khan, head of mobile financial services, and Nadir Ikram, technical lead at the National Bank of Pakistan (NBP), the country’s largest government-owned bank. Read on to learn more about how NBP uses APIs to help implement digital banking and reduce the burden of legacy manual processes. NBP, Pakistan’s largest government-owned bank, serves private and commercial customers and also acts as the government treasury bank. This means that it handles all government transactions—including disbursements and cash collection. In the past, every government transaction had to be handled physically through the NBP branch network. But in a populous country like Pakistan, managing the huge volume of financial t.
Google Cloud Platform Blog 09/13/2019 12:00
Editor's note: Today we hear from Dang Nguyen, API Platform Product Owner at Experian, on how the company uses the Apigee API management platform to digitally transform from a traditional credit bureau to a true technology and software provider. Read on to learn how Experian uses APIs to help businesses make smarter decisions and individuals take financial control. Chances are, when you think of you think of a traditional credit bureau that provides credit reports. But Experian has transformed into a true technology and software provider. We gather, analyze, and process data in ways that other companies just can’t. Businesses use this data to make smarter decisions about credit and lending, as well as to prevent identity fraud and crime. We.
Google Cloud Platform Blog 09/13/2019 12:00
Editor’s note: Today we’re hearing from the founder of , a digital intelligence platform that analyzes huge amounts of digital customer data to improve the customer experience, enhance sales, and increase loyalty. The company credits a huge leap in innovation—along with a 10-fold increase in business—to their decision to adopt Google Cloud. Here’s more detail on how Quantum Metric uses Google Cloud’s BigQuery. At Quantum Metric, we’re in the business of bringing our customers business insights that are based on customer experience data and analytics for mid-market and Fortune 500 companies. Our software, powered by big data, machine intelligence, and Google Cloud, helps our customers identify, quantify, prioritize and measure opportunities
The cloud has made it possible for audiences to find the content they love anywhere, on any device, and as a result many broadcasters are looking to the cloud to help them grow and meet customer needs. Broadcasters are using the cloud to streamline content management workflows, modernize their video delivery infrastructure, and develop deeper relationships with audiences through data. We want to help broadcasters do exactly that, which is why we’ve worked with media and entertainment companies across the world to help them transform their workflows and bring their end users the best possible viewing experience across a multitude of devices. We’ve been incredibly inspired by all the ways Google Cloud customers like Sky, Viacom, Dish Network
Google Cloud Platform Blog 09/12/2019 09:00
Compute Engine instances running on (GCP) can scale up and down quickly as needed by your business. As your fleet of instances grows, you’ll want to ensure that you have enough Compute Engine quota for growth over time and that you understand your resource usage and costs. At scale, gaining a single view across projects and products requires comprehensive monitoring, and you’ll want to be able to track and manage all your cloud resources. It’s also worth keeping in mind that several of our GCP managed services, such as Cloud Dataflow, Cloud Dataproc, Google Kubernetes Engine, and managed instance groups, all provide autoscaling. That means they scale Compute Engine instances up or down based on the processing load and therefore aren’t stati.
Google Cloud Platform Blog 09/12/2019 09:00
(CNNs) are the foundation of recent advances in image classification, object detection, image segmentation, and many other computer vision applications. However, practitioners often encounter a problem when they try to train and run state-of-the-art computer vision models on larger input images: their CNN no longer fits on a single accelerator chip! To overcome this limitation, Cloud TPUs now provide a new that makes it possible to split up a single model across several TPU chips to process much larger input data sizes. This technique is general enough to handle large 2D images as well as 3D volumes, which makes it valuable for applications ranging from object detection for autonomous navigation to analysis of 3D medical scans. For example,
Google Cloud Platform Blog 09/12/2019 09:00
Providing reliable data services that you can trust to serve your data is the most important goal for our database team here at (GCP). That’s why we put money on the table in the form of availability service-level agreements (SLAs). We’re pleased to announce that all Cloud Spanner instances (not just those of three nodes or more) are now covered under the SLA. Cloud Spanner now supports 99.99% monthly uptime percentage for all regional instances and 99.999% monthly uptime percentage for all multi-region instances under the , regardless of instance size. How is this achieved? Each regional Cloud Spanner node is backed by three replicas (each in a different availability zone), and each multi-region Cloud Spanner node has five or more replicas.
Google Cloud Platform Blog 09/11/2019 19:00
This the second blog in our six part series on how to use Cloud Security Command Center. In our , we looked at how to enable Cloud Security Command Center and how it can improve your cloud security posture. Today’s web applications are developed at a rapid pace, and that pace is only getting faster. This makes it difficult to know if your web apps have vulnerabilities and how to fix them before they hit production. We recognize this problem, and it’s why we developed Cloud Web Security Scanner, a built-in feature in that allows you to detect vulnerabilities—including cross-site scripting or outdated libraries—in GKE, Compute Engine, and App Engine. In this blog, we’ll walk through how to get started with Cloud Web Security Center, with the
Google Cloud Platform Blog 09/11/2019 09:00
Editor’s note: Today we’re hearing from , an event-based ticketing and marketing platform and a division of . They moved to Google Cloud so they could develop new features faster, gather and act on data insights, and bring customers a great online experience. At Universe, we serve customers day and night and are always working to make sure they have a great experience, whether online or at one of our live events. Our technology has to make that possible, and our legacy systems weren’t cutting it anymore. What we needed was a consistent, reliable infrastructure that would help our internal teams provide a fast and innovative ticket-buying experience to customers. With our data well-managed, we could free up time for our developers to bring n.
