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
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
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
"ESG compared Google BigQuery’s serverless Enterprise data warehouses (EDW) solution with some alternative EDW services offered by AWS, Microsoft, and Snowflake. While all of these offerings provide significant cost savings, reduction in complexity, and increased business agility when compared with an on-premises EDW solution, there are some significant differences between the offerings.
Read The Economic Advantages of Google BigQuery versus Alternative Cloud-based EDW Solutions to learn more.
Container adoption continues to grow as organizations look to transition from virtual machines to microservices-based architectures, known for their increased efficiency, portability, and scalability. But while containers afford an additional layer of security through their ability to isolate applications, a containerized environment is still susceptible to malicious attacks between containers or the within the shared resources of the underlying host.
Download this eBook to learn how you can develop a stronger security strategy for your AWS container deployments, from start to finish. Key takeaways include:
• Planning for maximum portability
• Setting permissions for users and system resources
• Creating an action plan based on log monitoring and IDS data
Published By: Rackspace
Published Date: Nov 06, 2019
In this hands-on guide, our AWS Amazing Minds share advice on how to navigate and optimise your cloud journey on AWS, tackling the 9 most common questions around upskilling on AWS, automation, DevSecOps, customised cloud and more.
Our customers were the catalyst for creating the Amazing Minds series. Independent research combined with insights from our day-to-day business interactions, told us unequivocally that they wanted to be part of the journey. We also know that a secure and high-performing cloud journey is at its best when it’s a shared experience.
Download the guide to see how you can achieve how performance outcomes on AWS and save time and money whilst doing so.
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.
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.
Countless studies and analyst recommendations suggest the value of improving security during the software development life cycle rather than trying to address vulnerabilities in software discovered after widespread adoption and deployment. The justification is clear.For software vendors, costs are incurred both directly and indirectly from security flaws found in their products. Reassigning development resources to create and distribute patches can often cost software vendors millions of dollars, while successful exploits of a single vulnerability have in some cases caused billions of dollars in losses to businesses worldwide. Vendors blamed for vulnerabilities in their product's source code face losses in credibility, brand image, and competitive advantage.
A forward-looking CMDB does more than keep an organization's IT operations running. It draws clear connections between IT components and business services, which is the core of Business Service Management (BSM). But even more critical than the CMDB's ability to support business as it is now, is the question of how well it will drive business innovation in the future.
Over the last several years, DigitalOcean has built out its feature set in a way that has taken it from a provider of cheap and simple virtual machines (VMs) to a legitimate public cloud alternative, most recently adding support for Redis and MySQL to its managed database services. As its services evolve, it continues to experience healthy growth and maintain popularity among the independent developer audience. Over the past two years, DigitalOcean has accelerated the velocity of its feature development, looking to better meet the needs of a business audience. By emphasizing a simplified feature set, pricing structure and user experience, even as it expands its competitive footprint in the shadow of public cloud vendors such as Amazon Web Service (AWS), Microsoft Azure and Google Cloud Platform (GCP), Digital Ocean continues to help define what it means to be an alternative public cloud in a market dominated and largely defined by hyperscalers.
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.
Published By: Cisco EMEA
Published Date: Jun 19, 2019
The EU’s General Data Protection Regulation (GDPR) became enforceable on May 25, 2018, and privacy laws and regulations around the globe continue to evolve and expand.
Most organizations have invested, and continue to invest, in people, processes, technology, and policies to meet customer privacy requirements and avoid significant fines and other penalties. In addition, data breaches continue to expose the personal information of millions of people, and organizations are concerned about the products they buy, services they use, people they employ, and with whom they partner and do business with generally.
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.
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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).
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time.
AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance.
In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences.
Join this webinar to learn:
How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development.
How AWS supports BI solutions f
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time.
This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
Amazon Redshift Spectrum—a single service that can be used in conjunction with other Amazon services and products, as well as external tools—is revolutionizing the way data is stored and queried, allowing for more complex analyses and better decision making.
Spectrum allows users to query very large datasets on S3 without having to load them into Amazon Redshift. This helps address the Scalability Dilemma—with Spectrum, data storage can keep growing on S3 and still be processed. By utilizing its own compute power and memory, Spectrum handles the hard work that would normally be done by Amazon Redshift. With this service, users can now scale to accommodate larger amounts of data than the cluster would have been capable of processing with its own resources.