Regardless of whether your data resides on-premises, in the cloud, or a combination of both, you are vulnerable to security threats, data breaches, data loss, and more. Security is often cited as a concern for organizations who are migrating to the public cloud, but the belief that the public cloud is not secure is a myth. In fact, the leading public cloud service providers have built rigorous security capabilities to ensure that your applications, assets, and services are protected. Security in the public cloud is now becoming a driver for many organizations, but in a rapidly evolving multicloud environment, you must keep up with changes that might impact your security posture. This eBook outlines the three core recommendations for cloud security across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform.

Compiling a cloud services comparison is a daunting task in the rapidlyevolving cloud environment. There are thousands of cloud services, dozens of cloud service providers, and numerous Infrastructure-as-aService (IaaS) providers offering pay-as-you-go pricing models—each one frequently changing and upgrading their portfolios. We have chosen to limit our cloud services comparison to the top three IaaS providers providing service in the Western Hemisphere—Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP)—because, not only are these the IaaS providers most organizations are familiar with, they are also the IaaS providers whose services most organizations are likely to compare. This eBook provides an introduction to the range of services offered by the leading cloud service providers, information on regions and availability zones, a breakdown of cloud storage services, and more, to help inform you on your multicloud journey.

Regardless of whether your data resides on-premises, in the cloud, or a combination of both, you are vulnerable to security threats, data breaches, data loss, and more. Security is often cited as a concern for organizations who are migrating to the public cloud, but the belief that the public cloud is not secure is a myth. In fact, the leading public cloud service providers have built rigorous security capabilities to ensure that your applications, assets, and services are protected. Security in the public cloud is now becoming a driver for many organizations, but in a rapidly evolving multicloud environment, you must keep up with changes that might impact your security posture. This eBook outlines the three core recommendations for cloud security across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform.

Both the speed of innovation and the uniqueness of cloud technology is forcing security teams everywhere to rethink classic security concepts and processes. In order to keep their cloud environment secure, businesses are implementing new security strategies that address the distributed nature of cloud infrastructure. Security in the cloud involves policies, procedures, controls, and technologies working together to protect your cloud resources, which includes stored data, deployed applications, and more. But how do you know which cloud service provider offers the best security services? And what do you do if you’re working on improving security for a hybrid or multicloud environment? This ebook provides a security comparison across the three main public cloud providers: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). With insight from leading cloud experts, we also analyze the differences between security in the cloud and on-premises infrastructure, debunk

Today, deep learning is at the forefront of most machine learning implementations across a broad set of business verticals. Driven by the highly flexible nature of neural networks, the boundary of what is possible has been pushed to a point where neural networks outperform humans in a variety of tasks, such as classifying objects in images or mastering video games in a matter of hours. This guide outlines the end-to-end deep learning process implemented on Amazon Web Services (AWS). We discuss challenges in executing deep learning projects, highlight the latest and greatest technology and infrastructure offered by AWS, and provide architectural guidance and best practices along the way. This paper is intended for deep learning research scientists, deep learning engineers, data scientists, data engineers, technical product managers, and engineering leaders.

The European Union’s new regulatory framework for data protection laws, the General Data Protection Regulation (GDPR), became enforceable on 25 May, 2018. Under GDPR, organisations have new obligations to improve the security and privacy practices for the personal data they collect and use. With these new obligations comes the potential for heavier fines and penalties. Fortunately, Amazon Web Services (AWS) can help guide your organisation toward compliance under the new requirements. Take advantage of our services, resources, and experts as you navigate these changes.

City leaders around the world are working to improve the quality of life and increase the number of useful services for their citizens, businesses, and visitors. Smart city initiatives are gaining attention in several countries, as administrators, industry, and citizens are working together to enhance their communities, cities, regions, and nations. After more than ten years of smart city hype, innovative projects have emerged, but few have provided a disruptive impact on the city system itself. Because every city is different, few of the existing models apply universally. An effective response requires leaders to consider a series of prerequisites: consider the local culture and the people, prioritize basic needs and requests, work at overcoming silos and encourage collaboration across departments, and consider each “smart” initiative as an integral part of an overall city system. A smart city reflects a number of aspirations: efficiency, resiliency, connectedness, innovation, and su

This paper examines how cities are using cloud technology to address public challenges, using the framework of the global coalition, Smart Cities Council. This framework promotes three core values for smart cities: livability, providing clean, healthy living conditions without pollution and congestion; workability, providing an enabling infrastructure (energy, transportation, internet connectivity) and high-quality jobs; and sustainability, doing so at no cost to future generations, as the Council puts it. This paper proposes a fourth core value, inclusivity: provisioning services to all city residents regardless of their background.