Google Cloud Platform Blog 09/10/2019 12:00
provides open source data and analytic processing for data engineers and data scientists who need to process data and train models faster at scale. However, as enterprise infrastructure becomes increasingly hybrid in nature, machines can sit idle, single workload clusters continue to sprawl, and open source software and libraries continue to become outdated and incompatible with your stack. It’s critical that Cloud Dataproc continues to empower data professionals to focus more on workloads than infrastructure by combining the best of cloud and open source. We’re happy to announce of Cloud Dataproc for Kubernetes so that we can continue to support this vision. With this announcement, we are bringing enterprise-grade support, management, and
Google Cloud Platform Blog 09/10/2019 12:00
is Google Cloud’s fully managed Apache Hadoop and Spark service. The mission of Cloud Dataproc has always been to make it simple and intuitive for developers and data scientists to apply their existing tools, algorithms, and programming languages to cloud-scale datasets. Its flexibility means you can continue to use the skills and techniques you are already using to explore data of any size. We hear from enterprises and SaaS companies around the world that they’re using Cloud Dataproc for data processing and analytics. Cloud Dataproc now offers alpha access to Spark jobs on Google Kubernetes Engine (GKE). () This means you can take advantage of the latest approaches in machine learning and big data analysis (Apache Spark and Google Cloud) t.
Google Cloud Platform Blog 09/10/2019 10:00
Last year, we published a blog post and demonstrated on Google Compute Engine. Since then, there have been a number of important developments. First, Microsoft announced . Second, with support for Windows nodes and Windows containers. Supporting Windows workloads and helping you modernize your apps using containers and Kubernetes is one of our top priorities at Google Cloud. Soon after the Microsoft and Kubernetes announcements, we added support for Windows Server 2019 in Compute Engine and . Given this expanded landscape for Windows containers on Google Cloud, let’s take a fresh look at how best to deploy and manage them. In this first post, we’ll show you how to deploy an app to a Windows container on Windows Server 2019 on Compute Engine.
Google Cloud Platform Blog 09/10/2019 09:00
With virtually unlimited storage and compute resources, the cloud has emerged as the prime location for enterprises doing large-scale big data and machine learning projects. Enterprises need ever more sophisticated technology to quickly innovate with data projects in the cloud, without compromising ease of use, scale, and security. At Google Cloud, we’re building cloud infrastructure that’s flexible and open-source-centric to meet customer needs. Our partners are essential to our mission of helping customers grow their tech capabilities and their businesses. Qubole, a Google Cloud Platform (GCP) partner, offers an integrated cloud-native data analytics platform. Qubole provides GCP users with a unified, self-service platform where data scie.
Google Cloud Platform Blog 09/09/2019 10:00
The resolves customer support cases. We also spend a portion of our time improving the supportability of Google Cloud services so that we can solve your cases faster and also so that you have fewer cases in the first place. The challenges of improving supportability for the large, complex, fast-changing distributed system that underpins Google Cloud products have led us to develop several tools and best practices. Many challenges remain to be solved, of course, but we’ll share some of our progress in this post. Defining supportability. The term “supportability” is : it’s the speed with which a problem in a product can be fixed. But we wanted to go further and redefine supportability in a way that encompasses the whole of the customer techni.
Google Cloud Platform Blog 09/09/2019 10:00
Where workloads go, attackers follow. As more organizations adopt containers and deploy sensitive workloads with Kubernetes, there are new container-specific surface areas that need to be hardened. Today, we are announcing in beta, which provides strong, verifiable node identity and integrity to increase the protection of your (GKE) nodes. A compromised Kubernetes node gives malicious actors a wide range of opportunities for attack. For example, one potential attack on a Kubernetes node can give adversaries the opportunity to gain (persistent) access to valuable user code, compute and/or data. This isn’t just a —a security researcher . In this case, by exploiting how credentials are bootstrapped for a worker node, the researcher got full ac.
Google Cloud Platform Blog 09/09/2019 10:00
If you run any kind of internet service, you know that production incidents happen. No matter how much robustness you’ve engineered in your architecture, no matter how careful your release process, eventually the right combination of things go wrong and your customers can’t effectively use your service. You work hard to build a service that your users will love. You introduce new features to delight your current users and to attract new ones. However, when you deploy a new feature (or make any change, really), it increases the risk of an incident; that is, something user-visible goes wrong. Production incidents burn customer goodwill. If you want to grow your business, and keep your current users, you must find the right balance between rel.
Google Cloud Platform Blog 09/09/2019 10:00
Many of the world’s largest enterprises run their businesses on SAP. As these companies drive toward digital transformation and plan for the upgrade to S/4HANA, they are increasingly looking to the cloud to support their mission critical workloads. One of the main advantages of the cloud is its flexibility. Whether enterprises are undergoing substantial organic growth, expanding their portfolio, or contemplating a merger, they want the peace of mind that they have the room to grow and expand as needed. To help more enterprises scale and grow their SAP HANA workloads, today we’re expanding our support for larger SAP deployments through a new set of large-memory machine types. We’ve added two new machine types to our VM portfolio, enabling cu.
Google Cloud Platform Blog 09/05/2019 11:00
The AI ecosystem has been expanding at a rapid pace, and shows no signs of slowing down. Customers told us about the challenges they faced managing their growing number of ML assets and preventing silos and redundant work and it inspired us to develop to help foster collaboration and reuse of assets like notebooks, trained models, and ML pipelines. In April, we the open beta of AI Hub, and we have been constantly working to improve it. Today, we’re happy to announce that we’re releasing a number of new and exciting features to make collaboration for data science and ML teams even easier, and to enable GCP users to build on each other’s work. “At Descartes Labs, we build models to predict how changes on the earth impact our customers, their

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