Government agencies often look to promote new technology for cost-savings and efficiency, but it does not stop there. The second and third-tier effects of technology can be long lasting for citizens, businesses, and economies. When public institutions adopt the cloud, they experience an internal transformation. Inside an organization, cloud usage drives greater accessibility of data and information sharing, increases worker productivity, and improves resource allocation. The external benefit of the cloud is recognized through a government’s ability to put reclaimed time and resources toward serving citizens. This includes provisioning public services, such as occupational-skills training, quicker and more effective service delivery, a pathway to a more productive workforce, and ultimately, a boost to local development. This whitepaper examines the enterprise-level benefits of the cloud, as well as the residual impact on economic development. The U.S. Economic Development Administration

In January 2016, the Federal Risk and Authorization Management Program released a draft of its high-impact baseline for moving federal data to the cloud. Not long after, Amazon Web Services (AWS) accepted an offer to pilot the new security threshold. AWS worked with FedRAMP to develop a set of standards under which highly sensitive government data could securely migrate into cloud environments. If ever you doubted that cloud computing was the new frontier for federal data and software management, look around. Over 2,300 government agencies worldwide have already migrated to the AWS Cloud. And in the U.S., this will only increase with the release of FedRAMP’s high baseline standards. Previously, CSPs could only become certified at a low or moderate baseline under FedRAMP, meaning agencies had no security baseline from which to spring their sensitive data into the cloud. These new standards effectively represent the fall of the final formal barrier to federal cloud computing. Terabytes o

Amazon Web Services (AWS) provides rapid access to flexible and low-cost IT resources. With cloud computing, public sector organizations no longer need to make large upfront investments in hardware, or spend time and money on managing infrastructure. The goal of this whitepaper is to help you gain insight into some of the financial considerations of operating a cloud IT environment and learn how to maximize the overall value of your decision to adopt AWS.

This document provides information to assist customers who want to use AWS to store or process content containing personal data, in the context of common privacy and data protection considerations. It will help customers understand: the way AWS services operate, including how customers can address security and encrypt their content, the geographic locations where customers can choose to store content, and the respective roles the customer and AWS each play in managing and securing content stored on AWS services.

Amazon Web Services (AWS) offers scalable, cost-efficient cloud services that public sector customers can use to meet mandates, reduce costs, drive efficiencies, and accelerate innovation. The procurement of an infrastructure as a service (IaaS) cloud is unlike traditional technology purchasing. Traditional public sector procurement and contracting approaches that are designed to purchase products, such as hardware and related software, can be inconsistent with cloud services (like IaaS). A failure to modernize contracting and procurement approaches can reduce the pool of competitors and inhibit customer ability to adopt and leverage cloud technology.

Innovation requires many ingredients: a great idea, creativity, persistence, the right data, and technology. Governments around the world are taking advantage of the cloud to reduce cost and transform the way they deliver on their mission. The expectations of an increasingly digital citizenry are high, yet all levels of government face budgetary and human resource constraints. Cloud computing (on-demand delivery of IT resources via the Internet with pay-as-you-go pricing) can help government organizations increase innovation, agility, and resiliency, all while reducing costs. This whitepaper provides guidelines that governments can use to break down innovation barriers and achieve a digital transformation that helps them engage and serve citizens.

DigitalOcean commissioned Cloud Spectator to evaluate the performance of virtual machines (VMs) from three different Cloud Service Providers (CSPs): Amazon Web Services, Google Compute Engine and DigitalOcean. Cloud Spectator tested the various VMs to evaluate the CPU performance, Random Access Memory (RAM) and storage read and write performance of each provider’s VMs. The purpose of the study was to understand Cloud service performance among major Cloud providers with similarly-sized VMs using a standardized, repeatable testing methodology. Based on the analysis, DigitalOcean’s VM performance was superior in nearly all measured VM performance dimensions, and DigitalOcean provides some of the most compelling performance per dollar available in the industry.

As organizations expand their cloud footprints, they need to reevaluate and consider who has access to their infrastructure at any given time. This can often be a large undertaking and lead to complex, sprawling network security interfaces across applications, workloads, and containers. Aporeto on Amazon Web Services (AWS) enables security administrators to unify their security management and visibility to create consistent policies across all their instances and containerized environments. Join the upcoming webinar to learn how Informatica leveraged Aporeto to create secure, keyless access for all their users.

Delivering complex, enterprise applications requires careful planning and execution to avoid common challenges when scaling. The XebiaLabs DevOps Platform's end-to-end release pipeline orchestration provides the reliability and repeatability needed to overcome those obstacles while deploying on Amazon Web Services (AWS). In this on-demand webinar, XebiaLabs will explore five ways to scale and streamline application deployments on AWS and hybrid environments.

The goal of this review is to educate customers on the capabilities that Cisco’s SD-WAN solution provides when working with Amazon Web Services (AWS). ESG describes Cisco’s solution and highlights the business value it can deliver to customers via its integration with AWS. ESG completed this summary as part of an AWS-commissioned report to review nine SD-WAN vendors. Readers should use this review as a starting point when investigating how they can leverage the combination of AWS and Cisco for business advantage. I would like to receive email communications about products & offerings from Cisco & its Affiliates. I understand I can unsubscribe at any time. For more information on how Cisco collects and uses personal information, please see the Cisco Online Privacy Statement.

The Cloud, once a radical idea in IT, is now mainstream. Whether it’s email, backup or file sharing, most consumers probably use a cloud service or two. Similarly, most IT professionals are familiar with cloud service providers such as Amazon, Google and Microsoft Azure, and many companies have moved at least some of their information technology processes into the cloud. In fact, the cloud has become so popular it’s easy to assume that running IT applications on-premises is not cost competitive with a cloud based service. In this report Evaluator Group will test the validity of that assumption with a TCO (Total Cost of Ownership) model analyzing a hyperconverged appliance solution from HPE and a comparable cloud service from Amazon Web Services (AWS).

For many companies the appeal of the public cloud is very real. For tech startups, the cloud may be their only option, since many don’t have the capital or expertise to build and operate the IT systems their businesses need. Existing companies with established data centers are also looking at public clouds, to increase IT agility while limiting risk. The idea of building-out their production capacity while possibly reducing the costs attached to that infrastructure can be attractive. For most companies the cloud isn’t an “either-or” decision, but an operating model to be evaluated along with on-site infrastructure. And like most infrastructure decisions the question of cost is certainly a consideration. In this report we’ll explore that question, comparing the cost of an on-site hyperconverged solution with a comparable set up in the cloud. The on-site infrastructure is a Dell EMC VxRailTM hyperconverged appliance cluster and the cloud solution is Amazon Web Services (AWS).

One of the value propositions of an Internet of Things (IoT) strategy is the ability to provide insight that was previously invisible to the business. But before a business can develop a strategy for IoT, it needs a platform that meets the foundational principles of an IoT solution. Amazon Web Services (AWS) believes in some basic freedoms that are driving organizational and economic benefits of the cloud into businesses. These freedoms are why more than a million customers already use the AWS platform to support virtually any cloud workload. These freedoms are also why AWS is proving itself as the primary catalyst to any Internet of Things strategy across commercial, consumer, and industrial solutions. This paper outlines core tenets that should be considered when developing an IoT strategy, the benefits of AWS in that strategy and how the AWS cloud platform can be the critical component supporting those core tenets.

Les technologies d'intelligence artificielle telles que l'apprentissage machine et le Deep Learning permettent d'obtenir des informations et de la précision à deux marques majeures dans des secteurs très différents : la santé et les assurances. Des théories sur les futures incidences de l'intelligence artificielle (IA) sur les entreprises et la société vont florissantes. Mais la réalité du terrain aujourd'hui pour les entreprises et les dirigeants appliquant des technologies comme l'apprentissage machine et l'apprentissage profond à leurs enjeux majeurs est déjà très enthousiasmante. Les modèles de fonctionnement sont refondés en se basant sur les informations obtenues de puissantes capacités cognitives. De nouveaux produits et services améliorent l'expérience client, voire la condition humaine. D'une façon très concrète et significative, l'IA change le monde pour le meilleur.

AI-Technologien wie Machine Learning und Deep Learning liefern zwei großen Marken in zwei sehr unterschiedlichen Branchen – Gesundheit und Versicherungen – Insights und Genauigkeit. Theorien zu den zukünftigen Auswirkungen künstlicher Intelligenz (AI) auf die Geschäftswelt und die Gesellschaft sind allgegenwärtig. Aber die Realität, wie Unternehmen sie kennen, die Technologien wie Machine Learning und Deep Learning anwenden, ist schon aufregend genug. Geschäftsmodelle werden anhand der Insights umgestaltet, die durch die leistungsstarken kognitiven Funktionen generiert werden. Neue Produkte und Dienstleistungen verbessern das Benutzererlebnis – um nicht zu sagen die menschliche Existenz. Auf sehr reale und bedeutsame Weise verbessert AI die Welt.

What is a Data Lake? Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.

Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes. This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.